UC San Diego MicroMasters Data Science "Probability and Statistics in Data Science using Python"

DSE 210 "Probability and Statistics in Data Science using Python" (Winter 2018) by Alon Orlitsky and Yoav Freund, Professors of CS and Engineering, UC San Diego. Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Part 2 of »Data Science« MicroMasters®, completed 01-Sep-2019

About this course

The job of a data scientist is to gain knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.

Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.

What you'll learn

The mathematical foundations for machine learning
Statistics literacy: understand the meaning of statements such as "at a 99% confidence level"

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
1.Linear_Algebra_Review.ipynb		1.Linear_Algebra_Review.ipynb
1.Regression I.ipynb		1.Regression I.ipynb
1.What-is-Probability.ipynb		1.What-is-Probability.ipynb
10_inequalities.ipynb		10_inequalities.ipynb
11_Statistics_lecture_notebook_.ipynb		11_Statistics_lecture_notebook_.ipynb
2.Matrix_notation_and_operations.ipynb		2.Matrix_notation_and_operations.ipynb
2.Regressing to the mean.ipynb		2.Regressing to the mean.ipynb
2.What-is-Statistics_.ipynb		2.What-is-Statistics_.ipynb
3.Long-term-frequencies.ipynb		3.Long-term-frequencies.ipynb
3.Polynomial Regression.ipynb		3.Polynomial Regression.ipynb
3.Solving_a_system_of_Equations.ipynb		3.Solving_a_system_of_Equations.ipynb
4.PCA.ipynb		4.PCA.ipynb
4.The-Three-card-Puzzle.ipynb		4.The-Three-card-Puzzle.ipynb
6_conditional_probability_hw.ipynb		6_conditional_probability_hw.ipynb
Counting Notebook.ipynb		Counting Notebook.ipynb
HW_4.ipynb		HW_4.ipynb
HW_Topic1.ipynb		HW_Topic1.ipynb
HW_Topic2.ipynb		HW_Topic2.ipynb
HW_Topic7.ipynb		HW_Topic7.ipynb
Permutations and Combinations Notebook.ipynb		Permutations and Combinations Notebook.ipynb
README.md		README.md
Syllabus_For__Probability__and_Statistics___in___Data___Science___using___Python.pdf		Syllabus_For__Probability__and_Statistics___in___Data___Science___using___Python.pdf
Titanic.ipynb		Titanic.ipynb
Topic13_Lecture.ipynb		Topic13_Lecture.ipynb
Topic4_Lecture.ipynb		Topic4_Lecture.ipynb
Topic5_Lecture.ipynb		Topic5_Lecture.ipynb
Topic6_Lecture.ipynb		Topic6_Lecture.ipynb
Topic8_Lecture.ipynb		Topic8_Lecture.ipynb
Topic9_Lecture.ipynb		Topic9_Lecture.ipynb
dice_HW.ipynb		dice_HW.ipynb
inequalities_HW.ipynb		inequalities_HW.ipynb

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