Data, AI, and Cloud Courses

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.

Take your R skills up a notch by learning to write efficient, reusable functions.

Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.

Build the foundation you need to think statistically and to speak the language of your data.

This course focuses on feature engineering and machine learning for time series data.

Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Leverage the OpenAI API to get your AI applications ready for production.

Learn about string manipulation and become a master at using regular expressions.

Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

Master sampling to get more accurate statistics with less data.

Learn to start developing deep learning models with Keras.

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

Discover how Marketing Analysts use data to understand customers and drive business growth.

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Learn to create your own Python packages to make your code easier to use and share with others.