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Learn how to set up and use Ollama to build powerful AI applications locally. This hands-on course covers pulling and customizing models, REST APIs, Python integrations, and real-world projects like a Grocery List Organizer, RAG System, and an AI Recruiter Agency. Perfect for developers and AI enthusiasts ready to bring their ideas to life with local LLMs. Don’t miss the exclusive BONUS project at the end!
💻 Code: https://github.com/pdichone/ollama-fundamentals
🔗 Ollama Starter Pack (code templates, cheat sheet, prompt guide, and more): https://bit.ly/ai-starter-pack
Course developed by @vincibits
Keep in touch: https://www.vincibits.com/welcome
⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:02:00) What Is this course about?
⌨️ (0:03:49) Course Prerequisites
⌨️ (0:05:28) Development Environment Setup
⌨️ (0:06:43) Ollama Deep Dive
⌨️ (0:13:08) Ollama Key Features
⌨️ (0:17:09) Ollama Setup
⌨️ (0:18:03) Download Ollama Locally
⌨️ (0:26:18) Ollama Models – How to Pull Different Ollama Models Locally
⌨️ (0:33:41) LLM Parameters Deep Dive
⌨️ (0:39:39) Understanding Model Benchmarks
⌨️ (0:42:56) Ollama Basic CLI Commands – Pull and Testing Models
⌨️ (0:47:09) Pull in the Llava Multimodal MOdel and Captioning an Image – Hands-on
⌨️ (0:52:13) Summarize and Sentiment Analysis and Customizing Models with the Modelfile
⌨️ (1:00:02) Ollama REST API
⌨️ (1:04:39) Ollama REST API – Request JSON
⌨️ (1:07:59) Ollama Models Support Different Tasks – Summary
⌨️ (1:08:40) Different Ways to Interact with Ollama Models – Overview
⌨️ (1:10:42) Ollama Model Running Under Msty App – Frontend Tool – RAG Hands-on
⌨️ (1:21:46) Introduction to Python Library for Building LLM Applications Locally
⌨️ (1:24:14) Interact with Llama3 in Python using Ollama REST API
⌨️ (1:29:29) Ollama Python Library Chatting with our Model
⌨️ (1:35:42) Chat Example with Streaming
⌨️ (1:37:15) Using Ollama Show Function
⌨️ (1:39:15) Create a Custom Model in Code
⌨️ (1:43:05) Build a Real-world Use case Application – Introduction
⌨️ (1:43:29) Build a LLM App – Grocery List Organizer
⌨️ (1:51:46) Building RAG Systems with Ollama – Overview of RAG Systems and Langchain Crash Course
⌨️ (1:59:24) Deep Dive into Vectorstore and Embeddings – the Whole Picture – Crash Course
⌨️ (2:05:33) Overview of Our PDF RAG System We will be Building
⌨️ (2:07:29) Set up our RAG System – Document Ingestion and Vector DB Creation and Embeddings
⌨️ (2:15:56) RAG System – Retrieval and Querying – Final
⌨️ (2:24:27) RAG System – Cleaner Code (Code Refactoring)
⌨️ (2:26:26) RAG System – Streamlit Version
⌨️ (2:28:00) BONUS for YOU!
⌨️ (2:28:33) Introduction to the Next Application – AI Recruiter Agency
⌨️ (2:29:18) Building the AI Recruiter Agency
⌨️ (2:56:13) Outro – Final Thoughts and Your Bonus – Thank you!
🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual
—
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