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.
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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.
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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What's inside
One course
Generative AI: Elevate your Data Engineering Career
(0 hours)
Generative AI: Elevate your Data Engineering Career
(0 hours)Learning objectives
- Apply your skills to recognize real-world generative ai uses and identify generative ai models and tools for text, code, image, audio, and video.
- Explain generative ai prompt engineering concepts, examples, and common tools and learn techniques needed to create effective, impactful prompts.
- Implement data engineering processes such as data warehouse schema design, data generation, augmentation and anonymization using generative ai tools
- Evaluate real-world case studies showcasing the successful application of generative ai for etl and data repositories
- Apply your skills to recognize real-world generative ai uses and identify generative ai models and tools for text, code, image, audio, and video.
- Explain generative ai prompt engineering concepts, examples, and common tools and learn techniques needed to create effective, impactful prompts.
- Implement data engineering processes such as data warehouse schema design, data generation, augmentation and anonymization using generative ai tools
- Evaluate real-world case studies showcasing the successful application of generative ai for etl and data repositories
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