5 Free Online Courses from MIT University Teaching You High-Income Skills

Make more money with these sought-after skills

The Internet became the best resource for learning skills. It gives access to everyone, regardless of their financial status, geographical location, and age. That truly democratizes education and money-making opportunities.

If you want to improve any aspect of your life, you can use free resources from the Internet—no more excuses. And if you still don’t know where to start — begin with learning a skill to monetize.

Many excellent universities are providing free online courses. The Massachusetts Institute of Technology is committed to promoting knowledge and teaching students in science, technology, and other fields in the twenty-first century.

Learn about five free online courses from the Massachusetts Institute of Technology and determine which suits you and your goals.

Introduction to Computational Thinking and Data Science

You will learn to utilize computing to achieve various goals and be introduced to some computational problem-solving concepts.

This course is designed for students with previous Python programming expertise and a basic understanding of computational complexity. You will spend significant time building programs to apply the course principles.

What you will learn:

• Curve fitting
• Random walks
• Statistical fallacies
• Dynamic programming
• Monte Carlo simulations
• Probability and distributions
• Plotting with the pylab package
• Advanced programming in Python 3
• Knapsack problems, Graphs, and graph optimization

Becoming an Entrepreneur

MIT-partnered Becoming an Entrepreneur guides people of all ages and backgrounds through business development. This course will inspire you to start a business and help you overcome its first hurdles.

The course uses MIT’s Disciplined Entrepreneurship, lean processes, and design thinking to generate new company ideas, conduct market research, design and test your offering, and pitch. Short videos and exercises will push you to step off your computer and into the community to make a difference.

You do not need any business or entrepreneurial experience to participate in this course.

What you will learn:

• Identifying business opportunities
• Designing and testing your offer
• Overcoming the Top Entrepreneurial Myths
• Defining your goals as an entrepreneur and startup
• Conducting market research and selecting your target customer
• Planning your company’s logistics, as well as pitching and marketing to consumers

Machine Learning with Python: From Linear Models to Deep Learning

Computer systems, physics, and engineering employ machine learning. Search engines, recommender systems (Netflix, Amazon), advertising, and financial institutions use machine learning algorithms for content suggestion, consumer behavior, compliance, and risk prediction.

Machine learning designs and studies computer algorithms that learn from experience to predict or govern.

Students will master techniques and ideas for automating training data predictions in this course.

What you will learn:

• Select appropriate models for various applications
• Understand the principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning.
• Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models
• Implement and manage machine learning projects, including training, validation, parameter tweaking, and feature engineering

Introduction to Computer Science and Programming Using Python

This is the first of two courses: Introduction to Computer Science and Python Programming, and Introduction to Computational Thinking and Data Science.

They are intended to enable people who have yet to gain prior experience with computer science or programming to learn to think computationally and develop programs to solve relevant problems.

Some students may utilize the two courses as a stepping stone to more complex computer science courses, but it will be their first and final computer science course for many.

This course gives students a quick overview of various topics to understand what is feasible when they need to think about how to utilize computation to achieve a goal later in their careers.

What you will learn:

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

Data Analysis: Statistical Modeling and Computation in Applications

Data science requires various skills, including mathematics, statistics, machine learning, problem-solving, programming, visualization, and communication.

In this course, students will combine these fundamental and practical skills with domain knowledge to ask and answer questions based on real-world facts.

This course will begin with an overview of standard statistical and computational techniques such as hypothesis testing, regression, and gradient descent methods.

Learners will be guided through analyzing an accurate data set from each area of concentration and presenting their results in written reports. They will also debate relevant and practical concerns with peers.

What you will learn:

• Model, form hypotheses, perform statistical analysis on accurate data
• Apply dimension reduction techniques, such as principal component analysis, to display high-dimensional data in genomics
• Analyze networks (for example, social networks) and apply centrality metrics to explain the significance of nodes, and then apply this to criminal networks
• Forecast time series utilizing moving average, autoregressive, and other stationary models using financial data
• Model environmental data and create predictions using Gaussian processes.
• Effectively communicate analysis results

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