5 free courses by MIT that you need to consider taking in 2025

There are many courses available for students and professionals to hone their skills so that they are in tune with what the employers are on the lookout for.

There is a growing need for professionals and students to learn more skills and stay updated with the latest developments in the job market.

Here are 5 free courses from the Massachusetts Institute of Technology (MIT), that everyone can learn and explore.(Unsplash)

There are many courses that are available for students and professionals to hone their skills and knowledge so that they are in tune with what the employers are on the lookout for.

Here are 5 free courses from the Massachusetts Institute of Technology (MIT), that everyone can learn and explore.

Fundamentals of Statistics:

This course aims to allow the participants to expand their statistical knowledge to not only include a list of methods, but also the mathematical principles that link them together, equipping you with the tools you need to develop new ones.

What participants can learn:

• Construct estimators using method of moments and maximum likelihood, and decide how to choose between them
• Quantify uncertainty using confidence intervals and hypothesis testing
• Choose between different models using the goodness of fit test
• Make prediction using linear, nonlinear and generalized linear models
• Perform dimension reduction using principal component analysis (PCA)

Becoming an Entrepreneur:

Are you curious about being an entrepreneur but cannot decide where to start? From developing new business ideas and doing market research to designing and testing your offering and pitching, this course by MIT aims to impart knowledge about entrepreneurship and does not need any previous business or entrepreneurship experience.

What participants can learn:

• Overcoming the top myths of entrepreneurship
• Defining your goals as an entrepreneur and startup
• Identifying business opportunities
• Performing market research and choosing your target customer
• Designing and testing your offering
• Planning your business logistics, plus pitching and selling to customers

Collaborative Data Science for Healthcare:

As per the official website, this course provides an introductory survey of data science tools in healthcare through several hands-on workshops and exercises. Participants who are interested in learning this course will benefit if they have experience with R, Python and/or SQL, unless the course is taken with computer scientists in the team.

What participants can learn:

• Principles of data science as applied to health
• Analysis of electronic health records
• Artificial intelligence and machine learning in healthcare

Data Analysis: Statistical Modeling and Computation in Applications:

This course aims to guide learners to analyse a real data set from each of these areas of focus and present their findings in written reports. They will also discuss relevant and practical issues with peers.

Participants will combine these foundational and practical skills with domain knowledge to ask and answer questions using real data, mentioned the official website.

What participants can learn:

• Model, form hypotheses, perform statistical analysis on real data
• Use dimension reduction techniques such as principal component analysis to visualize high-dimensional data and apply this to genomics data
• Analyse networks (e.g. social networks) and use centrality measures to describe the importance of nodes, and apply this to criminal networks
• Model time series using moving average, autoregressive and other stationary models for forecasting with financial data
• Use Gaussian processes to model environmental data and make predictions
• Communicate analysis results effectively

Introduction to Computer Science and Programming Using Python:

This course aims to introduce knowledge of computation and help the participants in writing programs to tackle problems. Students without prior programming background will find there is a steep learning curve and may have to put in more than the estimated time effort, mentioned the official website.

What participants can learn:

• A Notion of computation
• The Python programming language
• Some simple algorithms
• Testing and debugging
• An informal introduction to algorithmic complexity
• Data structures

For more information, visit the official website.