Learning Paths

Explore all of our learning paths across data science, analytics, and machine learning interview questions.

These courses are created by experts at top technology companies across many different industries.

Filters

lessonIcon

91 of 257 Completed

Data Science

Jay

Jay

Published March 10, 2023

30 Courses

Pandas
SQL
Database Design

Data science helps businesses make smarter decisions by combining programming, statistics, modeling, and machine learning skills. Learn how to ace data science job interviews with a well-structured approach.

lessonIcon

28 of 84 Completed

Data Analytics

Jay

Jay

Published October 18, 2022

8 Courses

Product Metrics
Business Case
Analytics
Marketing Analytics
A/B Testing

Data Analytics is the applied use of data to drive desision making. This learning path will help you understand and analyze data to develop insights, make better decisions and ultimately improve the company you work for!

lessonIcon

23 of 73 Completed

Data Engineering

Jay

Jay

Published November 15, 2022

8 Courses

Pandas
SQL
Database Design

Data engineers develop the tools and frameworks needed for data teams to function: they build pipelines, manage ETL, and build scalable data infrastructures. Learn the skills evaluated in data engineering job interviews.

lessonIcon

12 of 46 Completed

Product Metrics

Jay

Jay

Published August 5, 2020

6 Courses

Product Metrics
Business Case
Analytics
Marketing Analytics
A/B Testing

Learn how to use product analytics to solve problems and empower business decisions.

lessonIcon

18 of 63 Completed

Modeling & Machine Learning

Jay

Jay

Published August 20, 2020

11 Courses

ML System Design
Machine Learning
Deep Learning

Understanding of how to build, deploy, and test machine learning models and tackle business problems while applying modeling concepts.

lessonIcon

24 of 56 Completed

SQL

Jay

Jay

Published August 18, 2020

6 Courses

Pandas
SQL
Database Design

SQL tests your analytical sense, ability to pull data for building models, and interpretation of datasets and metrics.

lessonIcon

38 of 77 Completed

Statistics & AB Testing

Jay

Jay

Published August 20, 2020

9 Courses

Statistics
Probability

Statistics and A/B testing are the underlying parts of the data science knowledge base. Knowing how to run an A/B or multivariate test is table stakes.

lessonIcon

19 of 49 Completed

Probability

Jay

Jay

Published May 17, 2021

6 Courses

Statistics
Probability

Probability theory underlies much of what we do as data scientists. Learn the basics and then move on to intermediate applications.

lessonIcon

14 of 30 Completed

Python

Jay

Jay

Published July 19, 2021

4 Courses

Python
R
Algorithms

Other than SQL, Python is the most common language used in data science, due to its easy-to-read syntax and its robust collection of packages created specifically for data scientists.