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The Generative AI Edge: LLMs and Agentic Systems
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A Comprehensive Guide to Generative AI and LLMs:
Are you ready to move from curiosity to creation in the world of artificial intelligence? This comprehensive 8-week program is your blueprint for a career in modern AI development. Led by seasoned industry expert Ed Donner, this course is designed for those who want to do more than just understand AI—they want to build and innovate with it.
What You'll Learn:
This course and curriculum is meticulously crafted to transform your skills through practical application. During this course you'll :
Architect Cutting-Edge Solutions: Learn to design and construct advanced Generative AI products using state-of-the-art models and proven frameworks.
Explore the AI Landscape: Gain hands-on experience with over 20 different groundbreaking AI models, from powerful Frontier models to the most promising Open-Source solutions.
Master Essential Tooling: Develop a high level of proficiency with industry-standard platforms like HuggingFace, LangChain, and Gradio.
Deploy Advanced Techniques: Implement critical methods such as Retrieval-Augmented Generation (RAG), QLoRA fine-tuning, and the development of intelligent AI Agents.
Create Impactful AI Applications: Build a portfolio of powerful, real-world projects that showcase your skills, including a multi-modal customer support system, a corporate knowledge worker, and a code optimization tool that achieves a 60,000x performance boost.
Transition to Training: Move from simply using models to fine-tuning and training your own specialized models to outperform commercial alternatives on specific tasks.
Course Highlights:
Built on Doing: This is a project-based course. You'll solidify your understanding by building complex, real-world applications that deliver tangible results.
Stay Ahead of the Curve: The curriculum is focused on the latest frameworks and techniques to ensure your skills are current and in high demand.
Designed for Accessibility: No advanced math, calculus, or linear algebra is required. The content is practical and accessible, with step-by-step guidance and resources to support your learning journey.
The Program in Action: A Modular Overview
Module 1: Foundational Concepts: Dive into the core of Transformers and build your first AI business product by scraping and navigating company websites.
Module 2: The Power of APIs: Discover how to leverage Frontier APIs to develop a sophisticated customer service agent that understands text, audio, and images.
Module 3: Open-Source Models: Enter the world of Open-Source AI with HuggingFace, building a tool to generate meeting minutes from recordings.
Module 4: Code & LLM Selection: Understand how to choose the right LLM and create an AI tool that translates and optimizes code for massive performance gains.
Module 5: The RAG Revolution: Master Retrieval-Augmented Generation to build a powerful AI knowledge worker capable of answering company-specific questions.
Module 6-7: The Transition to Training: Learn to fine-tune both Frontier and Open-Source models, culminating in a project where you build a specialized model that surpasses commercial alternatives.
Module 8: Deployment & Agents: Learn to deploy your final project to a production environment with a polished UI and enhance its capabilities using advanced Agents.
Note – For comprehensive curriculum details and project information, please visit the Curriculum section.
This course is ideal For:
Developers and Data Scientists: Eager to enhance their skillset and build cutting-edge AI applications.
Career Changers: Individuals seeking a comprehensive pathway into the high-growth field of Generative AI.
Tech Professionals: Anyone looking to stay competitive by mastering the latest LLM frameworks and techniques.
Requirements
Familiarity with Python. However this course will not cover Python basics and is completed in Python.
A PC with an internet connection is required. Either Mac (Linux) or Windows.
We recommend that you allocate around $5 for API costs to work with frontier models. However, you can complete the course using open-source models if you prefer.
- Introduction to Generative AI – Understanding LLMs, transformers, and modern AI ecosystems.
- Anatomy of Transformer Models – Attention, embeddings, tokens (without heavy math).
- Setting Up Your AI Environment – Python, Hugging Face, LangChain, Gradio, and GPU options.
- Building Your First Mini AI App – A simple text summarizer/chatbot using a pre-trained model.
- Web Scraping for AI – Collecting and processing company website data for AI use.
- Project – Build a lightweight AI business intelligence tool using scraped data.
- API-based AI vs Open-Source AI – Pros, cons, and when to use each.
- Working with Frontier APIs – Calling models via OpenAI, Anthropic, or Cohere APIs.
- Building a Multi-Modal Customer Support Agent – Text, voice, and image inputs.
- Voice + Speech AI – Using Whisper and TTS for natural voice interaction.
- Image Understanding Models – Captioning, OCR, and multimodal Q&A.
- Project – Deploy a Multimodal Customer Service Bot.
- Introduction to Open-Source AI Models – Hugging Face model zoo tour.
- Working with Transformers Library – Loading, fine-tuning, and inference with open models.
- Building a Meeting Transcription & Summarization Tool (audio → text → summary).
- Evaluating LLMs – Benchmarks, prompt engineering, and task alignment.
- Lightweight UIs with Gradio for Open-Source Apps.
- Project – Meeting Minutes Generator with an easy-to-use interface.
- Choosing the Right Model – Criteria and decision-making for LLM selection
- Retrieval-Augmented Generation (RAG) – Concepts, architecture, and use cases
- Implementing RAG Pipelines with LangChain & Vector Databases (FAISS, Pinecone, etc.)
- Building a Knowledge Worker – Company-specific Q&A using internal documents
- Code Optimization with LLMs – Translating & optimizing code with large models
- Project – AI Corporate Knowledge Worker + Code Performance Booster
- Introduction to Fine-Tuning – Types (LoRA, QLoRA, instruction tuning).
- Hands-on Fine-Tuning of an Open-Source LLM for a Custom Use Case.
- Frontier Model Customization – Working with fine-tuning APIs for specialized tasks.
- Building Intelligent AI Agents – Chaining reasoning, task execution, and decision-making.
- Deploying & Scaling AI Apps – Hosting APIs, using Docker, Streamlit/Gradio UIs.
- Final Project – Deploy a Fine-tuned AI Agent with a Polished UI in Production.
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Anushri Mishra
I am an enthusiastic educator with one year of experience teaching Artificial Intelligence and Robotics. I specialize in simplifying complex technical concepts, making them engaging and accessible for learners of all backgrounds. My classes blend theory with hands-on projects, helping students understand how AI and robotics shape the world around us. Passionate about fostering curiosity and innovation, I am committed to inspiring the next generation of creators and problem-solvers through practical learning and interactive teaching methods. -
Satendra Patel
I am an enthusiastic educator with one year of experience teaching Artificial Intelligence and Robotics. I specialize in simplifying complex technical concepts, making them engaging and accessible for learners of all backgrounds. My classes blend theory with hands-on projects, helping students understand how AI and robotics shape the world around us. Passionate about fostering curiosity and innovation, I am committed to inspiring the next generation of creators and problem-solvers through practical learning and interactive teaching methods. -
Amar Deep Rao
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