| 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud - app2.py | 1.2 KB | ||
| 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud - ollama_with_ngrok.ipynb | 102.1 KB | ||
| 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud.mp4 | 207.3 MB | ||
| 1 - Hugging Face Tutorial.mp4 | 138.8 MB | ||
| 1 - LangChain Agents - Guide.docx | 15.2 KB | ||
| 1 - LangChain Agents - Recording 2025-09-17 080254.mp4 | 48.4 MB | ||
| 1 - LangChain Agents - agent.ipynb | 74.3 KB | ||
| 1 - LangChain Agents - requirements.txt | 204.8 B | ||
| 1 - LangChain Agents.mp4 | 70.8 MB | ||
| 1 - Mastering Fine-Tuning Exploring Types & Techniques in the LLM Era - fine-tuning.pptx | 817.5 KB | ||
| 1 - Mastering Fine-Tuning Exploring Types & Techniques in the LLM Era.mp4 | 133.4 MB | ||
| 1 - PyTorch Core Principles and Foundations - Introduction_to_PyTorch.pdf | 789.2 KB | ||
| 1 - PyTorch Core Principles and Foundations.mp4 | 200.1 MB | ||
| 1 - Understanding Embeddings in the world of NLP - embeddings.pptx | 1.2 MB | ||
| 1 - Understanding Embeddings in the world of NLP.mp4 | 159.1 MB | ||
| 1 - What is LlamaIndex & its Use-Cases.mp4 | 125.2 MB | ||
| 1 - What is MCP - MCP.pptx | 954 KB | ||
| 1 - What is MCP.mp4 | 168.4 MB | ||
| 2 - AI Voice Agent Emotion Analysis & Wellness Companion - app.py | 5 KB | ||
| 2 - AI Voice Agent Emotion Analysis & Wellness Companion - requirements.txt | 204.8 B | ||
| 2 - AI Voice Agent Emotion Analysis & Wellness Companion.mp4 | 162.4 MB | ||
| 2 - Exploring the GPT-2 Model and Understanding Custom Datasets with Hugging Face.mp4 | 146.6 MB | ||
| 2 - Fine-Tuning VS RAG - fine-tuning-vs-RAG.pptx | 1 MB | ||
| 2 - Fine-Tuning VS RAG.mp4 | 83.8 MB | ||
| 2 - Running Our First Local LLM using Qwen Model - app.py | 512 B | ||
| 2 - Running Our First Local LLM using Qwen Model - requirements.txt | 0 B | ||
| 2 - Running Our First Local LLM using Qwen Model.mp4 | 89.7 MB | ||
| 2 - Understanding FASTMCP A Python Framework for Building and Developing MCP.mp4 | 100.5 MB | ||
| 3 - Building a FastMCP setup integrated with a local database and an Ollama Agent - server.py | 2.4 KB | ||
| 3 - Building a FastMCP setup integrated with a local database and an Ollama Agent.mp4 | 343.1 MB | ||
| 3 - Building a RAG-powered Assistant with LLaMA 3.1 using Pinecone - llama-rag.ipynb | 6.9 KB | ||
| 3 - Building a RAG-powered Assistant with LLaMA 3.1 using Pinecone.mp4 | 312.2 MB | ||
| 3 - Deep Understanding of Language Models - Language Models.pptx | 1.8 MB | ||
| 3 - Deep Understanding of Language Models.mp4 | 105.2 MB | ||
| 3 - Hands-On Fine-Tuning From Theory to Practice - fine-tuning.ipynb | 48.1 KB | ||
| 3 - Hands-On Fine-Tuning From Theory to Practice.mp4 | 448 MB | ||
| 3 - Virtual AI Based Talking Agents.mp4 | 80.4 MB | ||
| 4 - AI Copilot Agent - agent.ipynb | 3.7 KB | ||
| 4 - AI Copilot Agent - app.py | 716.8 B | ||
| 4 - AI Copilot Agent.mp4 | 133.3 MB | ||
| 4 - Deepseek Coder Assistant - app.py | 6 KB | ||
| 4 - Deepseek Coder Assistant - requirements.txt | 0 B | ||
| 4 - Deepseek Coder Assistant.mp4 | 124.4 MB | ||
| 4 - Inside Transformer Architecture How It Works - Transformer Model.pptx | 3 MB | ||
| 4 - Inside Transformer Architecture How It Works.mp4 | 229.4 MB | ||
| 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - app.py | 1.9 KB | ||
| 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - main.py | 1.2 KB | ||
| 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - whisper.py | 1.6 KB | ||
| 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS.mp4 | 134.2 MB | ||
| 6 - AI Fitness & Diet Planner Agent - app.py | 2.1 KB | ||
| 6 - AI Fitness & Diet Planner Agent.mp4 | 106.9 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 53 total files | |||
Master AI Agent Development: LangChain, OpenAI, Ollama, MCP
https://WebToolTip.com
Published 10/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 6m | Size: 3.77 GB
Learn to build, deploy, and fine-tune intelligent AI Agents using LangChain, OpenAI, GPT-2, Ollama, MCP Anthropic Agents
What you'll learn
Build AI agents step by step using LangChain
Understand hands on practice of fine-tuning large language models
Integrate external tools and APIs to enhance agent capabilities
Develop real-world AI workflows and deploy agents in under 30 minutes
Deploy Agents using Cloud Frameworks and utilize MCP Local Servers
Requirements
Basic knowledge of Python will be helpful
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