AI in Data Analytics

AI use cases in the field of data analytics.

In today's data-driven world, AI is transforming how we approach everyday tasks, allowing data professionals to work smarter and faster. In this course we’ll discuss how to integrate generative AI into your workflow to shorten never-ending to-do lists and focus on high-impact insights. Using a five-step prompting framework, you'll learn to elicit high-quality responses from AI assistants like Gemini and apply them to real-world datasets.

The tedious hurdle of data cleaning, which often consumes up to 30% of an analyst's time, is a process ripe for assistance from AI. We’ll discuss how to identify data quality issues, standardize inconsistent date formats, and remove duplicates quickly and efficiently.

We’ll also demonstrate how to use AI as a project consultant for data manipulation. You will learn to prompt AI to build complex spreadsheet formulas, create pivot tables, and brainstorm the precise, actionable questions needed to unlock discoveries in demographics or purchase history data. For analysts working with programming languages, the course covers how to use AI to generate base outlines for R scripts and quickly debug syntax or logical mistakes.

Finally, you will explore the power of storytelling through data visualization. You will learn how to prompt AI to suggest the most effective charts and graphs, ensuring your findings are attention-grabbing and impactful. Throughout the course, you will apply a human-in-the-loop approach, learning to verify AI outputs and manage sensitive information responsibly. By the end of this course, you will be equipped to turn raw data into decisions faster than ever before.