Generative AI Applications

О курсе

Learn how to leverage generative AI to enhance data analysis, reporting, and project workflows through this comprehensive course in the Data Analytics Skill Path. You will develop critical competencies including applying prompt engineering techniques with Large Language Models (LLMs) for data analysis and reporting, using generative AI tools to document analytical code, performing feature engineering on unstructured text data, and generating synthetic datasets for testing and analysis. Through hands-on practice with Google Sheets, ChatGPT, Gemini, Copilot, and Python, you will explore practical applications of AI to uncover insights, automate workflows, and enhance analytical outputs. This course combines expertise from Google, IBM, DeepLearning.AI, and Microsoft, providing multiple perspectives on generative AI applications within data analytics. You will progress from designing prompts to extract insights and visualize data, to understanding AI tools and their industry applications, to mastering advanced prompt engineering techniques, and finally to implementing AI projects and generating synthetic datasets. The curriculum balances theoretical knowledge with practical exercises, preparing you to confidently apply generative AI in professional analytics and data-driven problem-solving contexts. Perfect for aspiring data analysts and AI practitioners seeking practical skills in using generative AI tools to enhance data analysis, reporting, and feature engineering workflows.

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