Many courses are free to learn. Some offer optional (paid) certificates that may help your career.
Data Science uses statistical methods. You can learn basic statistics here if it is not part of your course.
Data Science frequently uses Excel. We also list dozens of relevant courses.
Data Science may require programming. If not included in your course, you can learn Python (which is easier) or R (for heavy statistical analysis) separately.
1. Data Science Online Courses at Coursera
Coursera is a large provider of online courses from universities and companies. Learners can choose between introductory courses and longer course series over several months. The courses are usually professional with high-quality content.
IBM's What Is Data Science is a short course for absolute beginners. It takes a couple of hours to complete and gives you an overview of the subject.
The Crash Course in Data Science from Johns Hopkins University also gives a brief overview for learners without much prior knowledge.
More than 300,000 students have already taken Intro to Data Science in Python. This course from the University of Michigan gives an introduction to the field based on Python.
The Intro to Data Science Specialization is for learners who want to get a full professional training. The program takes approximately one month to complete and includes Python and SQL.
A more extensive course series is the Data Science Specialization. It consists of 10 online courses and includes R programming and machine learning. It will take several months to complete.
EdX is similar to Coursera in terms of the course content and quality. They offer courses from universities such as Harvard and Berkeley and also list corporate training programs (for example, from Microsoft).
Introduction to Data Science gives an easy introduction to a longer course series from Microsoft. It explores working with data mainly in Excel and introduces data visualization and statistical concepts in Big Data.
Microsoft also has two online courses about the relevant programming languages in the field, Python for Data Science and R for Data Science. Both courses have already been taken by several hundred thousand students.
UC Berkeley's Foundations of Data Science consists of three courses that include Python as well as machine learning. It is designed for beginners without coding or statistics knowledge who want to get an in-depth training.
Harvard University offers one of the most extensive course series in Data Science. It is based on the R programming language (which is part of the courses) and also includes machine learning and other more advanced topics.
Columbia University's Data Science for Executives offers an introduction to the field for business managers who "want to understand basic concepts in Data Science without getting into the weeds of programming".
The MicroMasters Program in Statistics and Data Science takes about one year to complete and is based on the on-campus courses at MIT.
Udemy's courses are created by individual experts, not by universities. Some learners find their courses to be hands-on but less focused on theoretical concepts. The quality can vary a lot between courses. These are some of their popular courses:
Data Science A-Z aims to take learners from no prior knowledge to data science expert through 200 video lessons. The teacher is a data scientist who claims to have taught more than one million online students overall.
Data Science and Machine Learning With Python is for learners who have some prior coding experience and at least high school-level math skills. It also covers more advanced machine learning and deep learning topics.
Udacity is another leading online learning provider and creates its own course content. It also offers nanodegrees, which are in-depth course series that aim to be an accepted industry standard in their field.
Intro to Data Science is a free beginners course that offers a general introduction and first insights into data analysis and visualization.
The well-known Data Science Nanodegree requires some prior experience in coding, machine learning and statistics. While strictly speaking it can be suitable for some beginners in Data Science, it is actually targeted at more experienced programmers. It takes four months to complete and was designed with industry partners such as IBM and Bertelsmann.
