[UDM] Data Science and Machine Learning Platforms Course (Jul 2024) + Resources

Develop Real-World AI with H2O.ai.
The Data Science and Machine Learning Platforms Course can help you master the entire data science lifecycle with the set of powerful tools offered by H2O.ai. You will begin by going through the preparation and management of machine learning projects, including project goals, tools, and workflow. Through practical instructions, you will navigate through the process of wrapping up data and visualizing it by means of H2O Flow and H2O Wave, which are user-friendly tools allowing you to get things done quicker and easier.

Automated Machine Learning is Easy
Learn how H2O Driverless AI makes the creation of complex models easier. You will be able to learn even more through interactive exercises on how to start experiments, tune models, and interpret results with inbuilt explainability features. Since this AutoML platform enables you to easily build high-performing models with little or no code, and provides in-depth understandings of how your models make their decisions, it is ideal with the technical community as well as for the data-savvy decision-makers.

From Experiment to Production
The Data Science and Machine Learning Platforms Course does not end after model training is complete, whereby IT gets you ready to be deployed in the real world. You will learn how to deploy, incorporate, and monitor your models with the H2O MLOps tools and Eval Studio. You will also get to know how to configure live endpoints, monitor performance measurement, and how to be compliant and governed. These applied competencies enable you to take projects through development to enterprise solutions.

Enter the Generative AI World
And in the last step of the Data Science and Machine Learning Platforms Course, you will move to the generative AI ecosystem of H2O, such as the H2O LLM studio, H2O GPT, and the GenAI AppStore. Learn about the production and customization of huge language models (LLMs) that can be used in applications such as automated content generation, questions and answers, and RAG (retrieval-augmented generation). You will also learn about the responsible AI practices, such as the evaluation methods and ethical use, so you will have a solid understanding of this new emerging field.