Associate Data Scientist

Learn to combine data from multiple tables by joining data together using pandas.

4 hours

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

4 hours

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hours

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hours

Explore a dataset containing a century's worth of Nobel Laureates. Who won? Who got snubbed?

2 hours

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

3 hours

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hours

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

4 hours

Find out when and where crime is most likely to occur, along with the types of crimes commonly committed in LA.

2 hours

Learn how to manipulate and visualize categorical data using pandas and seaborn.

4 hours

Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!

2 hours

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

3 hours

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

3 hours

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hours

Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.

2 hours

Learn how to work with dates and times in Python.

4 hours

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hours

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

4 hours

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

2 hours

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

4 hours

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

4 hours

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

2 hours

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hours

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

2 hours

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering

2 hours

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hours

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

2 hours