Thread by @heyshrutimishra

MIT University released online courses for FREE worldwide.

11 must-have courses for 2024 you cannot afford to miss:

(Bookmark for later)

1. 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-…

2. 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…

3. 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…

4. 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/…

5. Introduction to Computational Thinking and Data Science

Topics:

• Plotting with the pylab package

• Stochastic programming and statistical thinking

• Monte Carlo simulations

edx.org/learn/computer…

6. 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…

7. 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…

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/…

9. 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…

10. Math Methods for Quantitative Finance:

Topics:

• Probability and Statistics

• Stochastic processes: Brownian motion, Itô calculus, derivative pricing

• Optimization: Lagrange multipliers, Markov processes

edx.org/learn/finance/…

11. Derivatives Markets: Advanced Modeling and Strategies

Topics:

• Advanced derivatives pricing approaches adaptable to valuing new products

• The many ways to shape risk exposure with derivatives

edx.org/learn/finance/…

That's a wrap!

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