Introduction to Generative AI for Data Analysis

Microsoft via Coursera

Coursera based on 41 ratings

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Overview

"Introduction to Generative AI for Data Analysis" is a beginner-friendly course designed to equip learners with foundational knowledge and practical skills in applying generative AI tools to enhance data analysis workflows. This course explores how modern AI models—like large language models (LLMs) and generative algorithms—can assist in tasks such as data cleaning, visualization, trend forecasting, and report generation. Learners will gain a clear understanding of generative AI principles, including prompt engineering and ethical considerations. The course emphasizes real-world use cases, enabling...

Syllabus

Introduction to Generative AI

Develop a foundational understanding of what Generative AI is, its current applications in data analysis, and the key tools and platforms available.

Data exploration with GenAI

Integrate generative AI tools into their existing data analysis workflows to streamline data exploration, uncover insights, and enhance decision-making processes.

Data cleaning with GenAI

Apply generative AI tools to investigate and summarize datasets, and identify patterns and relationships, and formulate hypotheses for further analysis.

Prompt Engineering Fundamentals

Develop the skills to create and optimize effective prompts for diverse data analysis tasks, enhancing the quality and efficiency of data cleaning, analysis, and visualization outcomes.

Ethical and Safe Use of GenAI

Evaluate and apply ethical, legal, and practical considerations in utilizing generative AI for data analysis, ensuring responsible application and risk mitigation.