Ollama Mastery: Run Local AI Models with Python & CLI
Learn how to install, manage, and run local AI models using Ollama with CLI and Python integration.
🏷️
Ollama
LocalAI
LLM
AIModels
CLI
GenerativeAI
Local_Deployment
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1 students
- ▶️ Recorded Course
- Course Instructor: Md Abdullah Al Mamun
- Category: Artificial Intelligence
- Sub Category: Generative AI
- Child Category: Ollama
- Last updated: 05/2026
- Language: English
| Course Style Plan | ||||
|---|---|---|---|---|
| 🎬 Course Mode | ⏰ Daily Spend | 🗓️ Weekly Schedule | 📊 Total Class | ⏳ Course Duration |
| ▶️Recorded Course | 1 Hours | Mon, Wed, Sat | 1 | 1 Hours |
Ollama Mastery: Run Local AI Models with Python & CLI
Artificial Intelligence
>
Generative AI
>
Ollama
Ollama
LocalAI
LLM
AIModels
CLI
GenerativeAI
Local_Deployment
Learn how to install, manage, and run local AI models using Ollama with CLI and Python integration.
Course Requirements
- 💻 Basic Computer Knowledge: Familiarity with using a computer, installing software, and browsing the internet.
- 🧠 Basic Programming Understanding (Optional but Helpful): Knowledge of any programming language (like C, Java, or JavaScript) will be beneficial.
- ⚙️ Laptop / PC Configuration: Minimum 8GB RAM (recommended), SSD storage, and a modern processor for smooth development.
- 🌐 Internet Connection: Stable internet connection for downloading tools, dependencies, and accessing resources.
- 🧑💻 Software Installation: Ability to install tools like Flutter SDK, Android Studio, or VS Code.
- 📱 Android Device (Optional): A physical Android phone for real-device testing (emulator can also be used).
- 🧩 Google Account: Required for accessing Google services and publishing apps on Play Store.
- 🔥 Willingness to Learn & Practice: Dedication to coding, debugging, and building real-world projects.
Course Details
This course is designed to help you master Ollama, a powerful tool for running large language models (LLMs) locally on your computer—without relying on cloud services.
You’ll begin with a complete introduction to Ollama and its ecosystem, understanding how it enables developers to run and manage AI models efficiently on local machines.
Next, you’ll learn how to install Ollama and navigate its user interface, followed by mastering essential CLI commands to control and interact with models seamlessly. You’ll also explore how to switch between different models and optimize your workflow.
The course then moves into practical development by integrating Ollama with Python. You’ll learn how to call models using HTTP APIs and use the official Python package to build AI-powered applications.
By the end of this course, you will:
- Understand Ollama and its ecosystem
- Install and configure Ollama locally
- Use CLI commands to manage AI models
- Switch and manage multiple models efficiently
- Integrate Ollama with Python using APIs
- Build local AI-powered workflows without cloud dependency
This course is perfect for developers, AI enthusiasts, and anyone interested in running AI models locally for privacy, speed, and cost efficiency.
Course content
4 sections • 8 lectures • 00h 32m total length
Chapter
1. Introduction about Ollama
3 lectures
00h 12m
▶
Ollama Tutorial for Beginners | Run LLMs Locally on Your Computer
Video
3m
Discover how to use Ollama to run powerful Large Language Models (LLMs) directly on your local computer without relying on cloud services. In this beginner-friendly Ollama tutorial, you’ll learn what Ollama is, how it works, why developers and AI enthusiasts are using it, and how to install and manage local AI models easily.
▶
Ollama Complete Ecosystem Guide | Library, GitHub, Discord & Docs
Video
5m
Welcome to this complete walkthrough of the Ollama Ecosystem! In this video, you’ll explore everything Ollama offers — from the official homepage and model library to GitHub, Discord community, documentation, and Ollama Cloud services.
▶
Ollama Setup Tutorial | System Requirements, Download & Installation
Video
4m
This beginner-friendly guide covers everything you need to get started with local Large Language Models (LLMs), including system requirements, GPU support, RAM recommendations, and installation instructions.
Chapter
2. Ollama UI Tutorial
2 lectures
00h 08m
▶
Ollama UI Tutorial for Beginners | Chat with Local AI Models Easily
Video
3m
Ollama UI makes AI chatting simple, clean, and beginner-friendly. You’ll explore the interface, create new chats, manage conversation history, download models, and start prompting AI models like Gemma directly from your local machine.
▶
Ollama CLI Tutorial for Beginners | CMD Commands Explained Step by Step
Video
5m
Welcome to this complete Ollama CLI tutorial for beginners! In this video, you’ll learn how to use Ollama commands inside the Windows Command Prompt (CMD) to install, manage, run, switch, and remove AI models locally. Ollama’s Command Line Interface (CLI) gives developers and AI enthusiasts powerful control over Large Language Models (LLMs) directly from the terminal.
Chapter
3. Use Ollama Locally
2 lectures
00h 09m
▶
Ollama Model Switching Guide | CLI & UI Tutorial for Beginners
Video
3m
In this video, you’ll learn how to switch between different AI models in Ollama using both the Command Line Interface (CLI) and the Ollama User Interface (UI). Ollama makes it easy to experiment with multiple Large Language Models (LLMs) like Gemma and LLaMA directly on your local machine. Whether you prefer using commands or a visual interface, this tutorial will guide you step by step.
▶
Connect Python with Ollama Locally | HTTP API & Chat Endpoint Explained
Video
6m
In this beginner-friendly video, you’ll learn how to connect Python applications with Ollama using the local HTTP API and stream AI responses in real time. Ollama exposes a powerful local API that allows developers to interact with Large Language Models (LLMs) directly from Python code, Postman, curl, or any HTTP client.
Chapter
4. Ollama Project
1 lecture
00h 03m
▶
Ollama Python Client Tutorial | Build Chatbots & AI Tools Locally
Video
3m
In this beginner-friendly video, you’ll learn how to connect your Python applications with Ollama using the official Ollama Python library. Instead of manually writing HTTP requests, the Ollama Python package provides a simple and efficient way to interact with local Large Language Models (LLMs) directly from Python code.
What you'll learn?
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Perform statistical analysis using both R and Python
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Create advanced visualizations with ggplot2 and Seaborn
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Build and evaluate predictive machine learning models
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Clean, transform, and prepare messy real-world datasets
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Complete end-to-end data science projects for your portfolio
What will be included in this course?
24/7 Access to Course Materials
Downloadable Resources
Certificate of Completion
Lifetime Access
Mobile & TV Access
Frequently Asked Question
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OrbitOCP offers both live interactive classes and recorded sessions so you can learn at your own pace.
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Yes, you will receive a certificate of completion after successfully finishing the course requirements.
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Professional software engineer with 12+ years of experience leading end-to-end application development with project delivery. Results-driven Generative AI & Data Science Engineer with 8+ years of experience delivering enterprise-scale software and AI solutions across fintech, telecom, and education domains. Strong expertise in Python, machine learning, GenAI frameworks, and DevSecOps, with hands-on experience in model fine-tuning, NLP pipelines, vector databases, and cloud platforms. Proven leader in building secure, scalable systems, translating data into business insights, and driving end-to-end AI projects from design to deployment.