DeepLearning.AI

Advanced Computer Vision with TensorFlow

Advanced Deployment Scenarios with TensorFlow

Advanced Learning Algorithms

Advanced Retrieval for AI with Chroma

AI Agentic Design Patterns with AutoGen

AI Agents in LangGraph

AI and Climate Change

AI and Disaster Management

AI and Public Health

AI For Everyone

AI for Medical Diagnosis

AI for Medical Prognosis

AI For Medical Treatment

AI-Powered Software and System Design

Apply Generative Adversarial Networks (GANs)

Browser-based Models with TensorFlow.js

Build Basic Generative Adversarial Networks (GANs)

Build Better Generative Adversarial Networks (GANs)

Build LLM Apps with LangChain.js

Building Agentic RAG with LlamaIndex

Building AI Applications with Haystack

Building Applications with Vector Databases

Building Multimodal Search and RAG

Building Systems with the ChatGPT API

Building Your Own Database Agent

Calculus for Machine Learning and Data Science

Carbon Aware Computing for GenAI Developers

ChatGPT Prompt Engineering for Developers

Convolutional Neural Networks

Convolutional Neural Networks in TensorFlow

Custom and Distributed Training with TensorFlow

Custom Models, Layers, and Loss Functions with TensorFlow

Data Modeling, Transformation, and Serving

Data Pipelines with TensorFlow Data Services

Data Storage and Queries

Device-based Models with TensorFlow Lite

Efficiently Serving LLMs

Embedding Models: From Architecture to Implementation

Evaluating and Debugging Generative AI

Finetuning Large Language Models

Function-Calling and Data Extraction with LLMs

Functions, Tools and Agents with LangChain

Generative AI for Everyone

Generative AI with Large Language Models

Generative Deep Learning with TensorFlow

Getting Started with Mistral

How Diffusion Models Work

Improving Accuracy of LLM Applications

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Introduction to Data Engineering

Introduction to Generative AI for Software Development

Introduction to On-Device AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

JavaScript RAG Web Apps with LlamaIndex

Knowledge Graphs for RAG

LangChain Chat with Your Data

LangChain for LLM Application Development

Large Language Models with Semantic Search

Linear Algebra for Machine Learning and Data Science

LLMOps

Machine Learning in Production

Multi AI Agent Systems with crewAI

Natural Language Processing in TensorFlow

Natural Language Processing with Attention Models

Natural Language Processing with Classification and Vector Spaces

Natural Language Processing with Probabilistic Models

Natural Language Processing with Sequence Models

Neural Networks and Deep Learning

Open Source Models with Hugging Face

Pair Programming with a Large Language Model

Preprocessing Unstructured Data for LLM Applications

Pretraining LLMs

Probability & Statistics for Machine Learning & Data Science

Prompt Compression and Query Optimization

Prompt Engineering with Llama 2&3

Quality and Safety for LLM Applications

Quantization Fundamentals with Hugging Face

Quantization in Depth

Red Teaming LLM Applications

Reinforcement Learning from Human Feedback

Sequence Models

Sequences, Time Series and Prediction

Source Systems, Data Ingestion, and Pipelines

Structuring Machine Learning Projects

Supervised Machine Learning: Regression and Classification

Team Software Engineering with AI

Understanding and Applying Text Embeddings

Unsupervised Learning, Recommenders, Reinforcement Learning

Vector Databases: from Embeddings to Applications

AI For Everyone （すべての人のためのAIリテラシー講座）

AI、機械学習、ディープラーニングのための TensorFlow 入門

Améliorez les réseaux neuronaux profonds

IA para todos

IA para todos

KI für alle

L’IA pour tous

Modèles de séquence

Neuronale Netze und Deep Learning

Réseaux neuronaux convolutifs

Réseaux neuronaux et Deep Learning

Structurer des projets d’apprentissage automatique

TensorFlow を使った畳み込みニューラルネットワーク

Искусственный Интеллект (ИИ) для всех

Нейронные сети и глубокое обучение

Повышение эффективности глубоких нейросетей

Последовательные модели

Сверточные нейронные сети

Структурирование проектов по машинному обучению

الذكاء الاصطناعي للجميع

الشبكات العصبونية الالتفافية

الشبكات العصبية والتعلم العميق

النماذج المتعاقبة

تعزيز الشبكات العصبية : ضبط وتحسين مقياس فرط المعلمات

هيكلة مشاريع التعلم الآلي

머신 러닝 프로젝트 구조화

시퀀스 모델

신경망 및 딥 러닝

심층 신경망 개선: 하이퍼파라미터 튜닝, 정규화 및 최적화

컨볼루션 신경망