Generative AI for Data Science Foundations

As the landscape of data analysis evolves, the ability to leverage generative models is becoming a core requirement for modern data professionals. This course bridges the gap between traditional data science and the latest advancements in artificial intelligence, showing you how to work smarter with automated tools. You will transform your approach to data by learning how to use AI for complex tasks that previously required manual coding and extensive time. What you'll learn: - Understand foundational generative AI concepts and their specific applications in data science. - Apply prompt engineering techniques to automate data cleaning and code generation. - Generate high-quality synthetic data for augmentation and privacy-preserving research. - Explore Retrieval-Augmented Generation (RAG) patterns to query large datasets effectively. - Implement anomaly detection strategies using modern generative modeling techniques. - Navigate data security, privacy, and ethical considerations when using AI tools. The course begins with essential terminology and core definitions before moving into practical applications for data augmentation, feature engineering, and advanced analysis. You will progress through written explanations and code-based examples designed to build your confidence in deploying AI-driven solutions. This course is designed for beginners and aspiring data scientists who want to stay current with industry trends; no prior experience with generative models is required. Start building a future-ready skill set today.