Data science courses

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

Learn how to implement and schedule data engineering workflows.

Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.

Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.

Learn to retrieve and parse information from the internet using the Python library scrapy.

Learn how to clean and prepare your data for machine learning!

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.

Elevate your data storytelling skills and discover how to tell great stories that drive change with your audience.

Master data modeling in Power BI.

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

Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.

Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.

Learn how to use GitHubs various features, navigate the interface and perform everyday collaborative tasks.

Discover a wide range of DAX calculations and learn how to use them in Microsoft Power BI.

Explore Excel Power Query for advanced data transformation and cleansing to boost your decision-making and analysis.

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

Learn how to work with dates and times in Python.

Learn the role Generative Artificial Intelligence plays today and will play in the future in a business environment.

Learn to combine data across multiple tables to answer more complex questions with dplyr.

Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.

Learn the fundamentals of working with big data with PySpark.

Learn about the power of Databricks Lakehouse and help you scale up your data engineering and machine learning skills.

Enhance your reports with Power BIs Exploratory Data Analysis (EDA). Learn what EDA is for Power BI and how it can help you extract insights from your data.

Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.

Take your Power BI visualizations up a level with the skills you already have. Learn alternative data storytelling techniques to simply building dashboards.

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