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.
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Applied Learning Project
This Specialization emphasizes applied learning and includes a series of hands-on activities and projects. In these exercises, you’ll take the theory and skills you’ve gained and practice them with real-world scenarios.
You will perform hands-on labs to:
Generate text, images, and code using Generative AI
Apply prompt engineering techniques and best practices
Use generative AI tools to design data workflow
