Does data science require coding? A guide for non-programmers Whether an experienced professional or a fresher, people wishing to move into Data Science have one question often: “Does data science require coding?” Let’s establish a little more understanding first. Data Science is a field that is an amalgamation of mathematics, technology, and business. In a persistently evolving domain, the mathematical comprehension of Data Science remains accordant. Let’s understand more about this perception: Business: Data Science is a business-agnostic field of profession. You can leverage your business knowledge to do better data science in whatever area you come from. For example, if you belong from a CA background, you can assist Fintech organizations. In addition, given that you have a firm understanding of financial data, you can understand things better than the rest. However, you can enter any sphere of data science based on your interests. Technology: The field of technology undergoes some evolution daily. You should possess a mindset keen on always learning to be synonymous with the pace of growing technology. Once you grasp the establishing elements of technology, it is key to keep yourself upgraded based on what is latest. Now that we know we need to be up to date with technology, let’s understand: does data science require coding? Is it ideal to become a data scientist without coding? For freshers: Coding in data science takes a different and more complex form when it is time to apply it in the real world. It is way more than what you did in college or school. However, much of what you learn in data science can be found in simple, usable functions. Data science is pragmatic and non-theoretical. Google will already have all the answers to your questions, but you should be aware enough to ask the right questions. Meaning you need to build an understanding of how to code. By going over the data, you will need to figure out what will be the correct input and the viable output. A significant portion of the work here is to speculate the output. As discussed, coding is required, and a master’s in data science certificate from the Manipal Academy of Higher Education can help. For working professionals unfamiliar with coding: The question has been asked often – does data science require coding? It is assumed that you have an underlying doubt about whether you can learn code. The answer is yes, but the real outcome will be based on your will to learn. However, let’s suppose you enter a managerial role in data science moving forward. To meticulously guide your teammates, you need hands-on coding experience to understand what is happening. Hence, coding is required. To work better, you’ll need to try out few data science projects to improve your coding and thinking level required for this domain. For working professionals familiar with coding: Coding is essential to data science as it possesses a learning bend. Along with learning to code, from an application standpoint, you will be going through the process of relearning mathematics and business. Being a Data Scientist can be both challenging and fun, depending on your grasp of it. It would be beneficial if you were certain how you would add value to the company you work with. Few FAQs people have regarding coding and becoming data scientist Is coding a mandatory skill for a data scientist? While coding is not a strict requirement for all data science roles, it is highly recommended for data scientists to have a good understanding of at least one programming language. Coding skills allow data scientists to manipulate and clean data, create models, and automate processes, all of which are critical to the data science process. Which programming languages are considered essential for a data scientist? Python and R are considered as the most essential programming languages for a data scientist. Both languages provide a wide variety of libraries and frameworks for data manipulation, visualization, and modeling. Python is a general-purpose programming language that is widely used in the industry while R is particularly used for statistical analysis and visualization. Can a person with no coding background still become a data scientist? It’s possible, but it will be challenging to learn coding from scratch. While there are tools and platforms that make it easier for non-coders to perform data analysis, it’s still important for data scientists to have a good understanding of coding principles. It’s not impossible to learn coding, but it will take a significant amount of time and effort to acquire the necessary skills to become an effective data scientist. Languages used in data science If you have decided to land on learning new programming languages primarily for Data Science, the best, most notable ones to learn are Python and SQL. You can start with online learning platforms or apps to code where you won’t be needing any special software to install. Python: Data scientists use Python as their primary language of choice worldwide. It is a highly divergent language that fits properly into multiple technology stacks organizations use. Python also has brilliant backing from the developer community. All Data Science related technical interviews ask whether you are familiar with Python, without fail. The focus should be on acing concepts and general logic attached to them rather than trying to master the syntax of Python. Languages allow you to implement logic where it is needed effectively. SQL: Organizations assess SQL as a foundational querying language skill. SQL allows you to interrogate databases in a simple language. SQL is a rationally instinctive language to learn and can be one of the first languages to get started with for the initial boost of confidence. Does data science require coding: How can you start? Does data science require coding? Yes, it is required to excel in your career in data science. In contemplation of this article, it is established that learning to code is the most practical and favorable way to get into Data Science. Coding can seem intimidating, but what lies ahead is a simple advantage. Therefore, it is ideal to believe that coding is a fruitful barrier that will prove to be only beneficial if you decide to overcome it. Pursuing a master’s in data science from Manipal Academy of Higher Education through Online Manipal will help you excel and provide the right path to becoming a data scientist
Is data science hard? Know how you can build a successful career with a master’s degree Data science jobs are taking over the market by storm and attracting a lot of professionals to make a career transition. This interdisciplinary field has witnessed 650% growth in the job domain since 2012 and is believed to expand further in the upcoming years. As per a recent study by the PwC, Data Scientist is one of the best jobs in the United States, indicating that data science graduates can apply for a job in India and abroad. If you are also planning to move to data science from your career field but hesitating because of the subject’s nature, fret not! We have all the information to help you decide to answer your questions. Read ahead to find out how you can turn your career upside down and venture into a more successful domain! Data Science- Growth statistics As per the U.S. Bureau of Labor Statistics, the technical domain is set to have more than 11.5 million job openings by 2026. The job positions will include the following- Data Scientist Machine Learning Engineer Big Data Developer Director of Data Science Full Stack Engineer Customer Success Manager Since the demand is increasing and the supply of eligible professionals to fill this job opening is quite low, you can easily embark on a successful career transition journey by applying for a data science master’s course. The big question- Is data science hard? For professionals who have experience in the technical field, it can be a little less daunting, whereas for people who have zero technical background, they might find the course and this field a bit challenging. Data science includes coding, and you will have to learn programming languages such as Python, R, SQL, Scala, Java, MATLAB, and more, depending on the nature of the job. This is also one of the crucial reasons why there is a shortage of professionals in this domain. Though with the right course, you can easily learn these languages. The Master of Science in Data Science at Online Manipal provided by Manipal Academy of Higher Education offers the perfect blend of practical and theoretical knowledge that will help you overcome all the obstacles. Factors that make data science hard to pursue There is zero doubt that data science is one of the hardest subjects to master, but that should not be the end of it. The broad skill set this field requires is vast, but the maximum content in the syllabus is already covered in school. What you need to master is the advanced version of what you have studied previously. Data Science includes subjects such as probability, statistics, mathematics, computer science, software and such. For professionals working in any of these fields, learning data science won’t be much challenging. Here are some factors you should know- Data science is an interdisciplinary subject, including math, science, statistics and other subjects. You need to have a sound knowledge of programming languages to retrieve data from a huge database. Since the field is growing, you need to have what it takes to stand out from the crowd. Opt for a master’s program that offers programming, collaborative projects to work on, a capstone project to project your learnings, mentors with field experience, and industry-oriented coursework and syllabus. All of the multinational giants that are ruling the market have requirements for data science graduates. Data science professionals study the market trend and analyse the generated data to build a perfect strategy to dominate the market and consumers. As a data scientist, you might also be asked to conduct A/B testing to generate a more practical result. This practice includes a sound knowledge of statistics, and maximum companies in the corporate world use this methodology. Should you make this career transition? Now that we have answered your question- is data science hard or not, we hope that you are now ready to make a decision. Data Science is a revolutionary field and the salary offered is quite promising if you have the skill set that employers need. In addition, the lucrative career option has numerous job roles you can explore, such as data scientist, big data engineer, and more. The average salary of a fresher data analyst is 6 Lakh per annum in India which is high compared to other job roles of the same level. If you are a professional with work experience, you will get a good hike in your salary package once you change the job. Choose Online Manipal Ready to change your profession and venture into the complex world of data science? Choose Master of Science in Data Science offered by Manipal Academy of Higher Education on the Online Manipal website. The online course MAHE is taught by highly experienced faculty and has a career-oriented curriculum designed to elevate your career. The online course will allow you to keep your current job while studying online at your own pace. The syllabus includes mini projects to enhance your practical skills. Upon course completion you will receive career support from Online Manipal to find a suitable job opportunity. So, what are you waiting for? Join the course today!
Importance of university accreditations and recognitions Institutional accreditation and recognition are important for colleges and universities because they provide a way for these institutions to show that they meet certain standards. There are several different types of college accreditations, and each type has its own set of standards that institutions must meet. For example, the Accreditation Board for Engineering and Technology (ABET) accredits engineering programs at colleges and universities. A program must meet certain curriculum, faculty, and facilities standards to be accredited by ABET. National or regional organizations can also recognize colleges and universities. You can also read: 8 tips to prepare for your online classes Why should colleges be accredited and recognized? In India, many colleges offer higher education, but the government recognizes not all. It is because the government only recognizes those colleges which have been accredited by regulatory bodies like the University Grants Commission (UGC), the All India Council for Technical Education (AICTE), and the National Assessment and Accreditation Council (NAAC). There are several reasons why colleges need to be accredited and recognized: It ensures that the college offers quality education and follows the set standards It makes the students eligible for various government scholarships and other financial assistance programs It helps in the placement of students in reputed companies It increases the credibility of the college Thus, we can see many advantages for colleges to get accreditations and recognition. Colleges must be accredited and recognized to provide quality education to their students. Advantages of accreditations for institutes of higher education Accreditation is an assessment of an institution of higher education to ensure that it meets certain educational standards. This assessment is typically carried out by a third party, such as a governmental or independent organization. There are several advantages of having accreditation for institutes of higher education. 1. Assessing if an institution complies with educational standards Accreditation can help assess if an institution of higher education complies with educational standards. It is important for both students and parents, as they can be assured that the institution is high quality. 2. Increasing enrollment by gaining the confidence of students and parents Accreditation can help to increase enrollment at an institute of higher education by gaining the confidence of both students and parents. It is because they will be more likely to choose an institution that has been accredited. 3. Assisting employers in evaluating the programs’ legitimacy and students’ degree of expertise Accreditation can also assist employers in evaluating the legitimacy of programs at an institute of higher education, as well as the degree of expertise of its students. Employers are more likely to hire graduates from accredited institutions. 4. Enables graduates to take further certification tests Accreditation can also enable graduates from an institute of higher education to take further certification tests. It is because they will be more likely to be accepted into a certification program if their institution is accredited. 5. Attracts potential employers Accreditation can also attract more potential employers to an institute of higher education. It is because they will be more likely to recruit graduates from an accredited institution. 6. Sets objectives for self-improvement of educational institutions Accreditation can also set objectives for the self-improvement of educational institutions. It is because they must meet certain standards to maintain their accreditation. You can also read: How online courses help you to manage studies while working Benefits of getting a degree from an accredited college There are many benefits of getting a degree from an accredited college. 1. Quality education It is the most important benefit of attending an accredited college. The curriculum and teaching methods at accredited colleges are typically more rigorous than at non-accredited colleges, and the schools are often better funded. As a result, students who attend accredited colleges often receive a higher-quality education than those who attend non-accredited colleges. 2. Well-qualified teaching staff Accredited colleges must hire qualified teachers, and many have higher standards for their faculty than non-accredited colleges. As a result, students at accredited colleges often have access to better-qualified teachers than those at non-accredited colleges. 3. Financial aid Many accredited colleges offer financial aid to their students, and the schools often have more money available for financial aid than non-accredited colleges. As a result, students attending accredited colleges often have access to more financial aid than non-accredited colleges. 4. Higher chances of placement Many employers prefer to hire graduates of accredited colleges, and the schools often have better relationships with employers than non-accredited colleges. As a result, students who attend accredited colleges often have a better chance of being placed in a job after graduation than those who attend non-accredited colleges. 5. Credit transfer Many accredited colleges have agreements with other colleges and universities that allow students to transfer credits between the schools. As a result, students who attend accredited colleges often have an easier time transferring credits than those who attend non-accredited colleges. What are the various accreditations and recognitions of Manipal University Jaipur? Manipal University Jaipur is a private UGC-recognized university and is NAAC-A accredited. You can get access to MUJ’s online degrees on the Online Manipal website. MUJ’s online courses are recognized by UGC, and the online MBA is also recognized by UGC. Other than these, the university is also recognized and accredited by the following: All India Council for Technical Education (AICTE) World Education Services (WES) The Association of Commonwealth Universities (ACU) International Credential Assessment Service of Canada International Qualifications Assessment Service (IQAS) International Credential Evaluation Service (ICES) Read more: How to switch your career: things to consider
Is Data Science a good career option for you? In today’s scenario, data science is one of the most trending programs to choose. A significant proportion of advancement is witnessed in the world of IT divisions from organizations of all scales. Therefore, recruiters are all currently on the lookout for employees who are pursuing this subject. Data science establishes an understanding in you to comprehend data and combine it fittingly to communicate better, proving it useful for the respective organization. Therefore, the search for those students who can work with data admirably is on a high radar for recruiters. Before evaluating whether data science is a good career option, let us understand what it is and its importance. What is data science? Data science is the study and analysis of data to draw out substantial, meaningful insights for businesses. It is a multidisciplinary perspective that blends principles and practices from the spheres of mathematics, artificial intelligence (AI), statistics, and computer engineering to surveying large portions of data. This analysis helps data scientists ask and answer questions regarding what and why of the situation, followed by future speculations and solutions. Importance of data science Data science is significantly essential because it amalgamates tools, technology, and methods to produce meaning from the data surveyed or available. Most modern organizations are overburdened with data; there is a propagation of devices that can automatically accumulate and stockpile information. Payment portals and online systems apprehend more data in e-commerce, finance, medicine, and every aspect influencing human life. We have vast text, audio, video, and image data. Is Data Science a good career choice? Data science can be considered an intellectually claiming field of study and profession. To excel as a data scientist, you are required to fancy quantitative areas and be present to sanction firms to construct data-driven decisions. Therefore, programming languages like Python, SAS, or R are essential to learn here. Moreover, it would be beneficial if you went over your mathematical skills, with a spotlight on probability, statistics, and multivariate calculus. Finally, it would be advantageous if you were familiar with data visualization tools like Tableau. It is also advised to learn coding as a fresher, as even a slight change in parameter can alter results, and there is a very minute margin for committing mistakes. Then, as you move forward in your career as a data scientist, you will concentrate on machine learning algorithms, deep learning, natural language processing, and other related areas that have a foundation in unstructured data and big data. Is data science a good career option? This question is mainly answered by the statistical growth witnessed in this field. Data science has undergone a 650% growth in job options since 2012. Thus, the field of data science is expanding massively and is a good career choice. Reasons to pursue data science Data scientists are pivotal for any firm; they construct better business decisions. Therefore, firms depend on them and use their expertise to offer better solutions to clients. This is the main reason they hold a special position in the company. High demand Data Science is flourishing at a great speed as a career, and it is affirmed that there will be 11.5 million jobs in creation by 2026. This is proof enough to state that it is a high-demand job area. Data science is believed to be less saturated than other IT areas. Data science is an exceptionally bounteous field of the profession with many opportunities. Career and salary A career in data science will make you eligible for a handsomely paying job position. For example, an elementary-level data scientist can earn around ₹500,000 per annum with less than one year of experience. On the other hand, inaugural-level data scientists with one to four years of experience have an earning potential of over ₹600,000 per annum. A versatile field There are ample applications of data science. Mostly, it is used in banking, e-commerce industries, healthcare, and consultancy services, making the applicability of data science very versatile. Therefore, it will allow you to work in several fields. Improving the state of the data Skilled data scientists process and analyze a firm’s data. They refine the data quality along with analyzing it. Therefore, they work with enriching data, making it more useful for the firm. Take a step towards your dream future If you want a professional transition, shifting to data science is the biggest trend in today’s scenario. If you have pursued your bachelor’s in a relevant field that has established an IT base in your portfolio, pursuing a Master of Science in data science will be the most beneficial. Online Manipal is an online platform which provides the Master of Science in Data Science from Manipal University of Higher Education (MAHE). If you are well-versed in the following skills, it is advised to pursue data science as a career transition for bagging the best opportunities in the job market: Probability and statisticsProgramming languages and softwareData wranglingDatabase managementData visualizationMachine learning and deep learningCloud computing Learn more about the said course by visiting our course page. We are here to make online degree courses as approachable as possible across the country so enroll today and earn your degree!
