К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Generative AI, LLMs, and Advanced Applications with Python · LearnSpace
Назад в каталог
courseraАнализ данных

Generative AI, LLMs, and Advanced Applications with Python

Курс от Packt
Продвинутый≈ 10.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course 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. Delve into the world of generative AI and large language models (LLMs) with hands-on applications using Python. You'll explore the power of Variational Auto-Encoders (VAEs) and Generative Adversarial Networks (GANs) to create synthetic data, including images and music. Alongside, you'll get to grips with Transformers and self-attention mechanisms, which are foundational to models like GPT and ChatGPT, unlocking advanced AI applications. Learn the intricacies of GPT architecture, including tokenization and fine-tuning, and apply these concepts using tools like Hugging Face and Google Colab. The course also covers cutting-edge topics such as Retrieval Augmented Generation (RAG) and advanced LLM agents. Through interactive activities, you’ll create powerful AI applications like chatbots and personalized systems. This course is designed for learners aiming to advance their knowledge of AI, machine learning, and Python, with a focus on generative models and LLMs. If you want to build your own AI-driven applications and deepen your understanding of state-of-the-art AI technologies, this course is for you.

Навыки, которые вы освоите

Fine-tuningChatGPTAutoencodersOpenAI APIRetrieval-Augmented GenerationApplied Machine LearningModel EvaluationGenerative AIGenerative Adversarial Networks (GANs)Artificial Intelligence and Machine Learning (AI/ML)OpenAIGenerative Model ArchitecturesGenerative AI AgentsHugging FaceLarge Language ModelingLLM ApplicationApplication Programming Interface (API)

Программа курса

6 модулей · 57 учебных материалов

01Generative Models10 материалов

Generative Models

Introduction to the Course 'Generative AI, LLMs, and Advanced Applications with Python'ЧтениеFull Specialization ResourceЧтениеVariational Auto-Encoders (VAEs) - How They WorkВидеоVariational Auto-Encoders (VAE) - Hands-On with Fashion MNISTВидео

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

Generative AI, LLMs, and Advanced Applications with Python
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 10.6 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Испанский, Японский, Казахский, Венгерский

Часть программы вашего университета
Generative Adversarial Networks (GANs) - How They WorkВидео
Generative Adversarial Networks (GANs) - Playing with Some DemosВидео
Generative Adversarial Networks (GANs) - Hands-On with Fashion MNISTВидео
Learning More about Deep LearningВидео
Understanding Autoencoders and Variational AutoencodersDIALOGUE
Generative Models - AssessmentЗадание
02Generative AI: GPT, ChatGPT, Transformers, Self-Attention Based Neural Networks15 материалов

Generative AI: GPT, ChatGPT, Transformers, Self-Attention Based Neural Networks

The Transformer Architecture (encoders, decoders, and self-attention.)ВидеоSelf-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depthВидеоApplications of Transformers (GPT)ВидеоHow GPT Works, Part 1: The GPT Transformer ArchitectureВидеоHow GPT Works, Part 2: Tokenization, Positional Encoding, EmbeddingВидеоFine Tuning / Transfer Learning with TransformersВидео[Activity] Tokenization with Google CoLab and HuggingFaceВидео[Activity] Positional EncodingВидео[Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERTВидео[Activity] Using small and large GPT models within Google CoLab and HuggingFaceВидео[Activity] Fine Tuning GPT with the IMDb datasetВидеоFrom GPT to ChatGPT: Deep Reinforcement Learning, Proximal Policy GradientsВидеоFrom GPT to ChatGPT: Reinforcement Learning from Human Feedback and ModerationВидеоUnderstanding TransformersDIALOGUEGenerative AI: GPT, ChatGPT, Transformers, Self-Attention Based Neural Networks - AssessmentЗадание
03The OpenAI API (Developing with GPT and ChatGPT)12 материалов

The OpenAI API (Developing with GPT and ChatGPT)

[Activity] The OpenAI Chat Completions APIВидео[Activity] Using Functions in the OpenAI Chat Completion APIВидео[Activity] The Images (DALL-E) API in OpenAIВидео[Activity] The Embeddings API in OpenAI: Finding similarities between wordsВидео[Activity] The Completions API in OpenAIВидеоThe Legacy Fine-Tuning API for GPT Models in OpenAIВидео[Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star TrekВидеоThe New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!Видео[Activity] The OpenAI Moderation APIВидео[Activity] The OpenAI Audio API (speech to text)ВидеоThe OpenAI API (Developing with GPT and ChatGPT) - AssessmentЗаданиеIntegrating OpenAI Chat Completions APIDIALOGUE
04Retrieval Augmented Generation (RAG), Advanced RAG, and LLM Agents12 материалов

Retrieval Augmented Generation (RAG), Advanced RAG, and LLM Agents

Retrieval Augmented Generation (RAG): How it works, with some examplesВидеоDemo: Using Retrieval Augmented Generation (RAG) to simulate Data from Star TrekВидеоRAG Metrics: The RAG Triad, relevancy, recall, precision, accuracy, and moreВидео[Activity] Evaluating our RAG-based Cdr. Data using RAGAS and langchainВидеоAdvanced RAG: Pre-Retrieval; chunking; semantic chunking; data extractionВидеоAdvanced RAG: Query RewritingВидеоAdvanced RAG: Prompt Compression, and More Tuning OpportunitiesВидео[Activity] Simulating Cdr. Data with Advanced RAG and langchainВидеоLLM Agents and Swarms of AgentsВидео[Activity] Building a Cdr. Data chatbot with LLM Agents, web search & math toolsВидеоUnderstanding Retrieval-Augmented Generation (RAG)DIALOGUERetrieval Augmented Generation (RAG), Advanced RAG, and LLM Agents - AssessmentЗадание
05Final Project4 материалов

Final Project

Your Final Project Assignment: Mammogram ClassificationВидеоFinal Project ReviewВидеоApplying Supervised Machine Learning TechniquesDIALOGUEFinal Project - AssessmentЗадание
06You Made It!4 материалов

You Made It!

More to ExploreВидеоConclusion to the Course 'Generative AI, LLMs, and Advanced Applications with Python'ЧтениеFull course practice assessmentЗаданиеFull course assessmentЗадание