Full-Stack AI with Ollama: Llama, Deepseek, Mistral, QwQ

Overview

Build AI Apps with Open-Source Models:

NLP, Chatbots, Code Generation, Summarization, Automation & More(AI) What you'll learn:

Understand AI Model Deployment – Learn how to install, set up, and run AI models locally using Ollama.Build AI-Powered Applications:

Develop real-world AI applications using top models from Ollama, including LLaMA 3, Mistral, CodeLlama, Mixtral, and DeepSeek-R1.Implement NLP Tasks – Work with AI models to summarize text, generate content, proofread documents, and extract key information from legal and business texts.Develop AI-Powered Assistants – Build AI chatbots, customer support bots, and personal AI assistants using advanced LLMs.Generate & Debug Code with AI – Utilize CodeLlama to auto-generate code, debug programming errors, and improve software development efficiency.Integrate AI with Web Apps – Learn how to create full-stack applications with a FastAPI backend and interactive web UI, using AI models for real-time processingAutomate Business & Productivity Tasks – Implement AI solutions for automated email replies, AI-powered meeting summarization, and resume generation.Work with Real-World Data & APIs – Fetch live data from news APIs, finance APIs, and customer reviews, and analyze them using AI models for insights.Optimize AI Model Performance – Learn techniques for fine-tuning AI prompts, handling API responses, and improving response accuracy. Full-Stack AI with Ollama:

Llama, DeepSeek, Mistral, QwQ, Phi-2, MedLlama2, Granite3.2 is the ultimate hands-on AI development course that teaches you how to build and deploy real-world AI applications using the latest open-source AI models.

Whether you're a beginner exploring artificial intelligence or an experienced developer, this course will provide you with practical projects to integrate large language models (LLMs) into web applications, automation tools, and advanced AI-driven solutions.Throughout this course, you will learn how to install, configure, and use Ollama to run powerful AI models locally without relying on expensive cloud-based APIs. You’ll work with LLaMA 3, DeepSeek, Mistral, Mixtral, QwQ, Phi-2, MedLlama2, Granite3.2 and CodeLlama, gaining expertise in natural language processing (NLP), text generation, code completion, debugging, document analysis, sentiment analysis, and AI-driven automation.The course is packed with real-world AI projects.

You will develop an AI news summarizer, create an AI-powered proofreading tool, build a customer support chatbot, and implement an intelligent assistant for business automation. Each project provides hands-on experience with FastAPI, Python, Ollama, and REST APIs, ensuring you gain full-stack development skills in AI integration.This course also teaches you how to fetch and process real-time data using APIs, making it ideal for those looking to build AI-driven applications that analyze real-time information.

You’ll create a real-time news summarizer, an AI-powered financial report analyzer, and an AI job application screener to automate recruiting.By the end of this course, you will have built AI-powered projects, covering full-stack AI development, text processing, natural language understanding, chatbot development, AI automation, and LLM-based applications. You will be confident in deploying AI models, integrating them into production-ready applications, and leveraging state-of-the-art AI technologies to build intelligent solutions.Whether you are a developer, data scientist, entrepreneur, researcher, or AI enthusiast, this course will provide you with the skills to implement AI models effectively.

You will gain hands-on expertise in building AI-powered web applications, integrating NLP models, and automating tasks with AI-driven tools. This course is perfect for those who want to bridge the gap between AI research and practical implementation by working with top-performing models from Ollama.If you are ready to take your AI development skills to the next level and build cutting-edge AI-powered applications, then this is the perfect course for you!

Syllabus

• Introduction to Full-Stack AI with Ollama
Overview of AI model deployment with Ollama
Course objectives and learning outcomes
• Setting Up the AI Development Environment
Installing and configuring Ollama locally
Introduction to relevant tools: Python, FastAPI, REST APIs
• AI Models and Their Use Cases
Overview of LLaMA 3, Mistral, Mixtral, DeepSeek-R1, QwQ, Phi-2, MedLlama2, Granite3.2, CodeLlama
Comparison and evaluation of models for different tasks
• Building AI-Powered Applications
Developing NLP applications: text summarization, content generation, document proofreading
Building and deploying AI chatbots and personal assistants
Collaboration with FastAPI for backend development
• Implementing NLP Tasks with AI Models
Techniques for summarizing text and extracting key information
Generating content and automating document analysis
Sentiment analysis for business and legal texts
• Code Generation and Debugging with CodeLlama
Auto-generating code and debugging with AI
Enhancing software development efficiency with AI tools
• Integrating AI with Web Applications
Creating a full-stack application with a FastAPI backend
Building interactive web UI for real-time AI model interactions
• Automating Business and Productivity Tasks
AI-powered automation for email replies and meeting summarization
Automated resume generation and recruiting processes
• Working with Real-World Data and APIs
Fetching live data from news, finance APIs, and customer reviews
Analyzing data using AI models for actionable insights
• Optimizing AI Model Performance
Fine-tuning prompts and handling API responses
Techniques to improve accuracy and efficiency
• Real-World AI Projects
Developing an AI news summarizer
Creating an AI-powered proofreading tool
Building a customer support chatbot
Implementing an intelligent assistant for business automation
• Practical AI Application Development
Integrating LLMs into production-ready applications
Leveraging state-of-the-art AI technologies for intelligent solutions
• Course Conclusion and Future Directions
Review of skills gained and applications developed
Next steps for further learning and project development

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Taught by

Dr. Vivian Aranha

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Subjects

Computer Science