Ollama - Mastering Generative AI and Beyond

Name: Ollama - Mastering Generative AI and Beyond
Rating: 3.8 (50 reviews)

Unlock the Power of Gen AI with Ollama: Build Spring REST API, Execute Live Function Calls and Integrate with OpenWebUI

Created byRaghu The Security Expert

Last updated 10/2025

English

What you'll learn

Build and integrate a Spring Boot REST API with Ollama to interact with Generative AI models.
Implement real-time function calls to AI models through REST APIs, enabling dynamic AI-driven applications.
Seamlessly integrate and manage AI models using OpenWebUI for enhanced model performance and usability.
Apply the skills learned to deploy and optimize AI applications for real-world scenarios, enhancing user experiences.
Use Gradle to compile and Build Spring Boot Rest API App to interact with AI Models

Course content

5 sections • 21 lectures • 2h 30m total length

Introduction and Agenda5:41
Explore generative AI and Ulama fundamentals, models, and applications. Install Ulama on Windows or Linux and build a REST API to run AI models and fetch live data.

Agenda Items of this section2:30
Define generative AI and review its market examples and usage, then compare machine learning with artificial intelligence and explore key AI models such as GPT, Dall-E, and Codex.
Generative AI - Understanding and some use cases4:25
Establish a basic understanding of generative AI, its content generation across images, text, music, and code. Explore tools like Dall-E, ChatGPT, Copilot, Tabnine, and code-generation models.
Generative AI - Basic Terms7:55
Explore the basic terms of generative AI, including artificial intelligence, machine learning, supervised and unsupervised learning, reinforcement learning, algorithms, and models, with real-world examples.
Understanding Model in layman terms5:26
Use cake-baking analogy to explain the machine learning model: data collection, apply an algorithm, train, refine, finalize, and deploy a model for text generation, image generation, or video generation.
What are Tokens and Embeddings in AI Models?7:26
Understand how tokens and embeddings enable AI models to process prompts, with tokenization (word, subword, and character) converting text into embeddings fed to neural networks.
Prompt Engineering: Strategies and Practical Examples in DevOps and DevSecOps13:45
Master prompt engineering for DevOps and DevSecOps, using zero-shot, one-shot, few-shot, and chain-of-thought strategies. Explore input design, output guidance, model interaction, and practical prompts for Terraform and Kubernetes.
Let's understand the ML type, Algorithm and Model in ChatGPT4:10
Let's understand the ML type, Algorithm and Model in Dall-E3:19
Let's understand the ML type, Algorithm and Model in Github Copilot3:50
Explore the models, algorithms, and training processes behind GitHub Copilot, including the Codex model, transformer architecture, unsupervised and supervised learning, and public code fueling code generation.

What is Ollama and Why should we use it?7:17
HandsOn- Install Ollama on Windows9:31
Install Ollama on Windows to run local language models, assess model sizes and required RAM, download and pull models, and run them offline from the command prompt.
HandsOn - Install Ollama on Linux6:56
Perform a hands-on install of Ulama on a Linux AWS EC2 instance using a curl command. Run the session in CPU-only mode with the Ulama API at localhost:1143.

HandsOn - Create a Spring Boot Rest API app to use Ollama Models - Part 112:07
HandsOn - Create a Spring Boot Rest API app to use Ollama Models - Part 27:21
Build and run a Spring Boot rest api with the Gradle wrapper, call the mistral ulama model via a llama rest controller, and test with httpie for the formatted response.
Case Study - Fetch and Ingest Live data to AI Models - GitHub Repo Walkthrough9:08
Explore a case study that fetches and ingests live weather data into Ulama models via a Spring Boot weather query app, using weather api.com and a GitHub repo walkthrough.
Case Study - Fetch and Ingest Live data to AI Models - Code Walkthrough - Part 111:19
Case Study - Fetch and Ingest Live data to AI Models - Code Walkthrough - Part 25:49
Follow a code walkthrough that fetches live weather data via an API, ingests it into an AI model (Mistral via Llama), and validates results across sources.
HandsOn - Install Docker Desktop on Windows Machine to run OpenWebUI with Ollama2:45
Install Docker Desktop on Windows, enable Virtual Machine Platform and WSL 2, log in to Docker Hub, and prepare to run OpenWebUI with Ollama.
HandsOn - Provide a Web interface to Ollama on Local System17:43

Requirements

Basic Understanding of Java
Basic Knowledge of RESTful APIs
Willingness to Learn Gen AI and Ollama

Description

Disclosure: This course contains the use of artificial intelligence.

Welcome to "Ollama - Generative AI and Beyond," the ultimate course designed to empower you with the skills needed to harness the full potential of Generative AI. In this course, you'll dive deep into the innovative world of Ollama, a powerful platform that enables you to run large language models (LLMs) on your local machine without the need for a GPU. Whether you’re a developer, data scientist, or AI enthusiast, this course will equip you with the practical knowledge and hands-on experience needed to create and deploy AI-driven applications.

Key Features of the Course:

Spring Boot REST API Development: Learn how to create a robust Spring Boot REST API that interacts seamlessly with AI models using Ollama. You'll be guided through setting up your environment, coding the API, and integrating it with Ollama's powerful AI capabilities.
OpenWebUI Integration: Discover how to integrate Ollama with OpenWebUI, a user-friendly interface that simplifies managing and interacting with AI models. This feature enhances your ability to visualize, test, and optimize your models for better performance.
Live Function Calls via REST API: Gain hands-on experience in making live function calls to AI models through REST APIs. You'll learn to implement real-time interactions that bring your AI-driven applications to life.
Practical, Real-World Applications: By the end of the course, you’ll have built a fully functional system that leverages Ollama’s capabilities to execute live function calls. You’ll be equipped to deploy these models in real-world scenarios, providing intelligent automation, data analysis, and enhanced user experiences.
Comprehensive Learning Path: This course is designed to take you from the basics of AI and Ollama to advanced integration techniques, ensuring you gain a thorough understanding of the entire process.
Expert-Led Instruction: Benefit from expert guidance throughout the course, with detailed explanations, practical examples, and hands-on exercises that reinforce your learning.

What You’ll Achieve:

By the end of this course, you will have the confidence to develop and deploy AI-powered applications using Ollama, create scalable REST APIs, and perform live function calls that enhance user interaction. Whether you're aiming to advance your career in AI or seeking to bring innovative AI solutions to your projects, "Ollama - Generative AI and Beyond" offers you the tools and knowledge to succeed.

Who this course is for:

Developers and Programmers
AI Enthusiasts
Data Scientists and Engineers
Students and Learners
QA Engineers
DevOps Engineers
Security Engineers

Ollama - Mastering Generative AI and Beyond

What you'll learn

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Course content

Introduction1 lecture • 6min

Generative AI Basics9 lectures • 53min

Ollama Basics and Installation3 lectures • 24min

Create Spring Boot Rest API application to use AI Models with Ollama7 lectures • 1hr 6min

Next Steps1 lecture • 2min

Requirements

Description

Who this course is for: