Probabilistic Programming with Python and Julia

Probabilistic Programming with Python and Julia, available at $39.99, has an average rating of 3.65, with 26 lectures, based on 27 reviews, and has 194 subscribers.

You will learn about Introduction to probabilistic programming Bayesian statistics Markov Chain Monte Carlo Gaussian Mixture Models Bayesian Logistic Regression Bayesian Linear Regression This course is ideal for individuals who are Python and Julia users who like to learn probabilistic programming It is particularly useful for Python and Julia users who like to learn probabilistic programming.

Enroll now: Probabilistic Programming with Python and Julia

Summary

Title: Probabilistic Programming with Python and Julia

Price: $39.99

Average Rating: 3.65

Number of Lectures: 26

Number of Published Lectures: 26

Number of Curriculum Items: 26

Number of Published Curriculum Objects: 26

Original Price: €44.99

Quality Status: approved

Status: Live

What You Will Learn

Introduction to probabilistic programming
Bayesian statistics
Markov Chain Monte Carlo
Gaussian Mixture Models
Bayesian Logistic Regression
Bayesian Linear Regression

Who Should Attend

Python and Julia users who like to learn probabilistic programming

Target Audiences

Python and Julia users who like to learn probabilistic programming

You want to know and to learn one of the top 10 most influencial algorithms of the 20th century? Then you are right in this course. We will cover many powerful techniques from the field of probabilistic programming. This field is fast-growing, because these technique are getting more and more famous and proof to be efficient and reliable.

We will cover all major fields of Probabilistic Programming: Distributions, Markov Chain Monte Carlo, Gaussian Mixture Models, Bayesian Linear Regression, Bayesian Logistic Regression, and hidden Markov models.

For each field, the algorithms are shown in detail: Their core concepts are presented in 101 lectures. Here, you will learn how the algorithm works. Then we implement it together in coding lectures. These are available for Python and Julia. With this knowledge you can clearly identify a problem at hand and develop a plan of attack to solve it.

Mastering this course will enable you to understand the concepts of probabilistic programming and you will be able to apply this in your private and professional projects.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Overview

Lecture 2: Bayesian Statistics

Lecture 3: Distributions: Introduction

Lecture 4: Distributions: Uniform Distribution

Lecture 5: Distributions: Normal Distribution

Lecture 6: Distributions: Binomial Distribution

Lecture 7: Distributions: Poisson Distribution

Lecture 8: Monte Carlo Markov Chain

Chapter 2: Samplers

Lecture 1: Metropolis Hastings Sampling 101

Lecture 2: Metropolis Hastings Sampling Interactive 1

Lecture 3: Metropolis Hastings Sampling Interactive 2

Lecture 4: Metropolis Hastings Sampling Interactive 3

Chapter 3: Workspace Preparation

Lecture 1: Julia

Lecture 2: Python

Chapter 4: Gaussian Mixture Models

Lecture 1: GMM 101

Lecture 2: Kmeans 101

Lecture 3: GMM Coding (Julia)

Lecture 4: GMM Coding (Python)

Chapter 5: Bayesian Linear Regression

Lecture 1: Bayesian Linear Regression 101

Lecture 2: Bayesian Linear Regression Coding (Julia)

Lecture 3: Bayesian Linear Regression Coding (Python)

Chapter 6: Bayesian Logistic Regression

Lecture 1: Bayesian Logistic Regression 101

Lecture 2: Bayesian Logistic Regression Coding (Julia)

Lecture 3: Bayesian Logistic Regression Coding (Python)

Chapter 7: Bonus

Lecture 1: Congratulation and Thank you!

Lecture 2: Bonus lecture

Instructors

Bert Gollnick
Data Scientist
Sebastian Kaus
Data Governance Lead

Rating Distribution

1 stars: 6 votes
2 stars: 4 votes
3 stars: 5 votes
4 stars: 7 votes
5 stars: 5 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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