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Udemy

Generative AI & LLMs: Foundations to Hands-on Development

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Overview

Generative AI, Large Language Models(LLMs), Prompt Engineering, Fine-Tune AI Model,GPT models, Hugging Face,Google Colab

What you'll learn:
  • Understand Large Language Models (LLMs): Explore the evolution, architectures, and advancements in LLMs, including Transformers and self-attention mechanisms.
  • Master Prompt Engineering: Learn how to craft effective prompts to optimize AI-generated outputs and improve performance.
  • Fine-Tune AI Models: Develop expertise in fine-tuning LLMs using Python and Hugging Face to tailor models for specific applications.
  • Implement Ethical AI Practices: Gain awareness of the ethical and societal implications of AI, including bias and transparency.
  • Develop AI-Powered Applications: Build a chatbot, a text summarizer, and a fine-tuned model through hands-on projects.
  • Leverage AI Toolkits and Frameworks: Utilize industry-standard tools such as GPT-2, Hugging Face, and Python libraries to create Generative AI solutions.

The rise of Generative AI has transformed the field of artificial intelligence, with Large Language Models (LLMs) leading the way in applications such as chatbots, text generation, and automated summarization. "Generative AI & LLMs: Foundations to Hands-on Development" is a hands-on, comprehensive course designed to equip learners with in-depth knowledge of LLMs, prompt engineering, and model fine-tuning. Through theoretical insights and practical labs, participants will gain expertise in developing AI-powered applications using Python and Hugging Face.

This course covers essential concepts, including the evolution of LLMs, attention mechanisms, ethical considerations, and best practices. It also delves into prompt engineering techniques and fine-tuning methodologies to customize models for specific tasks. With real-world projects and hands-on labs, learners will apply their knowledge by building AI chatbots, text summarizers, and fine-tuned models.

Whether you're a student, developer, researcher, or business professional, this course offers invaluable insights and actionable knowledge that will empower you to harness the transformative potential of LLMs. By the end of this course, you will be well-equipped to develop, optimize, and fine-tune Generative AI applications, making them valuable contributors in the AI-driven world.

Take the first step toward becoming a proficient AI practitioner and join the forefront of innovation in Language AI!

Syllabus

  • Introduction to Large Language Models (LLMs)
  • Understanding Language AI
  • Major Advancements and Technologies
  • The Rise of Attention Mechanisms
  • Categories of LLMs Representation and Generative Models
  • Applications and Ethical Considerations
  • Conclusion and Future Directions
  • Hands-On Project 1 - Develop a Generative AI chatbot in Python
  • Quiz 1
  • Introduction to Mastering Prompt Engineering for Generative AI
  • The Role of Prompts in AI Models
  • Types of Prompts Direct, Indirect, and Contextual
  • Technical Foundations of Prompt Engineering
  • Best Practices and Common Pitfalls in Prompt Engineering
  • Advanced Techniques in Prompt Engineering and Future Trends
  • Hands-On Project 2 - Create a Gen AI Text Summarizer in Python
  • Quiz 2
  • Introduction to Fine-tuning Large Language Models
  • Understanding Language Models
  • The Need for Fine-tuning
  • Data Selection for Fine-tuning
  • Fine-tuning Techniques and Approaches
  • Challenges in Fine-tuning
  • Toolkits and Frameworks for Fine-tuning
  • Future Trends in Fine-tuning Large Language Models
  • Best Practices for Fine-tuning
  • Hands-On Project 3 - Fine-tuning a Generative AI application in Python
  • Quiz 3

Taught by

Dr Mohammad Dabbagh

Reviews

4.5 rating at Udemy based on 400 ratings

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