10 mins
What is Data Science?
Data Science in simple terms is an integration of statistics and computer science. It has applications in myriad industries. Data science jobs involve using procedures and algorithms to analyze vast datasets, aiming to create predictive models, support decision-making, discover patterns, and offer valuable insights. Clearly, every business niche can and does use data science to improve its business model, bottom lines, productivity and competitiveness in the marketplace. This is why an MSc in data science is such a great option for an exciting career for you.
Is a Data Science course the right fit for you?
If you have an aptitude for Mathematics and Statistics and have the willingness to learn, Data Science is a field that you can explore. Here are some more questions you can ask yourself to get better clarity on whether to choose a Data Science course or not.
- Do you have a solid foundation in mathematics and statistics?
- Can you imagine yourself doing analytical tasks where you assess large datasets to derive meaningful insights?
- Are you willing to invest in continuous learning as this is an ever-evolving field?
- Do you have the necessary communication skills to communicate your findings with a larger group? If not, are you ready to work on it?
- Will you find excitement in exploring data and uncovering patterns?
If your answers to these questions were yes, you can indeed give the Data Science course a try.
Best countries to study Data Science
The USA, the UK, Australia and Canada are some of the best countries to study Data science abroad. Several universities from these countries made it to the QS World University Rankings by Subject 2024 for Data Science.
- 19 universities from the USA were listed in the QS rankings by Subject, 2024. Of these, 4 universities made it to the top 5.
- The UK has 6 universities on the list including the University of Oxford at position 4.
- The 7 universities from Australia that made it to the 2024 ranking list include the University of Melbourne, Monash University and the University of Technology, Sydney.
- The best university in Canada for Data Science and AI courses is the University of Toronto.
Top-ranking universities for Data Science
MSc data science is a sought-after postgraduate credential and many universities across the world offer it. If the ranking of the university is important to you, you can refer to reputed ranking lists like the QS World University Rankings to decide on the universities to apply to. The top twenty universities offering Data Science courses and featured in the QS World University Rankings 2024 are as follows:
|
Rank |
University |
| 1 | Massachusetts Institute of Technology (MIT), USA |
| 2 | Carnegie Mellon University, USA |
| 3 | University of California, Berkeley (UCB), USA |
| 4 | University of Oxford, UK |
| 5 | Harvard University, USA |
| 6 | National University of Singapore (NUS), Singapore |
| 7 | ETH Zurich, Switzerland |
| 8 | Nanyang Technological University, Singapore (NTU Singapore) |
| 9 | The University of Toronto, Canada |
| 10 | The Hong Kong University of Science and Technology, Hong Kong SAR |
| 11 | EPFL – École polytechnique fédérale de Lausanne, Switzerland |
| 12 | The University of Washington, USA |
| 13 | Georgia Institute of Technology, USA |
| 14 | University of Illinois at Urbana-Champaign, USA |
| 15 | Princeton University, USA |
| 16 | Cornell University, USA |
| 17 | New York University (NYU), USA |
| 18 | UCL, UK |
| 19 | Imperial College London, UK |
| 20 | The Chinese University of Hong Kong (CUHK), USA |
| 20 | The University of Pennsylvania, USA |
Universities picked by Indian students for Data Science courses
Not everybody can make it to top-ranking universities. Seats are limited and the admission process is highly competitive. However, several other reputed universities and colleges offer Data Science courses. Here’s a list of universities from countries like the USA, the UK, Australia and Canada that were preferred by a large number of Indian students.
Popular universities in the USA:
- The University of New Haven
- The University of North Texas
- New Jersey Institute of Technology
- The University of Alabama Birmingham
- The University of Massachusetts
Popular universities in the UK:
- The University of Hertfordshire
- The University of Essex
- The University of Leeds
- Coventry University
- The University of Liverpool
Popular universities in Australia
- RMIT University
- Deakin University
- Monash University
- La Trobe University
- The University of Western Australia
Popular universities in Canada
- Carleton University
- Thompson Rivers University
- The University of Calgary
- Loyalist College
- The University of Waterloo
How to decide where to study Data Science?
Here are 8 ways to decide where to study Data Science. (The key to making this decision is to collect as much information as possible, about the course and university options, your interests and preferences).
- Ask questions to yourself to figure out your interests before you start looking for course options.
- Look for top-ranking universities in the field of Data Science and see if you like any. (Keep in mind that universities that do not make it to the top-ranking list too, offer unique course options).
- Analyse the course options and the universities offering these courses.
- Go through the course details to understand whether it aligns with your interests and career aspirations.
- Are you concerned about the financial aspects? Look for institutions that offer courses at a cheaper rate or ones that offer scholarships that considerably support you with your finances.
- Are you more focused on learning from the experts? If you are aware of well-known personalities in the field of Psychology, you can apply to institutions where they offer lectures.
- Are job opportunities your priority? Look for institutions that offer career guidance and internship programmes.
- Speak to alumni and faculty at the universities you are applying to, to gather a better understanding of the campus, facilities and opportunities.
Subject specialisations: Course options for a masters in Data Science
Different universities offer different options with their MSc in data science. The course work may have the basic/ foundational subjects covered but add more to it, take a different spin on specializations or give you a more in-depth look into the business aspects. Before you enrol or even apply, it is best to thoroughly look through what the course encompasses and whether it is aligned with your career plans, in general. It also helps to begin with a fair idea of what kind of data science courses are offered by various universities abroad:
1. MSc Data Science and Analytics: A course that trains you to understand Big Data, its implications in the real world and ways to make the best of the transformation happening in the niche. The emphasis may be on future tech, security, and impact on the everyday life of humans.
2. MSc data science, Global public health: This is a common slant on data sciences courses to take, with healthcare being one of the prime areas where data science can yield incredible value. The focus would be on the important insights that data can give and the benefits of such insights in addressing public health concerns. Policy making based on hard evidence, strategizing to address diseases of various kinds, and improving health and lifestyle overall could all form a part of such a course.
3. MS or MSc data science (Mathematics): This course emphasises the study of data to make accurate predictions in several niches. Understanding how to sift through the massive quantum of data, identify relevant parts, analyse it accurately and then leverage it to make decisions, these are covered. The course would equip you with the computational skills you need to achieve all of these objectives depending on the industry that seeks them.
4. MSc data science with research focus: Data science companies prefer graduates equipped with a sound grounding in knowledge and techniques on the research side as well. Data science is still an emerging technology and innovation is the key to success here. Further research in the field is valued highly and so, graduates with research abilities and critical thinking skills are easily employable.
5. MSc data science and Artificial Intelligence: With AI growing in importance in every aspect of life, a data sciences course that trains you to devise data-driven AI solutions for industrial applications is very valuable. This course would give you complete technical expertise in both data science and AI, even if you do not have a very strong computer science background.
6. MSc data science, data interpretation: Another skill set with far-reaching application, this course is aimed at training you to interpret data in myriad ways for deriving different solutions. Also key here is the training in managing, analysing, interpreting and leveraging data trends at micro as well as global scales.
7. MSc data science, Security: Be it cybersecurity at the business level national level or even global level, data sciences can prove their worth in gold. These courses are designed to give you practical skills and thorough training in taking raw data and transitioning it into an accurate, actionable foundation for quick decision-making. Visualization and ethics will form a big part of the coursework.
8. MSc data science specializations for computer grads: If you are a computer science graduate seeking to specialize in a specific niche, these data science courses may be ideal. Thanks to your previous grounding, these courses can jump in to delve deeper into the specialisation and train you to make sense of the immense, heterogeneous data that we have at hand in nearly every field. You are trained to analyse complex data, develop powerful insights and come up with innovative strategies in your area of specialization.
9. MSc data science– data extraction: To optimally utilize the power of data, it is critical to understand how to extract it thoroughly and without impairment. These courses have an emphasis on data extraction, using mathematical, computing and statistical skill sets and help train you to glean relevant, meaningful and highly valuable data. The course also trains you for the correct use of data, accurate analysis and modelling as well.
10. MSc data science, Analytics: While analytics is a part of any data science course generally, these courses heavily focus on this aspect to train students in handling the sheer magnitude of data that is available. Students are trained to develop new methods to capture, segregate and group data from networked systems for the most efficient and thorough analysis using automated tools to arrive at usable information.
What will you learn in your MSc data science course?
While each MSc data science program will come with its own unique curriculum, post-graduation in data sciences typically covers the following areas comprehensively:
- A deeper introduction to data science in terms of its industrial relevance
- Theoretical and practical knowledge in data science development
- Training in using software to analyse data
- Using machine learning algorithms to analyse and utilize data
- Data synthesis
- Data science management
- Understanding the lifecycle of data in a business organization
- Problem-solving using data for key business problems
- Data science legalities and ethics
- Using data in decision-making for the business
- Strategic modelling
Typically, the MSc program will train students in optimally leveraging all forms of data, text, biometrics and visuals. Most programs come with hands-on experience and research projects too so you get practical training and exposure to how your knowledge can be applied in the field.
Some universities allow you to customize your MSc data science to the specific business niche that you wish to enter post-graduation. For example, the American University program lets you choose a specialization that will hone your MSc towards cybersecurity or micro, economic analysis, applied public affairs or a host of other options. The University of the Arts, London, has an MSc data sciences and AI program specifically designed for the creative industries that train you for content creation, software development, digital product development and more for these industries.
Entry Requirements for studying Data Science abroad
Each university may differ slightly in what they require from students who want to enrol in their data science post-graduate program. But a quick overview of typical eligibility requirements tells us the basic eligibility requirements are as follows:
- A bachelor’s degree from a regionally accredited institution, some universities may insist on a related bachelor’s degree, for example, in engineering or computer sciences
- Minimum grades on undergraduate courses may also be specified, e.g.: 60% minimum
- TOEFL minimum score of 95 iBT/ IELTS minimum score of 6.5 to 7 with no band score below 6 to 6.5
Data Science Course Fee
|
Destination |
Approximate tuition fee per year |
|
USA |
Postgraduate courses: 18 – 28 lakhs/year Undergraduate courses: 27 – 33 lakhs/year |
|
UK |
Postgraduate courses: 14 – 29 lakhs/year Undergraduate courses: 14 – 23 lakhs/year |
|
Australia |
Postgraduate courses: 9 – 23 lakhs/year Undergraduate courses: 18 – 21 lakhs/year |
|
Canada |
Postgraduate courses: 9 – 15 lakhs/year Undergraduate courses: 12 – 24 lakhs/year |
Career Prospects
Big data is one of the fastest evolving areas today and data science companies are witnessing dramatic growth. There is much to learn yet with this field and this only means that there are enough data science jobs in the application as well as research end of the marketplace.
Since data science is used in literally every industry and across the globe, there is no dearth of employment opportunities even for someone who has just covered an introduction to data science with a graduate program. For example, data science students are employable in any of these fields:
- Healthcare
- Business
- National security
- Education
- Marketing/ Advertising
- Investment and Finance
- Insurance
- Engineering/ construction
But for someone with an MSc and much deeper and comprehensive training in this area, the career opportunities and the pay packages are impressive. An MSc gives you the training you need to move higher up in the hierarchy and into a role where you can directly impact management decisions.
Here are some roles that you could fit into once you complete your MSc:
- Data analyst: Extraction of data from different courses, processing immense amounts of data, maintaining and upgrading databases, analysing data to predict trends or improve quality outcomes, all of these will form part of your work.
- Business Intelligence developer: You will be designing strategies to help your organization access critical information in the minimum possible time to improve response times and outcomes. You would also be addressing end-user solutions using data science applications.
- Statistician: For those who love juggling numbers, this job could be a dream come true. Statisticians gather, segregate and analyse data to arrive at insights and solutions to various problems. They also help develop new strategies for data collection and analysis.
- Application architect: Designing and managing applications that enable the use of data to deliver solutions or facilitate solutions is your job description. You would also assess existing applications, upgrade them and see how they work with end users.
- Data scientist: Beginning with extracting relevant data and basic data analysis to data modelling and maintenance, a data scientist does all of this and more. You will also be bridging the gap between the knowledge that the collected data offers and the professionals who can use it, communicating the information to them in an easy-to-understand format.
- Machine learning engineer: Developing and testing machine learning systems, working on algorithms, addressing end-user needs with apps, managing machine learning frameworks and libraries and using statistics to improve outcomes are all part of the job description.
- Data architect: Transforming the needs of the business into technological requirements, laying the groundwork for data standards and building a ground-up model framework that will be used by data scientists, this is your role.
- Database administration: You will be in charge of the storage, management and security of the data starting from database design and evolution. Creating operating manuals, overseeing archiving and retrieval and working with other teams to ensure a seamless flow of data to relevant people will all be your job.
- Business analyst: For those who also get a good grounding in business operations during their MSc data science, this is a great job profile. A business analyst segregates high-value data from the ‘noise’ and formulates frameworks for using relevant Big Data to help with key business decision-making needs.
- Big Data engineer: In this role, you will be focussed more intensely on Big Data infrastructure and tools to collect, assess and evaluate it. You will also be in charge of monitoring and measuring the performance of the frameworks and upgrading where and when needed. More importantly, you will have a say in the policies that determine how data is retained and sifted through in the organization.
Public health, marketing, everyday life, safety, business, and virtually any area you can think of can and does benefit from gathering, assessing and utilizing data. Data science companies are thriving today as we continue to discover exactly how data can help improve outcomes in nearly every aspect of our lives. This is the time to enter this field with a post-graduation from a reputed college where you have honed your skills to perfection, perhaps even specialized in a niche to make yourself a valuable asset to some organisation. If you are interested in computing, technology, statistical data or mathematics, or you are just keen on choosing a line that can make a real difference to many, choosing data sciences could pave the way to a dream career that also pays very well.
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