Prompt Engineering for Data Science and Analytics

Data professionals spend hours writing repetitive code, debugging scripts, and formatting reports. Learning how to leverage AI with structured prompt engineering can cut this manual effort in half and supercharge your analytical output. This course guides you through the fundamental principles of crafting targeted, reliable prompts specifically for data tasks. You will learn to guide AI models to produce accurate code, perform statistical analysis, and generate executive summaries with minimal errors. What you will learn: Understand the core concepts of prompt engineering, including system prompts, context windows, and temperature settings; Generate optimized SQL queries and database schemas through structured natural language instructions; Write and debug Python data science scripts, including data cleaning and visualization code; Apply AI prompting to Spark workflows and big data processing tasks; Design prompts that produce structured data outputs like JSON and markdown reports; Mitigate common AI limitations such as code hallucinations and biased logical reasoning. You will begin by exploring foundational AI terminology and prompt structures before moving into practical written exercises designed to build your skills step-by-step. The material covers real-world scenarios in data manipulation, statistics, and reporting. This course is designed for aspiring data analysts, junior data scientists, and database professionals looking to integrate AI into their workflow. No prior experience with prompt engineering is required, though a basic understanding of data concepts is helpful. Start reading today to transform how you analyze data and write code using the power of AI.