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Ways to prepare yourself for the future of work: AI vs Jobs

The impact of Artificial Intelligence (AI) on jobs is a debated topic across the globe. While it has led to a technological revolution in different fields, one cannot deny the concerns it raises about job displacement across various industries and occupations. AI has the potential to automate various tasks and, at the same time, create new job opportunities. But, if you have pursued a good BA or MA degree course from a top-notch university, you need not worry about AI taking away your job.

AI tools or systems are based on deductive reasoning and thus and can only recreate from the information and data uploaded by humans in the search engines. AI struggles to replicate human creativity, critical thinking, emotional intelligence, and a profound understanding of language and literature.  Hence, AI can never be as effective in storytelling, communication, or interpretation. The risk of it snatching away the creative jobs is very low because AI acts as a deductive intelligence using information that humans feed it with; it uses established rules, principles or knowledge to deduce conclusions.

Continue reading to explore how an MA in English graduate can thrive in the era of AI, forging a path with the richness of literature and language while embracing the transformative power of technology. 

Is AI causing a major threat? 

No doubt, Artificial Intelligence (AI) has made a significant impact over the last few years by reducing human effort with automation. There are still various aspects related to several jobs that AI cannot take over. Human caliber is deeply rooted in creativity and abilities like critical thinking, literary analysis, emotional intelligence, experience, and empathy, and Artificial Intelligence is still struggling to master these areas. Hence, AI so far, is not causing a major threat to humans in various job roles. 

The table below will enlighten you with some areas where AI can still not beat the skills required for creative jobs:

ParameterExplanation
Content writingGenerating creative content using innovative ideas specific to certain themes for a target audience is a task best done by experienced human writers and not any AI tool
Critical analysisAlthough AI has shown  remarkable excellence in data analysis, it somehow still lacks the depth of critical understanding and interpretation that comes from a human mind 
Communication skillsAI, as we all know is all about artificial intelligence, and therefore it lacks the emotional intelligence required to communicate with empathy in creative professions such as journalism, teaching, and counseling
Ethical decision-makingCreative jobs such as publishing and editing need ethical decision-making skills that can never be fulfilled by an AI system, so these are professions that need not worry about AI as a threat
Language adaptabilityCreative professions that need language adaptability such as translation, interpretation and consultation are still best dealt by humans and not by any AI tool

AI vs creative jobs in English & Literature 

Artificial Intelligence (AI) is indeed a powerful tool that helps creative minds working in different jobs after an MA in English. However, AI can never threaten creative jobs in English literature. The unique blend of skills and expertise that an MA in English graduate brings to the table can never be the same as that brought by artificial intelligence. 

Have a look at some areas where AI will fail to pose a threat to an MA in English graduate in terms of jobs:

  1. Literary analysis: Whether you agree or not, AI cannot pose a threat to an MA English graduate who has mastered the art of literary analysis and critical thinking. To interpret the literature, you need human understanding and empathy, which AI lacks.
  1. Teaching: No AI can bond personally with students as a human teacher, so it is evident that teaching is one profession where AI may assist but cannot pose a threat. AI modes cannot replace human educators. 
  1. Creative writing: AI is massively used for creative writing, but human writers are incomparable when it comes to producing original and authentic content capturing human experience and emotions. 
  1. Human relations and communications: Jobs related to human relations, such as HR or PR management, rely on interpersonal skills and emotional intelligence rather than on artificial intelligence. 
  1. Speechwriting: AI will somehow be unable to craft persuasive speeches for specific audiences. This is an area that needs a human understanding of the nuances of rhetoric and emotional intelligence instead of artificial intelligence.

How the way of work is going to change 

The simple formula to sustain the threat posed by AI is by staying abreast with the latest technologies and being open to continuous learning. Besides, one needs to be more adaptable and ready to acquire new skills to meet the changing demands of a dynamic and AI-integrated workplace. 

Listed below are some ways in which the work is going to change after the implementation of AI in various jobs:

  1. Upskill your knowledge: It is of utmost importance to be open to upskilling and learning new skills when it comes to preparing yourself for the future of work. Identify skills that will complement AI, such as creativity, emotional intelligence, and critical thinking. 
  1. Embracing technology: Try to familiarize yourself with the emerging technologies in the industry you belong to. At the same time, learn to use AI tools and systems and how these can be used to enhance your job rather than view them as a threat. 
  1. Strong networking: Those who wish to sustain the challenges in the way work will take place in the changing job scenario must be open to networking to get new opportunities. In short, building and maintaining a robust professional network is crucial. 
  1. Be adaptable: An adaptable mindset is invaluable for any job type in the current scenario. One should be open to new roles and responsibilities in the changing job landscapes. Try not to restrict yourself to only one kind of role; look for change and be flexible to adjust to each new role.
  1. Remote work skills: Last but not least, you must hone your skills to work from remote spaces and gel well in a flexible work arrangement. For this, develop strong communication and collaboration skills in virtual environments.

Conclusion

To sum up, AI might help accelerate the creativity aspects needed in a job, but it cannot replace the expertise that an MA in English graduate might bring to the same job. One must take the coexistence of AI and human workers as a complementary factor rather than assuming AI is a threat. After all, it is Artificial Intelligence that has made us realize the need to adapt and acquire new skills. Be it the depth of understanding the English literature language or the essence of creative endeavors, a UGC-entitled degree, Robust SMU alumni, expert faculty, and attractive scholarships are some of the key benefits to reap by choosing Sikkim Manipal University to pursue an online MA in English degree program through Online Manipal platform.

Sikkim Manipal University offers a globally recognized online MA in English, that is also affordable. SMU also offers easy financing options like fee concessions and scholarship opportunities for eligible candidates, which can reduce the financial burden for learners.

Tools covered in MAHE’s PGCP business analytics

In the digital world, technology undergoes constant changes, making informed decisions indispensable. Therefore, we need data scientists to identify these changes and locate their patterns. It helps different businesses and industries make better product and service choices. Moreover, a data scientist should be proficient in statistics, machine learning, and programming languages or tools. They manipulate and analyze data sets and keep up with changes in these tools.

The blog describes different tools in MAHE’s PGCP Business Analytics program that analysts should learn. Let’s dive in!

Also read- What is Business Analytics: An overview – Online Manipal

The Post Graduate Certificate Program (PGCP) in Business Analytics encompasses a comprehensive study of various tools and technologies that are instrumental in extracting valuable insights from data. Here are the learning tools in MAHE’s Business Analytics PGCP:

Microsoft Excel

  1. The program’s intuitive design and extensive online resources make it relatively easy for individuals to learn and apply analytical techniques. It is an ideal tool for professionals seeking to enhance their analytical capabilities without a steep learning curve.
  2. Microsoft Excel is extensively used for data analysis, reporting, and visualization. Its powerful features, such as pivot tables, charts, and functions, enable users to efficiently manipulate and analyze large datasets.
  3. Analysts leverage Excel for financial modeling, budgeting, forecasting, and trend analysis tasks. The tool’s ability to handle statistical functions allows professionals to conduct data-driven decision-making.
  4. Many organizations use Excel as a primary data analysis and reporting tool regardless of size or industry. Its compatibility with various data sources and the prevalence of Excel proficiency in the workforce contribute to its enduring popularity.

Python

  1. Python is renowned for its simplicity and readability, making it accessible to individuals with diverse backgrounds.
  2. It supports libraries and frameworks, such as Pandas, NumPy, and Scikit-Learn, essential for data manipulation, analysis, and machine-learning tasks. 
  3. Python is extensively employed for data cleansing, exploratory data analysis (EDA), statistical analysis, and predictive modeling. Its versatility allows professionals to extract actionable insights from large datasets, facilitating data-driven decision-making processes.
  4. The popularity of Python in business analytics is increased by its role in emerging technologies such as artificial intelligence (AI) and machine learning (ML).

Also read- Scope for business analytics grads in emerging economics – Online Manipal

R

  1. The language is open-source, and a vibrant community contributes to its continuous improvement. The availability of numerous online resources, tutorials, and forums facilitates learning for individuals enrolled in the PGCP Business Analytics program.
  2. The language supports various data manipulation and statistical techniques, enabling professionals to handle complex data sets efficiently. R’s compatibility with other programming languages and databases allows seamless integration into existing analytics workflows.
  3. R offers a comprehensive toolkit for professionals to extract meaningful insights from data.
  4. Many finance, healthcare, and e-commerce organizations leverage R for data analysis and decision support.

SSPS

  1. The program employs a point-and-click approach, reducing the need for extensive coding or programming skills. This characteristic makes SPSS an excellent choice for business analytics beginners who need a statistics or programming background.
  2. Participants learn how to import, clean, and manipulate data using SPSS and perform statistical analyses, from basic descriptive statistics to advanced predictive modeling. The course emphasizes hands-on exercises and real-world case studies to ensure learners gain practical experience.
  3. Participants in the PGCP program explore how SPSS can be employed to identify trends, make predictions, and derive valuable insights from data sets. The tool’s versatility allows for the analysis of structured and unstructured data.

Also read- Commerce to Business Analyst: What does the learning journey look like? – Online Manipal

Tableau

  1. This tool’s drag-and-drop functionality allows users to create visualizations without extensive coding knowledge. The platform also provides tutorials, online forums, and documentation, facilitating a smooth learning curve for beginners.
  2. It can transform complex datasets into easily understandable visualizations, fostering better decision-making.
  3. The tool supports real-time data connections, enabling users to make data-driven decisions promptly. It offers scalability, accommodating small and large enterprises in implementing analytics solutions tailored to their requirements.
  4. Professionals utilize Tableau for financial reporting and trend analysis in finance. Marketing teams employ the tool for visualizing customer behavior and campaign performance. Healthcare organizations leverage Tableau to analyze patient data and optimize operational processes. 

SQL

  1. The language is designed to be user-friendly, allowing both beginners and experienced professionals to use it easily. The syntax and the ability to retrieve, manipulate, and analyze data make SQL a valuable tool for anyone looking to harness the power of data.
  2. It is the standard language for interacting with relational database systems, such as MySQL, PostgreSQL, Microsoft SQL Server, and Oracle.
  3. Professionals proficient in SQL can extract valuable database insights and perform data cleaning and transformation. It is extensively used in data warehousing, business intelligence, and analytics projects.
  4. Every organization dealing with data relies on SQL to manage and query databases. Its widespread use is evident in job descriptions for roles such as data analyst, business analyst, and data scientist.

Why master Business Analytics with MAHE?

The Post Graduate Certificate Program (PGCP) in Business Analytics provided by MAHE is structured to equip students with the necessary skills and knowledge to navigate the complexities of modern business data. The program spans over 12 months, allowing participants to delve deep into the subject matter and gain a thorough understanding of various analytics tools and techniques.

With a suggested dedication of 15-20 hours per week, students can tailor their learning experience according to their schedules. The course fee is INR 65,000 per semester, with a total program cost of INR 1,30,000. MAHE provides an option for monthly installments, with an EMI starting as low as INR 10,833.

Moreover, the institution has included free access to paid Coursera content. This partnership expands the learning resources available to participants to complement the program’s curriculum.

Conclusion

In conclusion, the analytics tools taught in MAHE’s PGCP program in Business Analytics represent a comprehensive and cutting-edge array of resources. It empowers students with the skills and knowledge needed to thrive in the dynamic field of business analytics. Therefore, participants are exposed to diverse tools that cater to various aspects of data analysis, visualization, and interpretation throughout the program.

Also read- Six reasons why you should pursue a master’s degree in business analytics – Online Manipal

Popular AI-assisted data analytics tools of 2024

Data science has become the most critical and valuable force in this modern world. It is beneficial for businesses to make informed decisions. This field of data science relies heavily on AI and data analytics. In the future, applying artificial intelligence and data science will expand the advancement opportunities in all industries.

Data sets are becoming vast and complex. The complex information from these data sets can be broken down through these machine learning algorithms. Big data has enabled businesses to adopt sophisticated analysis processes to generate meaningful insights. This shift of advanced analytic systems was pivotal, providing a foundation to build on sophisticated machine learning algorithms.

The blog has listed notable AI-powered tools for data analytics in 2024. Let’s dive in!

What is AI Data Analysis?

AI data analysis refers to applying artificial intelligence (AI) techniques to process and interpret vast data sets, uncovering meaningful insights and patterns. Here are some use cases:

  • Repetitive and time-consuming tasks involved in data processing can be automated through machine learning and other AI-driven approaches.
  • AI helps organizations understand the underlying structures in their data by identifying trends, correlations, and anomalies.
  • AI models can predict future trends and events by utilizing historical data and learning from patterns.
Job TitleAverage Data Science Salary (INR)
Core Data Scientist₹ 8.24 LPA
Data Analyst₹ 6 LPA
Data Engineer₹ 11.4 LPA
Data Architect₹ 21.46 LPA
Data Manager₹ 12.43 LPA

Source

Bengaluru maintains its position as the foremost center for data science and analytics employment, comprising 26% of such jobs. However, there has been a marginal decrease from the 29% recorded in 2022.

How to Use AI for Data Analysis?

A. Defining Objectives for AI-Driven Analysis

Identify the specific goals and outcomes you aim to achieve by applying artificial intelligence. This initial step sets the foundation for the entire process and ensures the subsequent stages align with the analysis’s overarching purpose.

B. Data Collection and Preparation

Ensure the data sources are reliable, relevant, and comprehensive. It may involve cleaning and preprocessing the data to handle missing values, outliers, and inconsistencies.

C. Selection of AI Techniques Based on Analysis Goals

Whether it’s machine learning, deep learning, or natural language processing, the selection should be tailored to address the specific requirements of the analysis.

D. Model Training, Evaluation, and Deployment

This step involves feeding the algorithm with historical data to learn patterns and relationships. Subsequently, evaluate the model’s performance using validation datasets to ensure its effectiveness and generalization.

E. Feature Extraction, Engineering, and Ethical Considerations

Identify relevant features contributing to the analysis and consider creating new features to capture additional insights. Moreover, ethical considerations, such as bias in data or model predictions, should be addressed.

F. Continuous Improvement and Refinement

Implement mechanisms for ongoing refinement based on new data, changing objectives, or emerging trends. Regularly update models to adapt to evolving patterns and maintain the accuracy and relevance of the analysis.

The Relationship Between AI and Data Analysis

A. Revolutionizing Data Analysis with AI

With its advanced algorithms and computational power, AI has emerged as a game-changer in handling and interpreting vast datasets. Machine learning algorithms, a subset of AI, enable systems to learn from data patterns and make predictions or decisions.

B. Real-Time Insights and Predictive Capabilities

AI systems can analyze data in real-time, enabling organizations to make informed decisions promptly. Predictive analytics powered by AI algorithms allows businesses to forecast trends, identify potential opportunities, and mitigate risks.

C. Consistency, Accuracy, and Adaptability in AI Data Analytics

Algorithms are designed to follow predefined rules and execute tasks consistently, leading to more reliable outcomes. Moreover, AI systems continually learn and adapt, refining their models based on new data inputs.

Top 10 AI Data Analysis Tools

Below are the tools combining AI and analytics for 2024:

A. RapidMiner

  • RapidMiner is a powerful AI data analysis tool known for its robust tools for data preparation, machine learning, and predictive modeling.
  • RapidMiner provides flexible pricing plans, including a free primary-use version. It offers a user-friendly interface and is accessible to a broad audience.

B. Tableau

  • Tableau is renowned for its dynamic dashboards and powerful data visualization capabilities.
  • It incorporates AI through features like Ask Data, enabling users to pose natural language questions to the data and receive instant visual responses.
  • Tableau offers various pricing options, including both on-premise and cloud-based solutions.

C. Microsoft Azure Machine Learning

  • Microsoft Azure Machine Learning is a cloud-based platform providing a versatile environment for developing and deploying machine learning models.
  • The tool’s strength lies in its integration with the broader Azure ecosystem. 
  • Microsoft Azure Machine Learning offers flexible pricing based on usage, with options for pay-as-you-go or pre-paid plans.

D. KNIME

  • KNIME is an open-source toolkit that offers comprehensive tools, including machine learning, blending, and transformation capabilities.
  • KNIME is free to use.

E. Google Cloud AutoML

  • Google Cloud AutoML simplifies machine learning model development by providing pre-built components and automation tools. 
  • The tool features a user-friendly interface with drag-and-drop functionalities.
  • Google Cloud AutoML follows a pay-as-you-go pricing model.

F. PyTorch

  • PyTorch is a popular open-source machine learning framework, especially known for its focus on deep learning.
  • PyTorch offers extensive tools and libraries for researchers and developers.
  • PyTorch is free and open-source, aligning with the philosophy of community-driven development.

G. DataRobot

  • DataRobot specializes in automated machine learning, allowing users to build, deploy, and manage machine learning models with minimal manual intervention.
  • DataRobot focuses on real-world business applications and predictive analytics.
  • DataRobot’s pricing model involves a combination of licensing fees and usage-based charges.

H. Talend

  • Talend is known for its data integration and administration prowess.
  • Talend’s capabilities extend to managing big data channels, suitable for organizations dealing with large volumes of diverse data.
  • Talend offers various pricing options, including open-source and subscription-based models.

I. H2O.ai

  • H2O.ai is an open-source platform focusing on machine learning and predictive analytics.
  • It incorporates automated machine learning features.
  • H2O.ai is freely available. 

J. IBM Watson Analytics

  • IBM Watson Analytics is a cloud-based tool that excels in data mining and predictive analytics.
  • It can generate automated insights and perform predictive modeling.
  • IBM Watson Analytics offers flexible pricing options.

How does MAHE help you realize your Data Science career dreams?

Manipal Academy of Higher Education (MAHE) is pivotal in realizing your career aspirations through its comprehensive MSc Data Science program. The program is designed to provide a deep understanding of the intricacies of data science, equipping students with the necessary skills to thrive in the rapidly evolving field. 

The curriculum covers various subjects: statistical analysis, machine learning, data visualization, and big data technologies. The institution provides hands-on experience with industry-relevant tools such as Python, R, SQL, and Hadoop.

Conclusion

In conclusion, the AI-assisted data analytics tools in 2024 showcase the relentless progress and innovation within the field. The tools discussed include various platforms, from established giants to emerging startups. These tools underscore the dynamic nature of the data analytics ecosystem. Therefore, integrating artificial intelligence is pivotal in enhancing analytical capabilities, uncovering insights, and driving informed decision-making.

Celebrating the historic convocation of MUJ’s first batch of online graduates

A picturesque campus on a beautiful winter morning in Jaipur, a jubilant vibe, and air buzzing with excitement. It was a historic day on December 9, 2023, for Manipal University Jaipur, as the first online batch of MBA and MCA students graduated with flying colors.

The grand Convocation procession by Manipal University Jaipur’s faculty

It was a truly special occasion, as these online students marked history by being the first batch to complete their online degrees from MUJ, which are recognized at par with on-campus degrees.  

The convocation, a momentous occasion, unfolded in the beautiful surroundings of the MUJ campus. The convocation marks the culmination of the journey of these students who commenced their study in April 2021. A total of 969 students marked this milestone in their academic journey. Among them, several graduates adorned their best attires and graced the MUJ campus with their presence for the in-person convocation. The rest of the achievers, who couldn’t make it in person, will receive their well-deserved certificates both digitally and in hard copy.    

Dr GK Prabhu, President, MUJ (left) and Mr Ambrish Sinha, CEO, UNext Learning (right) conferring degree certificate to a learner
Online graduates celebrating their milestone

The vibe was energetic as the first batch of online graduates explored the campus in the morning and met their peers. Soon after they were served a lavish buffet lunch, students headed to a state-of-the art auditorium, all set to receive their degree certificates. The convocation kicked off with a procession by the dignitaries- Dr G K Prabhu, President, Manipal University Jaipur, Cmde (Dr) Jawahar M Jangir, Pro President, MUJ, Dr Mallikarjuna Gadapa, Director, Center for Distance and Online Education, MUJ, and Mr Ambrish Sinha, CEO, UNext Learning. The Chief Guest was Dr Nalin Mehta, Managing Editor at Moneycontrol, a leading media and news company in India.  

Dignitaries who graced the event with their presence

Dr G K Prabhu addressed the first batch of online graduates and said, “Today marks a momentous occasion as you step into the next chapter of your lives. As you embark on new adventures, remember the knowledge and skills that you have gained here and use them to make a positive impact on the world. May you continue to learn, grow, and inspire those around you.” 

Speaking about the grand success of the convocation, Dr Mallikarjuna Gadapa, Director, Online Education, MUJ, said, “In the digital era, online degrees from Manipal University Jaipur help learners unlock future potential while not giving up on their present commitments and work. By offering quality education in the virtual realm, we are not only shaping minds but also revolutionizing the job landscape, ensuring that our graduates stand shoulder to shoulder with their peers, armed with skills that transcend traditional limitations.” 

Congratulating the online graduates, the Chief Guest, Dr Nalin Mehta, Managing Editor at Moneycontrol, said, “I was amazed to hear about the length and breadth and width of this cohort- ranging from early twenties to almost sixty. That is testament to the kind of opportunities this program has created. This first batch is historic not just for Manipal University Jaipur, but also for the nation at large.” 

The convocation ceremony was a testament to the meticulous planning and execution by the university. Every detail was well thought out, ensuring a seamless and memorable experience for the graduates. From the moment the students entered the campus to the heartfelt speeches delivered on the stage, the event was a symphony of accomplishment and pride. 

Online graduates taking the oath

For the 229 students who graced the campus, the day was marked by the thrill of crossing the stage, shaking hands with faculty members, and receiving their hard-earned degrees. What made this convocation even more special was the diversity of the graduating class. Students from diverse backgrounds came together, forming connections that will last a lifetime. The online graduates comprised of fresh graduates and working professionals from over 70+ fields like defense services, entrepreneurs, freelancers, etc. 

Batch photo of first online graduates of MBA & MCA, Manipal University Jaipur

Here’s what the online graduates had to say after receiving their degrees. 

Aritraa Chatterjee, online MBA 

“I did not expect so many people to attend the convocation. I got the opportunity to network with my peers here. I would like the future online graduates to also attend this event, as it is a one-time opportunity.” 

Taniya Kulkarni, online MCA 

“It was a wonderful experience, and we are proud to be the first batch of online graduates at MUJ.” 

Not just the online learners, but the faculty too were super excited to meet their students, who they have met only in online sessions for the last two years. The faculty members expressed joy and happiness in meeting the first batch of online learners. 

Mr Abhishek Pandey, Assistant Professor, Manipal University Jaipur, said “I congratulate the learners on achieving this incredible milestone. It is a very special day for Manipal University Jaipur because we’re celebrating the first ever convocation of online learners. Learners are stepping into a new journey in their lives. The knowledge, technical skills, communication skills, collaboration skills, and the effort to continuously gain knowledge will help learners face real-life challenges.” 

CS Arpita Agarwal, Assistant Professor, Manipal University Jaipur, said, “This is a special occasion for all learners as they are entering the practical world. Change is the only constant. Our learners are trailblazers who have proven that learning knows no boundaries. Our very dear online learners are all set to face the world with confidence.” 

As the sun set on the day of the convocation, the campus stood witness to not just an academic ceremony, but a celebration of achievements, friendships, and the indomitable spirit of learning. 

Is Python necessary for learning data science?

Because of its simplicity and ease of use, Python for data science is one of the most popular programming languages in the scientific and research domain. People without engineering backgrounds can easily learn how to use it because of its simplicity and large libraries. Additionally, it works better for rapid prototyping.

AI scientists favour Python as well, with regard to application domains. Developers tended to rely on Java when it came to areas like creating fraud detection algorithms and network security, but they chose Python for data science applications like sentiment analysis and natural language processing (NLP) because it has a large library of tools that make it easier to solve complex business problems and create robust systems. Is Python necessary for learning data science or not? Here we discuss.

What is Python? 

Python is an open-source, interpreted, high-level language that offers excellent object-oriented programming techniques. Data science leverages this language in all their projects and is one of the best languages data scientists can leverage. Python offers excellent capabilities for dealing with arithmetic, statistics, and scientific functions. To cope with data science applications, it offers fantastic libraries. 

The key features of Python 

Despite being a relatively advanced programming language, Python is simple to learn. It can take more time to fully understand Python’s complex concepts, packages, and modules.

  • Simple to read and very easy to learn

Python code resembles everyday English terms. The indentations define the code. Due to its simplicity of learning, Python is the perfect tool for novice programmers. It gives programmers the benefit of using fewer lines of code than one to complete tasks. In other words, it is more like playing with it than working with the codes. 

  • Free and open source

Python is created under an open-source licence that OSI has accepted. It can be downloaded and used in applications free of charge. It can be downloaded and used in applications without costing anything. Additionally, it may be freely changed and distributed again. 

  • The same code can be used on multiple devices

The code written once can be applied on several machines, making Python portable. Let’s say you use a Mac to write Python programmes. There are no modifications required to run it later on Windows or Linux.

  • Dynamically typed 

In order to run a programme in any programming language, its type must be declared before a variable can be used. But it is not the same in Python. Here, the type of the variable can be decided during runtime. As a result, Python is now a dynamically typed language.

As an illustration, you don’t need to write int x = 10 when you need to give the integer value of 10 to the variable “x”. Writing x = 10 is all that is required. The fact that Python supports both object-oriented and procedure-oriented programming is one of its key strengths. 

Use cases of Python with examples 

The following use cases speak of the efficiency of Python for data science.

  • Machine intelligence

Python is quite well-liked in the machine learning or AI fields. Despite being an old language, Python has evolved to work with numerous new technologies. Building complex machine learning modules requires a vast array of computations, which Python’s stability makes it capable of handling. 

Some of the well-known libraries provided by Python to work on machine learning and artificial intelligence projects are Sensorflow, Numpy, Keras, and Scikit Learn.

  • Game development

Python also helps with game development, simple AI, and standard web programming. 3D game development is made possible by Python packages like PyGame and PySoy. Additionally, it offers a library for any topic, regardless of your field.

  • Educational sector 

Python is one of the most utilised programming languages for creating educational software and online courses. It is a programming language that is user-friendly for beginners and has a low learning curve and a multitude of resources. Python is a very “readable” language, as was already said, and is frequently used for creating online courses.

The benefits of learning Python as a data scientist

If you learn python for data science, you can unlock the following benefits – 

  • Libraries that can enhance the ease of programming 

The large sum of libraries efficient in the working and improving the ease of the programming is its biggest utility for enabling a data scientist to efficiently finish the hard jobs faster and with fewer rewrites.  As a data scientist, you should be aware of the following crucial libraries that make Python a trustworthy and effective tool for data analysis and visualisation.

  • NumPy assists us with strong multifunctional tools and array objects as one of the most fundamental Python libraries. Many people use NumPy for data analysis. A homogeneous multidimensional array is its main component. 
  • Matplotlib offers effective and stunning visualisations. Several stories can be written utilising the data that Matplotlib has visualised. 
  • Pandas are among the most widely used and favoured libraries for data science. Its intended applications include statistical, engineering, social science, and practical data analysis.  
  • Object and procedure-oriented programming

If data and objects are the main design considerations rather than functions and logic, a programming language is said to be object-oriented. On the other hand, a programming language is procedure-oriented if it emphasises functions (reusable code) more. 

Given that it was created as a high-level programming language for general purpose programming, Python supports both procedural and object-oriented programming. Python is a multi-paradigm, allowing you to create programmes or libraries that are primarily procedural, object-oriented, or functional in any combination of these three areas of programming.

  • A large, helping community 

Leveraging data science using Python has many advantages, one of which is that you’ll have access to a fantastic community of Pythonistas and can even join them. Since it has been around for three decades, Python has been designed to be simple to learn and simple to build with. 

There is a sizable and passionate community of Pythonistas out there. They can always help you and can share their tips, answer your questions, correct your code, and discuss new ideas because it has remained relevant to so many people and businesses for such a long time. You can find them anywhere. 

R vs Python for data science

Both data scientists and analysts use R and Python frequently, but each has a particular purpose in the process. In essence, Python is a general-purpose language utilised across all types of software engineering and data science, whereas R is used specifically for data analysis and statistics. It is generally a hot topic in Python for data science interview questions.

Points of comparisonRPython
Data explorationCan determine general patterns from dataLibraries are used to get insights out of data
Statistical modellingSpecifically built for statistical analysis SciPy is library in Python that is efficient for this
Data visualisationCan produce slick, objective visualisationsThe Matplotlib library of Python is good for this

  • Data exploration

Although, unlike data analysis, data exploration isn’t used to get the most insights out of the data, it is useful in determining general patterns in it. R was natively developed to achieve this, whereas, in Python, there are separate libraries that can be used to have it done without writing a single line of code. 

  • Statistical modelling

The process of developing an appropriate model follows the collection and exploration of your data. The process of building a data model, or collection of abstract rules that specify how data pieces relate to each other, frequently using characteristics of the real world, is known as data modelling. We refer to the process of using models to forecast future data as machine learning.

R and Python can both be utilised for statistical modelling. R was specifically built for statistical analysis i.e. making a paper or report, while Python has much better uses because of its general-purpose programming language. SciPy in Python is used for scientific calculations.

  • Data visualisation

Data visualisation is an intricate task, and poor results may impact the understanding of the visualisation. When it comes to data visualisation, then R is relatively easier, but you can use Python libraries like Matplotlob to generate graphs and charts for your data. R was developed to display the outcomes of its statistical analysis, but one of its greatest capabilities is data visualisation. Because of this, it’s simple to produce slick, objective visualisations.

However, if you decide against learning Python, you could lose out on a number of worthwhile job prospects. 

Master your skills with online MSc in Data Science with MAHE

The online data science programmes offered by Manipal Academy of Higher Education (MAHE) through Online Manipal are a great way to start if you are looking for a lucrative career in the fields of data science and artificial intelligence. Whether you want to work in the industry or move into another field, a data science course taught by experts will help you know how to learn Python for data science. 

The course will enable you to improve your analytical ability and problem-solving techniques and gain a command of several programming languages. For more information, visit the Online Manipal website now!

Know everything: MBA Information Systems vs. MBA Information Technology

In the ever-evolving landscape of business and technology, the intersection of managerial acumen and information sciences plays a pivotal role in shaping the organizational success. Two specialized branches that underscore this dynamic relationship are MBA in Information Systems (MBA-IS) and MBA in Information Technology (MBA-IT). These programs cater to professionals seeking to navigate the complexities of the digital age, yet they differ in their strategic focus and the skill sets they emphasize on. In this exploration, we delve into the nuances of MBA-IS and MBA-IT, shedding light on their distinct characteristics, the unique value they bring to the table, and how each can chart a distinct career trajectory in today’s fast-paced dynamic realm of business and technology.

In MBA Information Systems, students learn about the theory behind computer systems and networks. They also learn to create databases, analyze data, and even design software for various purposes. Students who enter this program will be prepared for IT management or administration careers, as well as any other job that requires an understanding of how computers function at a basic level.

MBA Information Technology students also study the theory behind computer systems and networks and learn how these theories apply to business practices. In addition, students study how companies can use technology more effectively to improve their performance through better organizational strategies or improved communication between departments (such as sales teams). 

Want more detailed information about information systems vs. information technology? Check out our blog on MBA courses details for both the sectors.

What is an MBA in Information Systems?

An MBA specializing in information systems (IS) is a master’s degree that prepares students for careers in the IT field. Students who pursue this degree learn to manage, analyze and develop business processes to ensure that business operations are efficient and effective. This can include managing data security and risk management, developing software systems and applications, and ensuring the integrity of business operations.

The IS specialization within an MBA program prepares graduates to work in various positions within companies that rely heavily on technology and digital processes. As such, you’ll be able to work with databases, networks, and other devices to optimize business processes for efficiency. You’ll also be able to help manage data security risks and oversee software development projects.

Quick read: Why choose MBA in Information System Management?

An IS specialization will teach you:

  • How to research, analyze and solve problems related to information systems within an organization
  • Design new applications
  • Evaluate existing technologies
  • Improve existing systems
  • Develop policies related to data protection
  • Conduct feasibility studies
  • Implement new technologies into existing environments
  • Determine network requirements based on workloads
  • Identify potential threats based on system vulnerabilities.

What is an MBA in information technology?

An MBA in Information Technology is a degree designed to provide you with the skills and knowledge you need to succeed in the field of information technology.

The skills covered during an MBA in IT include management, project management, networking, and security. You’ll also learn about business fundamentals like finance and marketing. This combination of knowledge will prepare you for an IT manager or executive career or help you work your way up the ladder at a company where your current position requires additional training.

The skills covered in this type of MBA include:

  • Project management
  • Data Analytics
  • Security management

Difference between MBA in Information Systems and MBA in Information Technology?

The following is the difference between information systems and information technology.

MBA Information SystemsMBA Information Technology
An MBA in Information Systems is a professional degree.An MBA in Information Technology is a graduate business degree. 
Students who complete an MBA in Information Systems take courses like operations management, organizational behavior, and accounting for data analysis.Students who complete an MBA in Information Technology take courses like software engineering, computer networking, and systems analysis and design.
An MBA in Information Systems prepares you for careers as a chief information officer (CIO), IT manager, or technology consultant. An MBA in Information Technology prepares you for careers as a software engineer or computer scientist.
Information Systems graduates can work in almost any business field as long as they know how to code or program computers well enough that their employer needs them for those skills (like working on websites). Information Technology graduates will usually work with hardware rather than software, though they may also learn some programming languages if they want to advance their career paths towards becoming an IT manager rather than just an implementer
MBA in Information Systems can be obtained through online programs and part-time programs,An MBA in Information Technology can only be obtained through full-time programs at traditional universities or colleges.
IT degrees tend to focus more on systems architecture (also called enterprise architecture).IS degrees tend to focus more on decision-making processes (also called business analysis).
MBA in Information Systems is generally broader, covering all aspects of IT from security to ecommerce.MBA in Information Technology covers only one aspect of IT—generally either networking or programming.
MBA in Information Systems requires more general management skills.MBA in Information Technology requires specialized knowledge in a single area of technology.

Are MBA Information Systems and MBA Information Technology the same?

MBA Information Systems and MBA Information Technology are both Master of Business Administration degrees, but the difference between MBA in systems and MBA in information technology is vast.

An MBA Information Systems degree generally focuses on information technology, while an MBA Information Technology degree focuses on business.

Information systems study how information is collected and stored, organized, used, and distributed within a business. It can also be referred to as data management or IT management.

Information technology studies how computers and other electronic devices are used in business settings.

An MBA in Information Systems would be useful for someone who works in IT support or security at a company’s headquarters. An MBA in Information Technology would be useful for someone who works in IT sales or project management at a large company’s headquarters.

Want to know more about which career is best? Check out our blog on careers to explore after MBA in information systems to know more!

What is best for you?

 If you’re interested in working with computers and technology, then an MBA in Information Technology would be best for you because it will teach you about database management systems, network security, and architecture, and computer programming languages like C++ or Java, all the skills needed to work with computers professionally. An MBA in Information Systems would be more helpful if you want a job where you manage people or budgets rather than hardware/software systems themselves; these include project manager or accounting manager positions.

To answer your question: What can I do with an MBA in Information Systems?

Online MBA in Information Systems by MAHE: The new-age way of learning!

MAHE’s online MBA in Information Systems, is revolutionizing the way professionals navigate the treacherous intersection of business and technology. This program epitomizes the new-age approach to learning, offering a comprehensive curriculum designed to equip students with cutting-edge skills in information systems management. MAHE’s online platform ensures accessibility for working professionals, enabling them to seamlessly integrate academic pursuits with career commitments. The advantages of this program lie not only in the flexibility it provides but also in MAHE’s commitment to excellence, boasting a faculty of seasoned experts and a curriculum tailored to industry demands. As the business landscape increasingly relies on robust information systems, MAHE’s Online MBA in Information Systems emerges as the ideal conduit for individuals aspiring to lead in the digital age, combining the flexibility of online learning with the prestige of a renowned institution.

Conclusion

the choice between pursuing an MBA in Information Systems (MBA-IS) or an MBA in Information Technology (MBA-IT) hinges on aligning personal career aspirations with the specific skill sets each program offers. MBA-IS caters to those aiming for strategic roles in leveraging information for business success, emphasizing management and analysis. On the other hand, MBA-IT zeroes in on the technical aspects, preparing individuals for leadership in technology-driven environments. As technology continues to reshape the business landscape, both paths are integral, offering distinct avenues for professionals to contribute meaningfully. Ultimately, the decision should be driven by a deep understanding of personal strengths, career goals, and the unique demands of the evolving industries each program serves, ensuring a well-informed and rewarding career trajectory.

Visit the Online Manipal website to explore the online MBA in information systems. This program is designed to help you update with latest and most in-demand tools and skills in the field. 

What are the best MBAs for IT professionals?

For IT professionals, pursuing an MBA is invaluable as it bridges the gap between technical expertise and strategic business skills. It enhances leadership, communication, and managerial capabilities, making them well-rounded assets. Professionals with this dual skill set are highly valued by employers for their ability to align technology with organizational goals. Choosing the right MBA specialization is crucial, aligning education with career aspirations—specializations like information Systems, Data Science, or Business Analytics are most preferred. This strategic combination not only propels IT careers but also positions individuals to navigate the evolving landscape of technology and business seamlessly. 

How will an MBA help IT professional? 

  • Business acumen: An MBA equips IT professionals with essential business knowledge, enabling them to understand organizational goals, strategies, and financial considerations. This broader perspective enhances decision-making and strategic thinking. 
  • Leadership development: MBA programs often emphasize leadership skills, fostering the ability to manage teams, projects, and navigate complex organizational structures. This is crucial for IT professionals aiming to move into managerial or executive roles. 
  • Communication and interpersonal skills: Effective communication is vital in the business world. MBAs help IT professionals develop strong interpersonal skills, facilitating collaboration with cross-functional teams, clients, and stakeholders. 
  • Strategic thinking: IT professionals with MBAs gain a strategic mindset, learning to align technology initiatives with overall business objectives. This skill is essential for contributing to organizational growth and competitiveness. 
  • Networking opportunities: MBA programs provide extensive networking opportunities, connecting IT professionals with peers, alumni, and industry leaders. Building a robust professional network can open doors to career advancements, partnerships, and opportunities. 
  • Career diversification: An MBA enhances an IT professional’s versatility, allowing them to explore diverse career paths within the business world. Whether in technology management, consulting, entrepreneurship, or leadership roles, the MBA widens the spectrum of career possibilities. 

Also read: BCA after diploma for IT professionals 

Best MBA programs for IT professionals 

IT professionals have access to a wealth of online MBA courses that can benefit them professionally. Here are some highly recommended online top MBA programs for IT professionals: 

  • MAHE (Manipal Academy of Higher Education): Manipal University offers an online MBA program tailored towards IT professionals designed by experts to give students the education and skills needed to succeed in today’s rapidly advancing business environment. MAHE’s online MBA provides specializations in information systems, data science, business analytics, and others, that will help IT professionals level up their careers.  
  • Indian School of Business (ISB): ISB offers a Post Graduate Program in Management (PGPM), accessible online. This program is tailored to working professionals and includes courses such as Digital Marketing and Information Systems for Managers, which could be particularly useful to IT specialists. 
  • Symbiosis Centre for Distance Learning (SCDL): SCDL offers the Post Graduate Diploma in Business Administration (PGDBA), which can be completed virtually. This program is tailored to IT professionals with classes such as Information Technology Management and E-Commerce, which are essential for IT pros. 
  • SP Jain Institute of Management and Research (SPJIMR): SPJIMR offers a postgraduate management program (PGPM) accessible online. It’s tailored to professionals in this field with courses like Digital Strategy & Marketing or Information Technology Management, applicable to IT pros. 

Most-suited MBA specializations for IT professionals 

Here are some MBA specializations for IT professionals: 

  • MBA in Information Systems 

The MBA in Information Systems is an advanced degree program that examines the relationship between technology and business. It’s designed to prepare students for leadership positions within IT management, such as digital transformation or technology-related consulting. 

The MBA in Information Systems typically covers topics related to information technology, such as database management, cybersecurity enterprise systems, data analytics, and engineering software.  

  • MBA in Data Science 

An MBA in Data Science is a graduate-level degree program that explores the relationship between business and analytics. It prepares students for leadership positions in decision-making based on data and business intelligence and uses that same data to drive innovation. 

The MBA in data science typically covers topics such as machine learning, data mining, statistical analysis and visualization of data, management of databases, and design of systems.  

  • MBA in Business Analytics 

The MBA in Business Analytics is a graduate-level program combining business and data analysis. It’s designed to give students the knowledge and skills needed to use analytics based on data to make more informed decisions for their businesses. 

The MBA with a concentration in Business Analytics typically involves classes on statistics and data management, visualizing data, predictive models, and machine learning.  

The MBA with a concentration in Operations Management typically covers various topics related to business operations. These include logistics, supply chain management, operational strategy, process improvement, inventory management, and quality control.  

  • MBA in Project Management 

An MBA with a concentration in Project Management is a graduate-level degree designed to equip students with the abilities and skill sets needed for effective project management from start to finish.  

The MBA focused on Project Management typically offers courses on project control and planning, risk management, quality assurance in projects, and procurement management.  

  • MBA in IT & FinTech 

An MBA in IT & FinTech is a graduate degree program that examines the relationship between technology, finance, and the financial sector. Its purpose is to prepare students for leadership positions within financial services that utilize cutting-edge technologies like digital banking and innovations within finance. 

Furthermore, the MBA IT & FinTech curriculum examines business topics like organizational behavior, accounting marketing, and finance operations management. 

Check out: What are the various MBA specializations and how to choose the right one? 

Career prospects after an MBA for IT professionals 

An MBA can present IT professionals with numerous career advancement opportunities. Here are some of the potential outcomes of having earned your MBA: 

  • IT Manager: IT Managers are accountable for leading and managing their organization’s IT department. This includes deploying and maintaining IT systems after their development.   
  • Technology Consultant: These consultants assist businesses in improving their technology systems and processes. An MBA in technology leadership provides IT specialists with expertise in business operations and the strategic capabilities required to become effective technology consultants. 
  • Digital Transformation Managers: These managers assist businesses in adopting new processes and technologies to meet business objectives. They’re accountable for finding ways to maximize efficiency and effectiveness through technology adoption.  
  • Product Managers: Product managers oversee innovative technological product creation and release. They work alongside engineers developing software and IT specialists to guarantee that the item meets market requirements. 
  • Entrepreneurs: The entrepreneurship after an MBA can equip IT specialists with the necessary expertise to launch their technology company. IT pros with an entrepreneurial mindset can use their technology and business knowledge to create innovative products and solutions. 

Also read: Best MBA specializations for commerce graduates 

Elevate tour technical expertise and managerial skills with an online MBA through Online Manipal 

Progress in your by seamlessly blending technical expertise with managerial skills through the online MBA programs offered by Manipal Academy of Higher Education (MAHE) and Manipal University Jaipur (MUJ) on the Online Manipal platform. Tailored for learners from diverse fields, including IT, these programs feature a range of electives and MBA specializations. These online programs have the same credibility as on-campus counterparts and are particularly designed for working professionals. By enrolling, professionals can enhance their technical prowess, acquire crucial business acumen, and hone managerial skills. This strategic combination empowers them to scale new heights in their careers, all within the flexible framework of online learning. 

Conclusion  

Top MBA programs for IT professionals enhance career growth opportunities by giving them the leadership, business acumen, and management abilities needed to hold leadership positions within the sector. An MBA can greatly benefit professionals pursuing IT management or leadership positions who wish to bridge the gap between technologies and business.  

When selecting an online MBA, factors like reputation and accreditation, costs and flexibility of the program, and networking opportunities should all be considered. Furthermore, ensure the course curriculum and offerings match your career objectives and personal interests. Visit the Online Manipal website to know more about future-ready online MBA programs. 

Six reasons why you should pursue a master’s degree in business analytics

A career in business analytics is exceptionally promising, with increasing demand for professionals who can derive insights from data. Businesses rely on analytics to make informed decisions, creating a surge in job opportunities. Pursuing a master’s in business analytics equips individuals with advanced skills in data analysis, statistical modeling, and decision-making, making them highly sought-after in diverse industries. This degree not only facilitates entry into the field but also enhances career progression, offering roles such as business analyst, data analyst, business intelligence manager, or data scientist. With data-driven decision-making becoming integral to success, a master’s in business analytics opens doors to a dynamic and lucrative career path. 

Reasons for pursuing a master’s in business analytics 

High industry demand: The global demand for business analytics professionals is soaring as companies recognize the value of data-driven decision-making. Pursuing a Master’s ensures you enter a field with abundant job opportunities. 

Strategic decision-making: Businesses rely on analytics to make informed decisions. A master’s in business Analytics teaches you how to translate data into actionable strategies, enhancing your ability to contribute meaningfully to organizational success. 

Versatility across industries: The skills acquired are applicable across diverse sectors, from finance and healthcare to marketing and operations, providing flexibility and widening your scope for career choices. 

Competitive salaries: The advanced skills gained in a Master’s program often translate into higher earning potential. Companies recognize the strategic importance of analytics professionals and are willing to offer competitive salaries. 

Global opportunities: Business analytics skills are in demand globally, offering opportunities for international career mobility. This global relevance enhances your ability to work in different markets and cultures. 

Job security: In a data-driven era, professionals with expertise in business analytics are in high demand, providing a level of job security as companies increasingly rely on data for decision-making. 

Integration of emerging technologies: Stay at the forefront of technology by gaining exposure to emerging tools and techniques such as machine learning and artificial intelligence. This ensures that you are well-prepared to address the evolving needs of the industry. 

Also read: Who should do MSc in business analytics course? 

Top jobs you can get with a master’s in business analytics 

  • Data Scientist: Analyzing complex data sets to derive actionable insights, data scientists use statistical techniques and machine learning algorithms to inform business decision-making. 
  • Business Intelligence Manager: Overseeing the design and implementation of business intelligence tools, these professionals help organizations streamline operations and improve strategic planning. 
  • Data Analyst: Interpreting data and presenting findings to aid business decision-makers, data analysts play a crucial role in translating raw data into actionable insights. 
  • Analytics Manager: Responsible for leading analytics teams, these managers ensure the effective use of data to drive business strategies and achieve organizational goals. 
  • Quantitative Analyst: Employing mathematical and statistical methods, quantitative analysts assess financial risks, develop models, and provide insights for investment decisions. 
  • Market Research Analyst: Using data analysis to understand market trends and consumer behavior, market research analysts help businesses make informed marketing and product development decisions. 
  • Operations Analyst: Optimizing business processes, operations analysts use data to identify inefficiencies, reduce costs, and improve overall operational effectiveness. 
  • Supply Chain Analyst: Applying analytics to optimize supply chain processes, these professionals enhance efficiency, reduce costs, and improve overall supply chain performance. 
  • Risk Analyst: Evaluating potential risks and developing strategies to mitigate them, risk analysts use data analysis to ensure businesses make informed decisions that minimize potential negative impacts. 
  • Healthcare Data Analyst: Working in the healthcare sector, these analysts use data to improve patient outcomes, optimize healthcare operations, and contribute to evidence-based decision-making. 

Check out: How to get into business analytics? 

Scale up in your career with an MSc in business analytics 

An MSc (Master of Science) in Business Analytics is a postgraduate academic degree program that focuses on providing advanced knowledge and skills in the field of business analytics. This program is designed to equip students with the tools and techniques necessary to analyze and interpret complex data sets, enabling them to make data-driven decisions in various business contexts. The curriculum typically covers topics such as statistical analysis, data mining, machine learning, predictive modeling, and business intelligence. 

Key components of an MSc in Business Analytics program often include: 

  • Statistical Analysis and Modeling: Teaching students how to use statistical methods to analyze and interpret data for decision-making. 
  • Data Mining and Machine Learning: Providing insights into advanced techniques for extracting valuable patterns and information from large datasets. 
  • Business Intelligence: Focusing on tools and strategies for transforming raw data into actionable insights to support business strategies. 
  • Predictive Analytics: Teaching methods to predict future trends and outcomes based on historical data. 
  • Big Data Analytics: Covering the challenges and opportunities presented by the analysis of large and complex datasets. 
  • Data Visualization: Training students to present data in a visually compelling and comprehensible manner for effective communication. 
  • Business Strategy and Decision-Making: Integrating analytics into the overall business strategy and decision-making processes. 

An MSc in Business Analytics is highly relevant in today’s data-driven business environment, preparing individuals for roles such as data scientist, business intelligence analyst, analytics manager, and more. The program aims to bridge the gap between business and technology, providing graduates with the skills needed to leverage data for strategic decision-making in various industries. 

Check out: Differences in MSc and MBA in business analytics programs 

Choose a reputed institution for your MSc business analytics program 

Choosing a reputable institution for your MSc in Business Analytics is crucial for several reasons, and the online program offered by Manipal Academy of Higher Education (MAHE) stands out as an excellent option. Here’s why: 

Curriculum excellence: The program is designed to meet industry standards, ensuring that students receive a comprehensive education. MAHE’s online MSc in Business Analytics is likely to cover a well-structured curriculum that incorporates the latest trends and technologies in the field. 

Expert faculty: Renowned institutions often have faculty members who are experts in their respective fields. The online MSc program at MAHE likely boasts experienced and qualified instructors who bring real-world insights to the virtual classroom. 

Programming languages and tools: A quality program should cover a range of programming languages and tools relevant to business analytics. MAHE’s program is likely to include instruction on popular languages like Python and R, as well as hands-on experience with tools such as Power BI, Jira, SAS, and others commonly used in the industry. 

Hands-on experience with virtual labs: Practical experience is crucial in business analytics. MAHE’s online MSc program is likely to provide hands-on experience through virtual programming labs, allowing students to apply theoretical knowledge in a practical setting. 

Flexibility in course delivery: Online programs offer flexibility, enabling students to learn at their own pace and convenience. MAHE’s online MSc likely provides a flexible schedule, allowing professionals or those with other commitments to pursue their studies without compromising on their current responsibilities. 

Live and recorded lectures: Access to both live and recorded lectures ensures that students can engage with the material in real-time or review it at their convenience. This flexibility caters to different learning styles and schedules. 

Extensive e-learning content: A robust online learning platform (LMS) should offer a wealth of digital resources. MAHE’s program is likely to provide extensive e-learning content, including e-libraries, reading materials, and multimedia resources to enhance the learning experience. 

Webinars by industry experts: Exposure to industry insights is invaluable. MAHE’s program is likely to feature webinars by industry experts, providing students with a practical understanding of how business analytics is applied in various sectors 

Also read: Future of business analytics in Canada 

MAHE’s online MSc in Business Analytics syllabus – Semester wise subjects 

Eligibility criteria for MAHE’s online MSc in Business Analytics  

  • Candidates must have completed graduation in any discipline with Statistics as one of the subjects from recognized universities/institutions or an equivalent qualification as recognized by the Association of Indian Universities (AIU) 
  • They must have minimum 50% marks in aggregate or equivalent grade in graduation 
  • Work experience is desirable but not compulsory 

Conclusion 

Pursuing a master’s degree in business analytics is a worthy investment in a data-centric future. It opens doors to numerous career opportunities in diverse sectors, providing specialized skills to navigate complex data landscapes. The program offers a competitive edge, positioning graduates as invaluable assets in an evolving job market. With increasing demand for data-driven decision-makers, obtaining a master’s in business analytics not only enhances individual expertise but contributes significantly to shaping the innovative landscape of diverse industries. 

Key takeaways

  • Getting a master’s degree in business analytics is worth it because you learn to bridge the gap between the IT industry and the business field. It enhances your analytical skills and logical reasoning. 
  • If you have a keen eye for identifying minor details and issues and understand how to tackle a situation, pursuing a master’s degree is worth the money and time. 
  • You learn how to organize and keep track of the records as your team’s project manager. 
  • The master’s degree allows you to boost the communication skills required in top firms to communicate with business stakeholders. 
  • A business analyst develops a great social network, which helps the corporate world to communicate in a fast-paced world. 

How to get into data science after mechanical engineering?

Data science has emerged as the most in-demand field in recent years, revolutionizing the way businesses operate and make decisions. In an era where data is generated at an unprecedented rate, organizations are seeking skilled professionals who can extract valuable insights from vast datasets to drive informed decision-making. This surge in demand is attributed to the increasing recognition of the power of data-driven strategies across various industries. Fortunately, the field of data science is accessible to individuals from diverse educational backgrounds, providing an opportunity for career transition and growth. 

Data science: A lucrative career path 

Data science roles are not only in high demand but also offer lucrative career prospects. The skill set required for data science is diverse, encompassing programming, statistical analysis, machine learning, and domain-specific expertise. As organizations increasingly rely on data to drive their strategies, data scientists play a crucial role in shaping business outcomes. This high demand for skilled professionals often translates into competitive salaries and attractive job opportunities. 

Check out: Is data science hard? 

Pursuing a career in data science from any educational Background 

One of the remarkable aspects of data science is its inclusivity. Students from any educational background, whether it’s mathematics, computer science, engineering, social sciences, or even humanities, can transition into a career in data science. The key lies in acquiring the relevant skills and knowledge. Online courses, bootcamps, and degree programs in data science are widely available, catering to individuals with different learning preferences and schedules. Many successful data scientists have backgrounds in fields unrelated to computer science, showcasing the versatility of the profession. 

Can mechanical engineers get into data science careers? 

Mechanical engineers, with their strong analytical and problem-solving skills, are well-positioned to transition into data science roles. While the technical background is beneficial, acquiring programming skills (such as Python or R) and learning data analysis and machine learning techniques are essential steps. Through online data science degrees and certifications, one can learn essential data science subjects and gain a deeper understanding of the world of data science. 

You can also check the best MBA specialization for mechanical engineers.

How data science courses help mechanical engineers in making a career switch 

Data science is an emerging field in the tech industry, and it is one that mechanical engineers can use to make a smooth and seamless career switch to data science. 

  • Gain knowledge  

Data science is a growing field, and it is not just mechanical engineering to data science. As more companies use data to make business decisions, they are looking for people with various backgrounds who can help them analyze that data. Mechanical engineers can take advantage of this trend by learning to apply their skills in a new context. 

  • Knowledge in programming languages 

If you want to make a career switch to data science, you will need to learn how to program and do fundamental data analysis. Although there are many programming languages, Python is one of the most common ones in the industry. If you are already familiar with Python or another language like Java or C++, then learning about machine learning algorithms will be easier! 

  • Enhance decision-making skills 

Data scientists need to understand how their work impacts others and how it can be used to improve lives. They must also know how to present their findings in a way that makes sense for different audiences. This means that data science will help you be better equipped to make decisions about their work and how it affects other teams or departments within an organization. 

Also read: Is data science a good career option for you? 

The transition from mechanical engineering to data science 

Can mechanical engineers do data science? Mechanical engineers interested in changing to a career in data science should be prepared for a steep learning curve. 

The career switch to data science requires an understanding of programming, math and statistics, as well as a new set of skills. 

Here’s why – 

  • Programming 

Mechanical engineers are familiar with programming, but not the same way data scientists use it. Data scientists use programming to build programs and algorithms that can be used to analyze data. They also use it to build models, which are representations of real-world processes. Mechanical engineers must learn new tools, such as Python and R. 

  • Math and statistics 

Students who have studied math but haven’t studied statistics make up the question, “can a mechanical engineer do data science”. Data scientists use statistics to understand the relationships between variables in their data sets, which is essential for making sense of large amounts of information.  

These skills will help mechanical engineers understand how their data sets work together—for example, when one variable increases or decreases while another stays constant—and what these relationships mean for their company’s products or services. 

  • Domain knowledge 

The field of data science is relatively new, and as such, many skills need to be learned. Data engineers have to learn how to manipulate data and write scripts, while data scientists have to learn how to use machine learning algorithms and create models. 

As a mechanical engineer, you’ve spent your whole life learning about how machines work, and that knowledge can easily be applied to data science. This means that you will be able to jump right into manipulating numbers and writing code without much trouble. 

  • Visualization 

Data visualization is a crucial part of data science; this is where the skills you learned as a mechanical engineer come in handy. You will need to visualize data to understand it better, so knowing how to make compelling visualizations with code will help you immensely. 

Check out: Career switch to data science 

Career opportunities in Data Science: Top data science jobs to look out for 

Data Scientist: 

Role: Analyzing and interpreting complex datasets to inform business decision-making. 

Skills Needed: Statistical modeling, machine learning, programming (Python/R), data visualization. 

Industry Demand: High demand across various industries such as finance, healthcare, e-commerce, and technology. 

Machine Learning Engineer: 

Role: Designing, building, and implementing machine learning models and algorithms. 

Skills Needed: Advanced programming, deep understanding of machine learning algorithms, data engineering. 

Industry Demand: Growing demand in fields like artificial intelligence, autonomous systems, and predictive analytics. 

Data Engineer: 

 Role: Developing, constructing, testing, and maintaining architectures (e.g., databases, large-scale processing systems) for data generation. 

Skills Needed: Database design, ETL (Extract, Transform, Load) processes, big data technologies. 

Industry Demand: High demand for professionals who can ensure efficient data processing and storage. 

Business Intelligence (BI) Analyst: 

Role: Translating complex data sets into insights that drive business decisions. 

Skills Needed: Data visualization, SQL, business acumen. 

Industry Demand: In demand across sectors for providing actionable insights to improve business performance. 

Data Analyst: 

Role: Collecting, processing, and analyzing data to help companies make more informed decisions. 

Skills Needed: Statistical analysis, data cleaning, SQL, Excel. 

Industry Demand: Wide-ranging demand in various industries for individuals who can turn raw data into actionable insights. 

Statistician: 

Role: Applying statistical methods to analyze and interpret data. 

Skills Needed: Advanced statistical modeling, data interpretation, domain-specific knowledge. 

Industry Demand: Commonly found in research, finance, healthcare, and government sectors. 

Quantitative Analyst: 

Role: Applying mathematical and statistical techniques to financial and risk management problems. 

Skills Needed: Strong mathematical background, programming skills, financial modeling. 

Industry Demand: High demand in finance, investment banking, and hedge funds. 

Research Scientist: 

 Role: Conducting research to develop new algorithms and models. 

Skills Needed: Advanced knowledge of machine learning, deep learning, research capabilities. 

Industry Demand: Found in academia, research institutions, and industries focusing on cutting-edge technology. 

Make a seamless transition into data science with online courses from the reputed Manipal universities 

Seamlessly transition into the dynamic field of data science with acclaimed online courses from Manipal University Jaipur (MUJ) and Manipal Academy of Higher Education (MAHE). These reputable institutions offer cutting-edge programs designed to equip aspiring data scientists and working professionals with a comprehensive understanding of data science concepts and programming skills. The flexibility of these courses caters to the needs of working individuals, allowing them to upskill without leaving their current jobs. Explore transformative programs such as the MBA in Analytics and Data Science (MUJ), MBA in Data Science from MAHE, MSc in Data Science from MAHE, and the PGCP in DSML from MIT. Take the first step towards a rewarding data science career with Online Manipal. 

Key takeaways

  • A mechanical engineer must have the right skills and experience. They should have strong analytical skills to process large amounts of information and find patterns. They should also be well-versed in programming languages and tools like Python, R, or Scala.  
  • They should also be familiar with machine learning models such as regression analysis, clustering algorithms, and decision trees. Also, they should know statistical methods such as linear regression, ANOVA, etc. 
  • They must understand big data analytics tools such as Hadoop/Spark/Flink/MapReduce/Cassandra/HBase/MongoDB etc. 
  • They should be able to work with different types of data, such as structured (e.g., relational databases), semi-structured, and unstructured. 
  • Finally, they must understand how their organization uses data science techniques to make decisions that affect their business processes and operations. 

How to become a software developer after BCA?

Software development is in high demand globally due to the digital transformation across industries. Developers create applications, systems, and websites, driving innovation. The increasing reliance on technology fuels demand, making it a lucrative profession. India stands out as a major contributor, producing a significant number of software developers every year. According to the US Bureau of Labor Statistics, there’ll be a 22% surge in demand for developers by 2029, emphasizing the profession’s pivotal role in our tech-driven society.  

Bachelor of Computer Applications (BCA) provides a solid foundation for aspiring developers, equipping them with essential programming and problem-solving skills. This degree serves as a stepping stone to a successful career in software development, aligning with industry demands and opening doors to lucrative opportunities. 

To know more, you can read 10 reasons you should enroll for an online BCA degree course

Software Developer roles and responsibilities 

Software developers use a variety of technologies and competencies to design, program, create, deploy, and manage software. Additionally, they contribute to the creation of software systems that fuel devices and networks and maintain the functionality of those systems. A software developer might work alone or alongside other programmers and developers on a team, depending on the situation. Their roles and responsibilities can vary based on the specific job, industry, and company, but generally include: 

Analysis and planning: 

  • Collaborate with stakeholders to understand software requirements. 
  • Analyze end-users’ needs and design software solutions to meet those needs. 
  • Plan the software development process, including timelines and resources. 

Coding and development: 

  • Write efficient, maintainable, and reusable code. 
  • Use programming languages and development frameworks to build software applications. 
  • Debug and troubleshoot issues in the code. 

Testing 

  • Develop and execute test cases to ensure software functionality and performance. 
  • Identify and fix bugs and glitches in the code. 
  • Conduct thorough testing to ensure the software meets quality standards. 

Documentation: 

  • Create documentation for code, algorithms, and software processes. 
  • Maintain comprehensive records for future reference and collaboration. 

Version control: 

  • Use version control systems (e.g., Git) to manage and track changes in the codebase. 

Deployment: 

  • Deploy software applications to production environments. 
  • Ensure smooth and efficient deployment processes. 

Maintenance and upgrades: 

  • Monitor and maintain software after deployment. 
  • Implement updates and improvements to enhance software functionality. 

Security: 

  • Implement security measures to protect software from vulnerabilities. 
  • Address security issues and apply best practices for secure coding. 

Collaboration: 

  •  Work closely with other developers, designers, and stakeholders. 
  • Collaborate with cross-functional teams to integrate software with other systems. 

Client interaction: 

  • Communicate with clients to understand their requirements and address concerns. 
  • Provide support and updates to clients as needed. 

You can also read BCA course details: Syllabus, job & salary

Steps to become a Software Developer 

So, “Can a BCA student become a software engineer or software developer?” The answer is “Yes.” Follow the steps mentioned below to get on the path to becoming a software developer. 

  • Acquire a bachelor’s in computer applications or a related subject 

Most students prefer to enroll in UG courses such as BCA or any other computer science bachelor’s degree programs, where they learn in-depth conceptual ideas of computer science subjects that aid in their understanding of the principles of software engineering.  

  • Master programming languages 

Even if you hold a degree or are a graduate, it won’t help you much if you can’t comprehend programming languages well enough to use it when creating software. Master important programming languages that are in high demand today such as languages like Java, C#, Python, and JavaScript. 

  • Become familiar with data structures and algorithms 

Data structures and algorithms aid programmers in issue-solving by requiring less time and memory. These two topics are very important since they are the foundation of programming. Study mathematics in addition, as it will help you identify problems and develop the best possible algorithm. 

  • Develop your Skills 

Earning a degree aids in learning the basics of software development, but you also need to grasp how to use theoretical knowledge in the real world. You must continue your practice and stay current with the latest technological advancements. Get acquainted with a few of the technologies and tools used by diverse industries.  

  • Create and implement projects or software 

Most employers probably demand prior software development or project management expertise. All the academic stuff you have learned is useless if you don’t know how to apply it. Create some software or other initiatives to put your newfound knowledge into practice and hone your skills.  

  • Pursue some internships 

The ideal way for students to gain exposure to and experience in the workplace is through internships. Students who participate in internships receive hands-on training and real industry exposure while working on projects or products that are relevant to their skill sets. They also learn how to collaborate with others and how to adapt to a team environment. 

  • Look for employment opportunities 

After fulfilling the aforesaid steps, you should start looking for job opportunities. Create a CV and a professional profile on numerous job boards, post your resume there, browse these sites, and submit applications for the openings listed there.  

Skills needed to become a software developer 

Programming languages: Proficiency in at least one programming language, such as Java, Python, C++, JavaScript, or others, depending on the development domain. 

Problem-solving skills: Ability to analyze problems and devise efficient and effective solutions. 

Algorithm and data structures: Understanding of algorithms and data structures for designing efficient and scalable software. 

Database management: Knowledge of database systems and the ability to design and query databases (e.g., SQL, NoSQL). 

Frameworks and libraries: Experience with development frameworks and libraries relevant to the chosen programming language (e.g., Django, Flask for Python). 

Soft skills and collaboration: Effective communication, teamwork, and collaboration skills to work with cross-functional teams, stakeholders, and clients. 

Testing and debugging: Proficiency in testing techniques and tools to ensure software reliability. Ability to debug and fix issues efficiently. 

Security awareness: Understanding of security best practices and awareness of potential vulnerabilities in code. 

 

How much does a Software Developer earn? 

Software developers get a handsome salary in India. The salary range of a software developer in India is around ₹ 1.8 Lakhs to ₹ 12 Lakhs, with an average salary of ₹ 7.0 Lakhs yearly. Software developers’ salaries depend on various factors such as skills, experience, employer, and location. 

You can read, Is an online BCA course equivalent to a regular BCA? 

Top recruiters for Software Developers 

Trends indicate that the urgent demand for jobs in engineering, product, data science, marketing, and sales will be fueled by developing technologies such as artificial intelligence, robotics, virtual reality, and cryptocurrencies. Such circumstances have simply opened new frontiers for experienced software developers across. Top recruiters for Software Developers include renowned firms like: 

  • Google 
  • Microsoft 
  • Amazon 
  • TCS 
  • Infosys 
  • Accenture 
  • Capgemini 
  • Wipro 
  • Tech Mahindra 
  • IBM 
  • HCL 

Become a skilled Software Developer with an online BCA through Online Manipal 

The online BCA program offered by NAAC A+ accredited Manipal University Jaipur is designed to produce tomorrow’s software developers by fusing the most recent advancements in computer technology, a focus on intellect and inventiveness, in addition to the evolving norms of the sector. Real-world case studies are introduced in the curriculum to help you build and refine your critical thinking abilities. The faculty assist the learners in articulating themselves professionally in a challenging world where confidence and communication are crucial.  Learners can also gain hands-on programming experience by practicing through virtual labs. The meticulously crafted curriculum also covers some of the essential software tools and packages including Python, Oracle, Visual Studio, MySQL, and others. 

Eligibility criteria: 

  • Students must have completed their 10+2 or 10+3 diploma from a recognized board and institute. 
  • Students must have at least 45% aggregate in their 10+2 or diploma. (40% for reserved categories) 

Benefits of the program: 

  • The program provides learners with global tech perspectives 
  • It helps individuals get better-paying jobs 
  • It provides learners with hands-on experience and coding skills 
  • It helps gain coding, analytical, and problem-solving skills. 

Conclusion 

The need for highly competent software developers is not going to go away anytime soon as the IT businesses are growing and are on the route to greater glory. So, if you are planning to launch your career in software development, then enroll in the online BCA program offered by Manipal University Jaipur to delve deep into the field of software development and pave your way toward a lucrative career. 

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