Overview

Data Engineering is all about efficient data collection, generation, transformation and storage. Generative AI tools have the capability of making each of data engineering tasks more efficient, effective, and convenient on an ETL pipeline. This specialization is designed not only for Data Engineers but for anyone who might be interested in the use of generative AI in Data Engineering. With three self-paced courses in the specialization, you will begin with learning the differences that distinguish generative AI from discriminative AI. You’ll delve into real-world generative AI use cases and explore popular generative AI models and tools for text, code, image, audio, and video generation. Next, delve into generative AI prompts engineering concepts and real-world business uses. Learn about prompt techniques like zero-shot and few-shot and explore various prompt engineering approaches and explore commonly used prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust. No experience is needed to begin this specialization, although you might find it helpful to have some data engineering knowledge. Take your career to the next level. Let’s get started!

Syllabus

Course 1: Generative AI: Introduction and Applications
Course 2: Generative AI: Prompt Engineering Basics
Course 3: Generative AI: Elevate your Data Engineering Career

Courses

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9 hours 16 minutes
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As generative AI (GenAI) reshapes workplaces and job roles, using it effectively is now essential. Prompt engineering is the key to directing GenAI models and refining their output for desired results. This course is for professionals, executives, students, and AI enthusiasts ready to harness prompt engineering to unlock tools like ChatGPT. You’ll learn practical techniques, structured methods, and best practices for crafting strong prompts. Explore zero-shot and few-shot prompting to boost reliability and output quality. Discover advanced methods such as the Interview Pattern, Chain-of-Thought, and Tree-of-Thought to produce accurate, context-aware responses. Hands-on labs and projects provide experience with multimodal prompting, the playoff method, and image generation. You’ll practice blending text and visuals and evaluating AI outputs for precision and usefulness. Podcasts, dialogues, and discussions link theory to real-world scenarios, while expert insights highlight strategies for effective prompt use. A final project and graded assessments ensure you can apply these techniques with confidence, leaving you with practical, job-ready skills. Hear from practitioners about the techniques and artistry behind writing impactful prompts. Enroll today to master prompt engineering and unlock GenAI’s potential.
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8 hours 6 minutes
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This course is designed for everyone—professionals, executives, students, and enthusiasts—interested in learning about generative AI and leveraging its capabilities in their work and lives. It is your first step toward understanding the power of generative AI, driven by models such as large language models (LLMs). In this course, you will learn the fundamentals and evolution of generative AI, with additional readings and expert insights offering a deeper view of its history and advancements. You will explore its capabilities across text, image, audio, video, virtual worlds, code, and data, with key takeaways and enhanced summaries at the end of each section to reinforce learning. You will understand the applications of generative AI in industries such as IT, finance, healthcare, education, entertainment, and human resources. You will also discover the features of popular tools and models, including GPT, DALL-E, Stable Diffusion, and Synthesia. Hands-on labs provide opportunities to practice using IBM Generative AI Classroom and tools such as ChatGPT. You will also hear from industry practitioners sharing real-world insights. Interactive activities, podcasts, and scenario-based exercises help you apply concepts, while a final practical project consolidates your skills by generating and refining outputs across multiple formats.