README.md

UCSanDiegoX: DSE210x: Statistics and Probability in Data Science using Python

Instructors :

• Alon Orlitsky, Professor, ECE and CSE Departments, UCSD
• Yoav Freund, Professor, ECE Department, UCSD

Learning Objectives

The course will teach you how to visualize, understand, and reason about probabilistic and statistical concepts, and how to apply your knowledge to analyze data sets and draw meaningful conclusions from data. They will cover both theoretical and practical aspects, and will start each topic with motivation and intuition and will proceed with rigorous arguments and provable techniques. Each topic will be accompanied by a Python Notebook that you could run and modify to experiment with the material learned and get a better feel for the material covered.

Topics Covered

• Counting and combinatorics
• Discrete and continuous probability
• Conditional probability and Bayes’ Rule
• Random variables
• Expectation, variance, and correlation
• Common distribution families
• Probabilistic inequalities and concentration
• Moments and limit theorems
• Hypothesis testing
• Sampling and confidence intervals
• PCA and regression
• Entropy and compression

Opinion/Comments

I audited for this course and pledged to complete it. I finished every Engagement, Quiz, Problem Set and Programming Assignment. This is a rigorous course which might be heavy for non-mathematical background learners. Once completed you will surely have a strong foundation in probability and statistics.

I have provided my Homeworks here (as an evidence of finishing and maintaining a repository for the course), which I completed during a month's time.

Thanks for passing by!