Data Science and Generative AI for Modern Analysts

The field of data science is evolving rapidly with the rise of generative models. Understanding how to combine traditional analytical methods with modern AI is now a core requirement for any aspiring professional. This course provides a clear path through the essential concepts needed to navigate this new landscape. You will transition from learning basic data manipulation to understanding how intelligent systems are built and deployed. By reading through detailed explanations and practicing with code-based examples, you will develop the skills to process information, build predictive models, and leverage generative AI to enhance your analytical workflows. What you'll learn: - Understand foundational data science concepts, statistical methods, and essential terminology - Apply modern Python libraries to clean, manipulate, and analyze diverse datasets - Build and evaluate machine learning models for classification and regression tasks - Explore natural language processing techniques to interpret and process text data - Implement generative AI patterns like prompt engineering and retrieval-augmented generation (RAG) - Practice using modern dataframe tools and vector databases for efficient data retrieval The curriculum begins with core definitions and mathematical foundations before progressing through structured data analysis, deep learning basics, and modern AI application patterns. You will follow a logical progression that builds your confidence in handling both structured data and unstructured text. This course is designed for beginners with no prior experience in data science or programming. All concepts are explained starting from the absolute basics. Start your journey into the world of data-driven intelligence today.