English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 23 lectures (1h 43m) | 919 MB
Master Local AI Development: Deploy LLMs, Build Applications & Create AI Tools Using DeepSeek R1, Ollama & Python
Ready to harness the power of local AI development with DeepSeek R1 and Ollama?
In this comprehensive masterclass, you’ll learn how to build sophisticated AI applications locally using DeepSeek R1, one of the most powerful open-source language models available today.
Whether you’re a developer looking to integrate AI into your applications or an AI enthusiast wanting to build custom solutions, this course provides everything you need to succeed.
Why This Course?
- Learn to run AI models locally for complete privacy and control
- Save costs by avoiding expensive API calls and cloud services
- Build production-ready applications with open-source technologies
- Master the latest tools in AI development
- Hands-on projects and real-world applications
Course Highlights:
- Complete setup guide for DeepSeek R1 with Ollama
- Working with different model variants (1.5B, 7B models)
- Performance optimization techniques
- Building practical AI applications
What Makes This Course Different?
This isn’t just another AI course – it’s a comprehensive guide to building real-world AI applications using open-source tools. You’ll learn not just the theory, but the practical implementation details that make a difference.
Who is this course for?
- Software developers wanting to integrate AI into their applications
- AI enthusiasts interested in local LLM deployment
- Tech professionals looking to build custom AI solutions locally
- Anyone interested in open-source AI development
Prerequisites:
- Basic Python programming knowledge
- Familiarity with command-line operations
- Computer with minimum 16GB RAM (see course for full requirements)
- No prior AI experience required
- What You’ll Build: Throughout this course, you’ll create several practical applications, including:
- Local AI development environment
- Custom chat applications
- Code assistance tools
- AI-powered productivity applications
Don’t miss this opportunity to master local AI development with DeepSeek R1 and Ollama.
With lifetime access to course updates, you’ll stay current with the latest developments in AI technology.
What you’ll learn
- Deploy DeepSeek R1 locally using Ollama to build AI applications with complete privacy, control, and cost efficiency.
- Master model variants (1.5B, 7B, full) and select optimal configurations based on hardware and use case needs.
- Build apps from scratch: chat interfaces, code assistants, and productivity tools using Python.
- Optimize AI application performance through resource management and scaling strategies for production use.
Table of Contents
Introduction
1 Introduction & What the Course is About
2 WATCH THIS — What You’ll Build in this Course
3 Course Prerequisites
4 Course Structure and Development Environment Setup
Download Code and Resources
5 Source code
DeepSeek R1 Fundamentals
6 DeepSeek R1 Deep Dive – Capabilities and What it Is
7 DeepSeek Foundation Core Architecture
8 DeepSeek Model Variations
9 Open vs. Closed Source LLMs – Overview
10 DeepSeek Foundations – Summary
DeepSeek R1 and Ollama – Deep Dive
11 Introduction to DeepSeek R1 and Hardware Requirements
12 DeepSeek Chatbox – Hands-on
13 Installing LM Studio and Installing DeepSeek R1 Distilled Model
14 Installing Ollama and Downloading R1 Distilled Model & Chatting with It
DeepSeek R1 Local Development
15 Development and Integration Locally – Overview
16 Using Ollama Local API Endpoint to Run DeepSeek R1 Model in Code – Hands-on
Hands-on – Building AI Applications with R1 – Building Use-cases
17 Document Analyzer – Introduction Demo
18 Hands-on Document Analyzer Code Walkthrough
19 Code Assistant – Demo Overview
20 Code Assistant Code Walkthrough
21 AI Multi-Assistant Demo
22 AI Multi-Assistant Code Walkthrough
Final Thoughts and Wrap up
23 Final Thoughts and Next Steps
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