Data, AI, and Cloud Courses

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

Learn how to implement and schedule data engineering workflows.

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

Learn the fundamentals of working with big data with PySpark.

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.

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

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.

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

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

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Master Git’s advanced features to streamline data science and engineering workflows, from complex merging to large-scale project optimization.

Take your dbt skills to the next level with this hands-on course designed for data engineers and analytics professionals.

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.

Learn how to clean data with Apache Spark in Python.

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Prepare for your next coding interviews in Python.

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

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 about ARIMA models in Python and become an expert in time series analysis.

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.

Learn how to approach and win competitions on Kaggle.