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Unclaimed ProfileGenerative AI & LLMs: Foundations to Hands-on Development is a comprehensive, practical guide designed for developers, data scientists, and tech enthusiasts eager to master the mechanics of modern artificial intelligence. Led by Dr. Mohammad Dabbagh, this program bridges the gap between theoretical machine learning concepts and real-world application. Students begin by exploring the foundational architectures of Large Language Models, including transformers and self-attention mechanisms, before transitioning into actionable skills. The curriculum covers essential techniques such as advanced prompt engineering to maximize model performance, as well as hands-on fine-tuning using Hugging Face, Python, and Google Colab. By working through tangible projects, including building custom chatbots and automated text summarizers, learners gain the confidence to implement tailored AI solutions. Additionally, the course addresses crucial considerations around ethical AI, bias mitigation, and transparency. Whether you are a software engineer looking to integrate intelligence into your applications or a researcher aiming to harness GPT-style models, this course provides the structural framework and practical tools needed to excel in the rapidly evolving landscape of generative technologies.
About the creator
Dr Mohammad Dabbagh
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Dr. Mohammad Dabbagh is an experienced educator and researcher specializing in software engineering, artificial intelligence, and advanced machine learning technologies. With a strong academic foundation and years of practical industry engagement, Dr. Dabbagh bridges the gap between complex theoretical concepts and real-world implementation. His course, "Generative AI & LLMs: Foundations to Hands-on Development," reflects his core philosophy that true mastery of artificial intelligence comes from building and experimenting. Dr. Dabbagh structures his curriculum to guide learners through the essential mathematics and architectural designs of Large Language Models (LLMs) before transitioning into practical, hands-on programming sessions. He believes in demystifying the…Show more
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Program Overview
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Price may change · updated within 1–2 weeks
Course language
Learning format
Subcategory
Price
Price may change · updated within 1–2 weeks
Course language
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.
Best For
- Software developers looking to integrate LLM capabilities into existing applications
- Data scientists aiming to transition from classical machine learning to generative architectures
- Tech professionals who want to understand the mechanics behind transformers and fine-tuning
- Practitioners who prefer a project-based approach to learning AI implementation
Not For
- Absolute beginners with no prior experience in Python programming
- Researchers seeking highly theoretical, mathematical deep dives into neural network proofs
- Professionals looking for a no-code or drag-and-drop AI tool demonstration
- Individuals seeking entry-level, non-technical introductions to AI concepts
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