MIT University launched free Ai online courses.
No payment is required.
Below are 10 courses you don't want to miss in 2026:
1. Introduction to Computer Science and Programming Using Python.
Topics:
• A Notion of computation
• Python programming language
• Some simple algorithms
• Informal introduction to algorithmic complexity
• Data Structures and more
🔗 edx.org/learn/computer…
Topics:
• A Notion of computation
• Python programming language
• Some simple algorithms
• Informal introduction to algorithmic complexity
• Data Structures and more
🔗 edx.org/learn/computer…
VIDEO
2. Machine Learning with Python
Topics:
• ML problem principles
• Implement & analyze models
• Choosing suitable models for different apps
• ML project implementation: Training, validation, tuning, and feature engineering
🔗 edx.org/learn/machine-…
Topics:
• ML problem principles
• Implement & analyze models
• Choosing suitable models for different apps
• ML project implementation: Training, validation, tuning, and feature engineering
🔗 edx.org/learn/machine-…
VIDEO
3. Supply Chain Analytics
Topics:
• Basic analytical methods
• How to apply basic probability models
• Statistics in supply chains
• Formulating and solving optimization models
🔗 edx.org/learn/supply-c…
Topics:
• Basic analytical methods
• How to apply basic probability models
• Statistics in supply chains
• Formulating and solving optimization models
🔗 edx.org/learn/supply-c…
VIDEO
4. Understanding the World Through Data.
Topics:
• Python programming and the Colab notebook programming environment
• Dependent and independent variables
• Relationships between data using linear and polynomial regression models
And more
🔗 edx.org/learn/data-sci…
Topics:
• Python programming and the Colab notebook programming environment
• Dependent and independent variables
• Relationships between data using linear and polynomial regression models
And more
🔗 edx.org/learn/data-sci…
VIDEO
5. Becoming an Entrepreneur
Topics:
• 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
🔗 edx.org/learn/entrepre…
Topics:
• 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
🔗 edx.org/learn/entrepre…
VIDEO
6. Computational Thinking for Modeling and Simulation
Topics:
• Interpolation methods and their impact on model convergence
• Numerical integration techniques
• Procedures for numerical differentiation
• Solving linear and nonlinear equations
🔗 edx.org/course/entrepr…
Topics:
• Interpolation methods and their impact on model convergence
• Numerical integration techniques
• Procedures for numerical differentiation
• Solving linear and nonlinear equations
🔗 edx.org/course/entrepr…
7. Foundations of Modern Finance
Topics:
• Valuation of fixed income securities and common stocks
• Risk analysis, APT, Efficient Market Hypothesis
• Introduction to corporate finance and capital budgeting and more
🔗 edx.org/learn/finance/…
Topics:
• Valuation of fixed income securities and common stocks
• Risk analysis, APT, Efficient Market Hypothesis
• Introduction to corporate finance and capital budgeting and more
🔗 edx.org/learn/finance/…
VIDEO
8. The Secret of Life
Topics:
• How to describe the building blocks of life and how their interactions dictate structure and function in biology
• How to predict genotypes and phenotypes given genetics data and more
🔗 edx.org/learn/biology/…
Topics:
• How to describe the building blocks of life and how their interactions dictate structure and function in biology
• How to predict genotypes and phenotypes given genetics data and more
🔗 edx.org/learn/biology/…
VIDEO
10. The Science of Uncertainty and Data
Topics:
• The basic structure and elements of probabilistic models
• Random variables, their distributions, means, and variances
• Probabilistic calculations
• Inference methods and more
🔗 edx.org/learn/probabil…
Topics:
• The basic structure and elements of probabilistic models
• Random variables, their distributions, means, and variances
• Probabilistic calculations
• Inference methods and more
🔗 edx.org/learn/probabil…
VIDEO
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