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Home » Ebooks & Tutorials » Technical » Internet & Networking » Coursera – Generative AI for Data Scientists – Specialization (by IBM)

Coursera – Generative AI for Data Scientists – Specialization (by IBM)

08/03/2024 Learning for Life Leave a Comment

Coursera – Generative AI for Data Scientists – Specialization (by IBM)
English | Tutorial | Size: 337.97 MB


Leap ahead in data science using generative AI . Build in-demand hands-on generative AI skills to supercharge your data science career in under 1 month!!!

What you’ll Learn:
• Apply skills to recognize real-world generative AI uses and identify popular generative AI models and tools for text, code, image, audio, and video
• Understand generative AI prompt engineering concepts, examples, and common tools and learn techniques to create effective, impactful prompts
• Learn how to identify appropriate generative AI tools for data science use cases
• Apply generative AI prompt techniques to generate and augment datasets and to develop and refine machine learning models

Skills you’ll Gain:
• Artificial Intelligence (AI)
• Data Science
• Machine Learning
• Prompt Engineering
• Generative AI

Specialization – 3 Course Series:
Generative AI knowledge is now an essential data science skill. According to Gartner, “By 2026, 20% of top data science teams will have rebranded as Cognitive Science or Science consultancies, increasing diversity in staff skills by 800%.”

With the industry trends in mind, IBM brings you this specialization to help boost your career! This three-course specialization is designed to help you kickstart your journey into applying generative AI in the field of data science. This includes existing and aspiring data professionals, such as data scientists, data analysts, data architects, and engineers, and even data enthusiasts.

You will begin the specialization by understanding the basics of generative AI and its real-world applications. Then, learn about generative AI prompts engineering concepts and approaches, and explore commonly used prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust. Finally, delve into applying generative AI tools and techniques throughout the data science methodology for data augmentation, data generation, feature engineering, model development, model refinement, visualizations, and insights. Give your data science techniques a boost with generative AI!

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RAPIDGATOR:
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TURBOBIT:
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Internet & Networking AI, Coursera, Data, Generative, IBM, Scientists, Specialization.

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