Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Pre-trained models are used everywhere right now to add AI functionalities to products. But have you wondered how they are trained? This course will teach you from start to finish the process of going from an idea and a dataset to a trained model.

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Learn to streamline your machine learning workflows with tidymodels.

This course covers generative AI with OpenAI’s ChatGPT, emphasizing prompt design and practical uses in marketing, research, and code generation.

Unlock the power of modular RAG architectures. This course will teach you to decompose RAG models into independent modules, implement flexible and reusable designs, and evaluate their performance, scalability, and maintainability for optimal results.

Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.

Enhance your machine-learning models! This course will teach you the tools and techniques to effectively monitor and evaluate model performance during training.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Discover Monte Carlo methods for reinforcement learning and apply them to simple games. Learn how to train agents to make optimal decisions through simulation and feedback-based learning.