This playlist is your hands-on guide to building intelligent, conversational, and reasoning AI applications with ease. We'll break down complex concepts into simple, bite-sized lessons, covering everything from LLM chaining, memory, retrieval-augmented generation (RAG), and agents to real-world chatbots, document Q&A, and more. You'll discover: ✅ How LangChain works for chaining LLM calls ✅ Building AI-powered chatbots & apps ✅ Retrieval-Augmented Generation (RAG) for smarter AI ✅ Integrating external data & APIs for real-world use cases Playlist Resources: https://learnwith.campusx.in/products#nav_bar Reach us at [support@campusx.in]
Curated by: CampusX (21 videos)
Github: https://github.com/campusx-official/Ollama-Youtube Discount Offer: https://learnwith.campusx.in/courses/GenAI-using-Ollama-68eec843d5d88122b615c7f5 This comprehensive masterclass provides a deep dive into Ollama and the landscape of Open Source LLMs as of 2026. Learn how to download, run, and manage powerful models like Llama, DeepSeek, and Qwen locally on your own computer to ensure data privacy and eliminate subscription costs. Key Topics Covered: Difference between Proprietary and Open Source Models. Hardware Requirements for local execution. Running models via CLI and Python. Building AI Agents with Tool Calling. Specializing models with Model Files. Scaling with Ollama Cloud and the Desktop App. 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚Chapters⌚ 00:00 – Intro 01:02 – Limitations of Proprietary Models 01:37 – Rise of Mature Open-Source LLMs 02:42 – Purpose of This Ollama Masterclass 03:16 – Scope and Depth of the Video 04:57 – What Are LLMs (Foundational View) 06:23 – Proprietary vs Open-Source LLMs 09:54 – What Open-Source Models Really Mean 11:54 – Why Open-Source LLMs Are Hard to Use 15:17 – Why Ollama Exists 18:51 – Benefits of Using Ollama 22:43 – Exploring the Ollama Model Library 28:37 – Hardware and System Requirements 32:22 – Installing and Running Ollama 34:31 – Basic CLI Commands and Model Interaction 44:26 – Advanced CLI: Inspecting and Tuning Models 51:41 – Using Ollama via Python Library 56:38 – Handling Images and Model Parameters in Code 01:04:14 – Managing Conversations and History 01:10:21 – Deep Dive into Tool Calling 01:17:54 – Workflow for Executing Tools 01:26:55 – Practical Tool Calling Demo 01:44:02 – Customising Models with Model Files 01:59:04 – Understanding Ollama’s REST API 02:14:11 – Orchestrating Tasks with LangChain 02:28:14 – Running Large Models on Ollama Cloud 02:43:16 – Using the Ollama Desktop App 02:47:51 – Summary and Full Course Details