About this Course

5,781 recent views
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level

S​ome experience with Data Science using the PyData Stack of NumPy, SciPy, Pandas, Scikit-learn.

Knowledge of Jupyter Notebooks will be beneficial.

Approx. 13 hours to complete
English

What you will learn

  • The basics of Probability, Bayesian statistics, modeling and inference.

  • You will also get a hands-on introduction to using Python for computational statistics using Scikit-learn, SciPy and Numpy.

Skills you will gain

  • Bayesian Inference
  • visualization
  • Python Programming
  • Scipy
  • Statistics
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level

S​ome experience with Data Science using the PyData Stack of NumPy, SciPy, Pandas, Scikit-learn.

Knowledge of Jupyter Notebooks will be beneficial.

Approx. 13 hours to complete
English

Offered by

Placeholder

Databricks

Syllabus - What you will learn from this course

Week
1

Week 1

21 minutes to complete

Environment Setup

21 minutes to complete
4 videos (Total 11 min), 1 reading
Week
2

Week 2

6 hours to complete

Introduction to the Fundamentals of Probability

6 hours to complete
17 videos (Total 119 min), 7 readings, 12 quizzes
Week
3

Week 3

4 hours to complete

A Hands-On Introduction to Common Distributions

4 hours to complete
12 videos (Total 49 min), 2 readings, 2 quizzes
Week
4

Week 4

3 hours to complete

Sampling Algorithms

3 hours to complete
6 videos (Total 32 min), 2 readings, 3 quizzes

Reviews

TOP REVIEWS FROM INTRODUCTION TO BAYESIAN STATISTICS

View all reviews

About the Introduction to Computational Statistics for Data Scientists Specialization

Introduction to Computational Statistics for Data Scientists

Frequently Asked Questions

More questions? Visit the Learner Help Center.