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Harnessing Ollama – Create Local LLMs with Python · LearnSpace
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courseraПрограммирование

Harnessing Ollama – Create Local LLMs with Python

Курс от Packt
Средний≈ 8.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will learn how to create local language models using Ollama and Python. By the end, you will be equipped with the tools to build LLM-based applications for real-world use cases. The course introduces Ollama's powerful features, installation, and setup, followed by a hands-on guide to exploring and utilizing Ollama models through Python. You'll dive into topics such as REST APIs, the Python library for Ollama, and how to customize and interact with models effectively. You'll begin by setting up your development environment, followed by an introduction to Ollama, its key features, and system requirements. After grasping the fundamentals, you'll start working with Ollama CLI commands and explore the REST API for interacting with models. The course provides practical exercises such as pulling and testing models, customizing them, and using various endpoints for tasks like sentiment analysis and summarization. The journey continues as you dive into Python integration, using the Ollama Python library to build LLM-based applications. You'll explore advanced features like working with multimodal models, creating custom models, and using the show function to stream chat interactions. Then, you'll develop full-fledged applications, such as a grocery list categorizer and a RAG system, exploring vector stores, embeddings, and more. This course is ideal for those looking to build advanced LLM applications using Ollama and Python. If you have a background in Python programming and want to create sophisticated language-based applications, this course will help you achieve that goal. Expect a hands-on learning experience with the opportunity to work on several projects using the Ollama framework.

Навыки, которые вы освоите

LLM ApplicationRetrieval-Augmented GenerationRestful APIVector DatabasesEmbeddingsSoftware InstallationLarge Language ModelingCommand-Line InterfaceDevelopment EnvironmentPython ProgrammingTool CallingUser Interface (UI)Application Development

Программа курса

9 модулей · 61 учебных материалов

01Introduction5 материалов

Introduction

Introduction & What Will You LearnВидеоFull Course ResourcesЧтениеCourse PrerequisitesВидеоPlease WATCH this DEMOВидео

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Packt - Course Instructors

Преподаватель курса

Harnessing Ollama – Create Local LLMs with Python
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 8.6 ч

9 модулей

Язык: Английский

Субтитры: Испанский

Часть программы вашего университета
Development Environment SetupВидео
02Ollama Deep Dive - Introduction to Ollama and Setup9 материалов

Ollama Deep Dive - Introduction to Ollama and Setup

Ollama Deep Dive - Ollama Overview - What is Ollama and AdvantagesВидеоOllama Key Features and Use CasesВидеоSystem Requirements & Ollama Setup - OverviewВидеоDownload and Setup Ollama and Llam3.2 Model - Hands-on & TestingВидеоOllama Models Page - Full OverviewВидеоOllama Model Parameters Deep DiveВидеоUnderstanding Parameters and Disk Size and Computational Resources NeededВидеоSetting Up a Python Development EnvironmentDIALOGUEOllama Deep Dive - Introduction to Ollama and Setup - AssessmentЗадание
03Ollama CLI Commands and the REST API - Hands-on8 материалов

Ollama CLI Commands and the REST API - Hands-on

Ollama Commands - Pull and Testing a ModelВидеоPull in the Llava Multimodal Model and Caption an ImageВидеоSummarization and Sentiment Analysis & Customizing Our Model with the ModelfileВидеоOllama REST API - Generate and Chat EndpointsВидеоOllama REST API - Request JSON ModeВидеоOllama Models Support Different Tasks - SummaryВидеоExploring O Lama and Local Language ModelsDIALOGUEOllama CLI Commands and the REST API - Hands-on - AssessmentЗадание
04Ollama - User Interfaces for Ollama Models4 материалов

Ollama - User Interfaces for Ollama Models

Different Ways to Interact with Ollama Models - OverviewВидеоOllama Model Running Under Msty App - Frontend Tool - RAG System Chat with DocsВидеоUsing Lama Commands for Model ManagementDIALOGUEOllama - User Interfaces for Ollama Models - AssessmentЗадание
05Ollama Python Library - Using Python to Interact with Ollama Models8 материалов

Ollama Python Library - Using Python to Interact with Ollama Models

The Ollama Python Library for Building LLM Local Applications - OverviewВидеоInteract with Llama3 in Python Using Ollama REST API - Hands-onВидеоOllama Python Library - Chatting with a ModelВидеоChat Example with StreamingВидеоUsing Ollama show FunctionВидеоCreate a Custom Model in CodeВидеоExploring LLaMA InterfacesDIALOGUEOllama Python Library - Using Python to Interact with Ollama Models - AssessmentЗадание
06Building LLM Applications with Ollama Models10 материалов

Building LLM Applications with Ollama Models

Hands-on: Build a LLM App - Grocery List CategorizerВидеоBuilding RAG Systems with Ollama - RAG & LangChain OverviewВидеоDeep Dive into Vectorstore and Embeddings - The Whole Picture - Crash CourseВидеоPDF RAG System Overview - What We'll BuildВидеоSetup RAG System - Document Ingestion & Vector Database Creation and EmbeddingsВидеоRAG System - Retrieval and QueryingВидеоRAG System - Cleaner CodeВидеоRAG System - Streamlit UIВидеоInteracting with OLAMA via Python APIDIALOGUEBuilding LLM Applications with Ollama Models - AssessmentЗадание
07Ollama Tool Function Calling - Hands-on6 материалов

Ollama Tool Function Calling - Hands-on

Function Calling (Tools) OverviewВидеоSetup Tool Function Calling ApplicationВидеоCategorize Items Using the Model and Setup the Tools ListВидеоTools Calling LLM Application - Final ProductВидеоOrganizing a Grocery List using PythonDIALOGUEOllama Tool Function Calling - Hands-on - AssessmentЗадание
08Final RAG System with Ollama and Voice Response6 материалов

Final RAG System with Ollama and Voice Response

Voice RAG System - OverviewВидеоSetup EleveLabs API Key and Load and Summarize the DocumentВидеоOllama Voice RAG System - Working!ВидеоAdding ElevenLab Voice Generated Reading the Response Back to UsВидеоFunction Calls with Large Language ModelsDIALOGUEFinal RAG System with Ollama and Voice Response - AssessmentЗадание
09Wrap Up5 материалов

Wrap Up

Wrap Up - What's Next?ВидеоImplementing LLMs for Interactive Voice ResponsesDIALOGUEWrap Up - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание