Generative AI for Data Science: Practical Applications

Generative AI is transforming the field of data science, enabling professionals to analyze data, generate code, and build intelligent applications faster than ever before. This text-based course helps you bridge the gap between traditional data science workflows and cutting-edge generative AI technologies. You will transition from manual coding and analysis to leveraging AI assistants and Large Language Models safely and efficiently. Through clear explanations and practical written exercises, you will gain a solid understanding of how generative models work, how to write precise prompts for data-related tasks, and how to evaluate and deploy these systems responsibly. What you'll learn: Understand the core concepts of generative AI, transformer architectures, and how models process data. Apply advanced prompt engineering techniques to clean, transform, and analyze complex datasets. Integrate modern retrieval-augmented generation patterns into your data workflows. Evaluate generative AI outputs for bias, hallucinations, and accuracy in data analysis. Practice writing and debugging Python code using AI-assisted coding tools. Configure responsible AI frameworks to ensure data privacy, security, and ethical compliance. The course begins with foundational concepts and key terminology of generative models before guiding you through written tutorials on prompt design, data manipulation, and responsible AI workflows. Designed for aspiring data scientists, analysts, and developers looking to add generative AI to their toolkit, this course requires no advanced AI background. Start reading today to master the intersection of generative AI and data science.