Learn the Fundamentals of Generative AI for Real-World Applications by DeepLearning AI and AWS [Paid]: Register Now!

Registrations are open for the exclusive course – Fundamentals of Generative AI for Real-World Applications by DeepLearning AI in collaboration with AWS. Check the details below!

About DeepLearning AI

DeepLearning AI is an education technology company empowering the global workforce to build an AI-powered future through world-class education, hands-on training, and a collaborative community. DeepLearning AI has created high-quality AI programs on Coursera that have gained an extensive global following. DeepLearning AI has become the pathway for anyone looking to build an AI career by providing a platform for education and fostering a tight-knit community.

About AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud, offering over 200 fully featured services from data centres globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

What You’ll Get from Generative AI with LLMs?

• Gain foundational knowledge, practical skills, and a functional understanding of how generative AI works.
• Dive into the latest research on Gen AI to understand how companies are creating value with cutting-edge technology.
• Instruction from expert AWS AI practitioners who actively build and deploy AI in business use cases today.

Course Objectives & Outcomes

• Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection to performance evaluation and deployment.
• Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases.
• Use empirical scaling laws to optimize the model’s objective function across dataset size, compute budget, and inference requirements.
• Apply state-of-the-art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project.
• Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners.
• Receive a Coursera certificate demonstrating your skills upon completion of the course.

Who Should Join?

• For data scientists: Gain deeper knowledge into the underlying structure and mechanisms of generative AI and explore avenues for further innovations in this field.
• For machine learning engineers: Learn how to better train, optimize and fine-tune generative models while learning about different use cases and applications.
• For prompt engineers: Explore advanced prompting techniques and learn how to control your output using generative configuration parameters.
• For research engineers: Explore the state of art generative models and architectures in depth to build on top of your own advanced techniques in generative AI.
• For anyone interested in generative AI: Get an extensive introduction to developing with generative AI and its fundamentals.

Instructors

• Antje Barth, Principal Developer Advocate, Generative AI, Amazon Web Services (AWS)
• Chris Fregly, Principal Solutions Architect, Generative AI, Amazon Web Services (AWS)
• Shelbee Eigenbrode, Principal Solutions Architect, Generative AI, Amazon Web Services (AWS)
• Mike Chambers, Developer Advocate, Generative AI, Amazon Web Services (AWS)

How to Join?

Interested candidates can directly join through this link.

Required Skill Sets

• This is an intermediate course, so you should have some experience coding in Python to get the most out of it.
• You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets.
• If you have taken the Machine Learning Specialization or Deep Learning Specialization, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI.

FAQs

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