5 FREE Harvard Courses to Learn Data Science

1. R Basics:

- In this course you will learn the basic R syntax

- Foundational R programming concepts such as data types, vectors arithmetic, and indexing

- How to perform operations in R including sorting, data wrangling using dplyr, and making plots

2. Machine Learning :

- The basics of machine learning

- How to perform cross-validation to avoid overtraining

- Several popular machine learning algorithms

- How to build a recommendation system

- What is regularization and why it is useful

3. Probability :

- Important concepts in probability theory including random variables and independence

- How to perform a Monte Carlo simulation

- The meaning of expected values and standard errors and how to compute them in R

- The importance of the Central Limit Theorem

4. Visualisation :

- Data visualization principles

- How to communicate data-driven findings

- How to use ggplot2 to create custom plots

- The weaknesses of several widely-used plots and why you should avoid them

5. Linear Regression :

- How linear regression was originally developed by Galton

- What is confounding and how to detect it

- How to examine the relationships between variables by implementing linear regression in R

​6. Inference and modeling

- The concepts necessary to define estimates and margins of errors of populations, parameters, estimates and standard errors in order to make predictions about data

- How to use models to aggregate data from different sources

- The very basics of Bayesian statistics and predictive modeling

Which course would you take?

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