Generative AI for Data Analysts Specialization Course Syllabus

Overview: This specialization is designed for data professionals seeking to integrate generative AI into their data analytics workflows. Comprising three core courses and a final project, the program offers a practical, hands-on approach to mastering key AI tools and techniques. With approximately 28 hours of total content, learners can complete the program at their own pace, gaining valuable skills in prompt engineering, data augmentation, and AI-enhanced analysis using tools like GPT, DALL·E, IBM Watsonx, Prompt Lab, Spellbook, and Dust.

Module 1: Generative AI: Introduction and Applications

Estimated time: 7 hours

• Understand the fundamentals of generative AI
• Explore capabilities and limitations of generative models
• Identify real-world use cases across industries
• Learn about ethical considerations in AI deployment

Module 2: Generative AI: Prompt Engineering Basics

Estimated time: 7 hours

• Introduction to prompt engineering concepts
• Master zero-shot and few-shot prompting techniques
• Use tools like Prompt Lab and Spellbook for effective prompting
• Evaluate and refine prompts for better AI outputs

Module 3: Generative AI Models and Tools

Estimated time: 5 hours

• Identify popular generative AI models including GPT and DALL·E
• Explore IBM Watsonx for enterprise AI applications
• Compare capabilities of different AI tools
• Integrate AI platforms into analytical workflows

Module 4: Enhancing Data Analytics with Generative AI

Estimated time: 9 hours

• Apply generative AI to data preparation and cleaning
• Generate synthetic data for analysis and testing
• Augment datasets using AI-driven techniques
• Query databases using natural language and AI

Module 5: Real-World Applications in Data Analytics

Estimated time: 6 hours

• Analyze case studies of AI in business intelligence
• Enhance data visualization with AI-generated insights
• Improve storytelling through AI-assisted narrative generation
• Address challenges in deploying AI at scale

Module 6: Final Project

Estimated time: 14 hours

• Design an AI-enhanced data analytics workflow
• Apply prompt engineering and AI tools to real datasets
• Present findings using AI-generated visualizations and narratives

Prerequisites

• Familiarity with basic data analysis concepts
• No prior AI experience required
• Access to a web browser and Coursera platform

What You'll Be Able to Do After

• Explain the core principles of generative AI in data analysis
• Apply prompt engineering techniques to improve AI interactions
• Utilize tools like GPT, DALL·E, and IBM Watsonx effectively
• Enhance data analytics workflows using AI for generation, querying, and augmentation
• Prepare for roles such as Data Analyst, Business Intelligence Analyst, or AI Specialist