MIT just made its AI classes available online for free.

This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. I go through the course and collect the main outline of each class.

The following ten classes are must-takes in 2024:

1. Using data to understand the world

a. Capabilities in data analysis
b. A few basic algorithms
c. A Computational Notion
d. Data Structures and Additional

Enrol today at MIT Understanding the World Through Data” at https:edx. org/learn/data-science.

2. Python-Based Machine Learning
Model Selection
ML Project Management
Issue Resolution
Apps for the real world

The MIT machine learning programme uses Python to move from linear models to deep learning.

3. Statistics Fundamentals

Create estimators using the maximum likelihood and technique of moments
Analyse data
Concepts related to probability
Practical applications

Fundamentals of Statistics, Massachusetts Institute of Technology, https:edx. org/learn/statistics

4. An Overview of Python Programming and Computer Science

Easy to use for beginners
Teach Python
Address issues
Practical exercises

Register today for the MIT Introduction to Computer Science and Python Programming course at https:edx. org/learn/computer-science.

5. Likelihood The Data-Driven Science of Uncertainty

Concepts related to probability
statistical techniques
data analysis
practical applications

probability, the science of uncertainty and data, at http edx. org

6. Analytics for Supply Chains

A data-driven strategy
Management of the supply chain
Analytical instruments
Use in business applications

The MIT supply chain analytics is available at : https://www.edx.org/learn/supply-chain-design

7. An Overview of Data Science and Computational Thinking.

Monte Carlo models.
using the PyLab programme for plotting.
Probabilistic modelling and statistical reasoning.

Introduction to Computational Thinking and Data-4, available at http:edx. org

8. Starting my own business.

Finding commercial prospects.
creating and evaluating your product.
busting the biggest entrepreneurship myths.

Becoming an entrepreneur at MIT is available at https edx. org/ learn/entrepreneurship.

9. Using Computational Thinking in Simulation and Modelling

Concepts of modelling
Techniques of simulation

The MIT uses computational thinking for modelling and simulation.

10. The Basics of Production Procedures

Production techniques
Design ideas
Sciences of materials

The principles of manufacturing processes at the MIT can be found at https:edx. org/learn/manufacturing/

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