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360-in-525 Courses
This is an Uppsala-Big-Data-Meetup
Download .dbc Course Contents
360-in-525 POA
360-in-525-1
360-in-525-2
360-in-525-3
360-in-525-4
00. Introduction
01. BASH crash
02, Numbers, Strings, Booleans and Sets
03. Map, Function, Collection, and Probability
04. Conditional Probability, Random Variables, Loops and Conditionals
05. Random Variables, Expectations, Data, Statistics, Arrays and Tuples, Iterators and Generators
06. Statistics and List Comprehensions with New Zealand Earthquakes
07. Modular Arithmetic, Linear Congruential Generators, and Pseudo-Random Numbers
08. Pseudo-Random Numbers, Simulating from Some Discrete and Continuous Random Variables
09. Estimation, Likelihood, Maximum Likelihood Estimators and Symbolic Expressions
10. Markov Chains
11. Limits, Convergence, and Estimation
12. Non-parametric Estimation and Testing
360-in-525-5
360-in-525-0
As an importable databricks notebook
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