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/…
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