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Statistics Fundamentals in Python

4.9+
11 reviews
Updated 03/2026
Confidently learn to calculate statistics and probability, evaluate statistical models, and draw conclusions from hypothesis tests.
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PythonProbability & Statistics20 hr33,329

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Track Description

Statistics Fundamentals in Python

Statistical knowledge is key to evaluating, interpreting, and reporting findings from your data. In this skill track, you'll learn the four fundamentals of statistics using Python, including:✓ Summary statistics and probability ✓ Statistical models such as linear and logistic regression ✓ Techniques for sampling ✓ How to perform hypothesis tests and draw conclusions from a wide variety of data setsBy the end of this track, you'll be ready to apply your statistical skills in Python to analyze data, implement and evaluate statistical models, and draw conclusions from hypothesis test results!

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Statistics in Python

    Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

  • Course

    4

    Sampling in Python

    Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

  • Course

    5

    Hypothesis Testing in Python

    Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

  • Project

    bonus

    Hypothesis Testing with Men's and Women's Soccer Matches

    Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

Statistics Fundamentals in Python
5 Courses
Track
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Don’t just take our word for it

*4.9
from 11 reviews
91%
9%
0%
0%
0%
  • Achraf
    last week

  • Ayu Putri
    4 weeks ago

  • Faqih Zulfikar
    7 months ago

  • Revandi
    7 months ago

  • Ade Muhammad
    7 months ago

  • Rian Oktavianto
    7 months ago

    very helpfull

Achraf

Ayu Putri

Faqih Zulfikar

FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginners as it starts from the foundational concepts of statistics and uses Python, which is known for its readability and ease of use.

What is the programming language of this Track?

The programming language of this track is Python.

Which jobs will benefit from this Track?

This track will benefit those pursuing careers in data analysis, data science, and other related fields where statistical knowledge is essential.

How will this Track prepare me for my career?

By completing this track, you will gain a strong foundation in statistical concepts and learn how to apply them using Python. This will enhance your skills and make you more competitive in the job market.

How long does it take to complete this Track?

This track usually takes 20 hours to complete, but users can spend as much time as they like since it is self-paced.

What's the difference between a skill track and a career track?

A skill track focuses on developing specific skills in a particular field, while a career track provides a more comprehensive learning experience to prepare for a specific career.

What are the courses included in this Track?

The courses included in this track are Introduction to Statistics in Python, Introduction to Regression with statsmodels in Python, Intermediate Regression with statsmodels in Python, Sampling in Python, and Hypothesis Testing in Python.

What is the track type?

The track type is skills, which means it focuses on developing specific skills rather than preparing for a specific career path.

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