Data science Specializations and courses teach the fundamentals of interpreting data, performing analyses, and understanding and communicating actionable insights. Topics of study for beginning and advanced learners include qualitative and quantitative data analysis, tools and methods for data manipulation, and machine learning algorithms.
Coursera offers plenty of free data science courses to choose from. For a quick introduction to data science or to brush up on a specific skill, check out University of Michigan’s Data Science Ethics, Eindhoven University of Technology’s Process Mining, Stanford University’s Introduction to Statistics, University of London’s Foundations of Data Science: K-Means Clustering in Python, and Duke University’s Data Science Math Skills.
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IBM’s Data Science Professional Certificate is a comprehensive set of courses that requires no prior knowledge or experience. If you’re looking for a quick deep dive, check out IBM’s What is Data Science? or Johns Hopkins University’s A Crash Course in Data Science, both of which can be completed in a day.
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A popular intermediate course is University of Michigan’s Applied Data Science with Python Specialization, which provides a well-rounded, skill-based introduction to data science. The Applied Data Science Capstone course from IBM is another popular choice. If you have working knowledge of Python programming, data analysis and visualization, SQL, and model development, consider the Advanced Data Science with IBM Specialization, or start with any of the courses within the specialization.
Anyone can learn data science, and no prior knowledge or experience is needed to start learning today. Generally, you should have some computer skills and an interest in gathering, interpreting, and presenting data. Learners with a basic understanding of statistics and coding may be able to skip some of the introductory courses.
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Embarking on a career in data science can be rewarding, especially for analytical thinkers who enjoy coding and working with data. Data scientists should feel comfortable learning various coding languages, maneuvering data systems and tools to collect and analyze data, and using that data to solve problems. Developing strong communication skills helps because you’ll often work with teams to deliver insights. Data science also provides a solid foundation for machine learning and AI, a popular and growing field. In just a few months, you can learn data science skills that can be applied to many industries.
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Beginners may want to consider courses and Professional Certificates since they require less time and money to gain the skills you’ll need to land an entry-level position. If you’re hesitant about signing up for a certificate, you can start with What is Data Science? (the first course in IBM’s Data Science Professional Certificate), or a free course like Introduction to Statistics, both of which are suitable for career switchers.
If you don’t have a bachelor’s degree, and want to invest time and money in one, consider the University of London’s Computer Science program to earn your degree completely online. For those already working in data science, the University of Michigan’s Master of Applied Data Science program could help advance your career.
Within data science, common jobs include data scientist, data analyst, data architect, and data engineer. Data science skills can be extremely useful for business and marketing analysts, who often use system tools to extract and analyze data. It is a high-demand field and skill set, and nearly every industry uses data science in one way or another.
Learn more: Your Guide to Data Science Careers (+ How to Get Started)