Environment Setup-Welcome!
Welcome to the Specialization!
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Welcome to Course 1!
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What can you expect from this course/specialization?
Python Environment Setup
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Introduction to the Databricks Ecosystem for Data Science
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Introduction to the Fundamentals of Probability-Belief and probability
Introduction and references
Introductions
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Chance regularities and random processes
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Outcomes, events and spaces
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Introduction to the Fundamentals of Probability-Rules for manipulating probability
Rules for manipulating probability
Addition rules of probability
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Multiplication rules of probability
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Conditional probability, Random Variables and Experiments
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Introduction to the Fundamentals of Probability-Introduction to distributions
Random variables
Random Variables and Distributions
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Moments, mean and variance
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Joint distributions of Random Variables
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Introduction to the Fundamentals of Probability-Estimation using MoM and MLE
MoM and MLE
Estimation using MoM and MLE
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Introduction to the Fundamentals of Probability-Decisions, loss and priors
Bayes' and decisions
Basics of Bayes' Rule
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Decisions and Loss Functions
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Loss functions
Introduction to the Fundamentals of Probability-More on Priors
More on priors
Priors introduction
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Priors as conjugates
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Informative vs non-informative priors
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Jeffrey's Prior
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Prior distributions and posterior ramifications
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A Hands-On Introduction to Common Distributions-Some Common Distributions
The Binomial Distribution
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Negative Binomial Distribution
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Poisson Distribution
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Exponential Distribution
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Gamma Distribution
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Normal Distribution
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Lognormal Distribution
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Student's t-distribution
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Beta Distribution
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Reference
Reference
A Hands-On Introduction to Common Distributions-Maximum Likelihood Estimation
MLE Estimation using a Beta Distribution
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Gaussian Mixture Model
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A Hands-On Introduction to Common Distributions-Non-parametric Methods
Non-parametric Methods: Kernel Density Estimation
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Sampling Algorithms-Sampling Algorithms
Introduction to Sampling
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The Inverse Transform Algorithm
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Rejection Sampling
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Importance Sampling
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Sampling Algorithms-Bayesian vs. Frequentist Algorithms
Differences between the Bayesian and the Frequentist
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Features of Bayesian and Frequentist Inference
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Reference
Bayesian vs. Frequentist Inference