Generative AI for Data Science Teams

As data science evolves, integrating generative AI into your team's workflow is no longer optional—it is a core competitive advantage. This course helps data teams move from basic terminology to the practical integration of large language models. You will understand how to leverage generative AI to streamline data pipelines, enhance analysis, and collaborate effectively. Through clear written explanations and structured text-based exercises, you will gain the confidence to implement AI-driven solutions within your existing data infrastructure. What you will learn: Understand foundational generative AI concepts and key terminology relevant to data teams; Apply prompt engineering techniques to optimize code generation and data analysis tasks; Explore retrieval-augmented generation (RAG) patterns and the role of vector databases; Integrate large language models into existing data pipelines and workflows safely; Establish collaborative workflows and best practices for responsible AI usage in data science. The course starts with essential definitions and foundational AI concepts before moving into practical pipeline integration and team workflow strategies. You will progress from core theory to real-world application through comprehensive reading materials and written scenarios. This course is designed for beginner data scientists, analysts, and team leads looking to adopt generative AI tools, with no prior experience with machine learning or generative models required. Start reading today to modernize your team's data science workflows with generative AI.