Representation Learning Courses and Certifications

Understanding Embeddings and Vector Representations

Learn to generate, compare, and store vector embeddings in Python using OpenAI and Hugging Face models.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Coursera

Validate LLM Embeddings for Production Use

Validate embedding models for production: generate sentence-transformer embeddings, build FAISS indices, measure recall@k, spot bad clusters with UMAP, and benchmark accuracy, latency, and cost.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Embed Everything

Build a scalable embedding pipeline: turn raw text and images into vectors with pre-trained models, then validate them with t-SNE and nearest-neighbor analysis in Python.

• Coursera
• 2 weeks, 2 hours a week
• Self-Paced
• Paid Course

Edureka

Vector Embeddings Fundamentals

Traces a reproducible path from Bag-of-Words vectors to Sentence Transformer embeddings and brute-force semantic search across product catalogues.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Aleksa Gordić - The AI Epiphany

Graph SAGE - Inductive Representation Learning on Large Graphs - GNN Paper Explained

A deep dive into GraphSAGE for inductive node representation learning on large graphs, including neighborhood aggregation, training, and comparisons with GCN and GAT.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Vector Embeddings Tutorial – Create an AI Assistant with GPT-4 & Natural Language Processing

2 ratings

Learn how text embeddings connect to vector databases to build an AI assistant with OpenAI and LangChain.

• freeCodeCamp
• Self-Paced
• Free Video

Bringing ML Workflows to Heterogeneous Cloud Native Machine Learning Platforms Using Intermediate Representation

Explore ML workflow portability using Intermediate Representation in Kubeflow Pipelines v2, enabling cross-platform compatibility and enhanced metadata tracking for efficient machine learning operations.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Bringing ML Workflows to Heterogeneous Cloud Native Machine Learning Platforms Using Intermediate Representation

Explore ML pipeline portability using Intermediate Representation in Kubeflow Pipelines v2. Learn about new features, orchestration engines, and adapting to different frameworks for efficient machine learning workflows.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Graham Neubig

CMU Low Resource NLP Bootcamp 2020 - Neural Representation Learning

Explores how neural models learn word and sentence representations, comparing count-based, prediction-based, and contextual approaches through GloVe, ELMo, BERT, CNNs, and Transformers.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Open Data Science

Representation Learning on Graphs and Networks

Explore graph representation learning with Dr. Veličković, covering deep graph embeddings, CNNs on graphs, and neural message-passing. Discover applications in chemistry, routing, 3D-vision, and recommender systems.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

VinAI

Federated User Representation Learning: Privacy-Preserving Personalization in Distributed Systems

Explore federated user representation learning for privacy-preserving collaborative personalization in machine learning, improving model quality while maintaining user privacy.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Montreal Robotics

Efficient Action Representation for Robot Learning

Explore efficient action representation techniques for enhancing robot learning, focusing on helpful abstractions and theoretical aspects of reinforcement learning.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Learning Embedded Representation of Stock Correlation Matrix Using Graph Machine Learning

Explore embedded representation of stock correlation matrices using graph machine learning. Learn to analyze non-linear relationships among financial instruments for investment processes and risk management.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Stanford Seminar - Audio Research: Transformers for Applications in Audio, Speech and Music

A research seminar on using Transformer architectures for raw audio synthesis, large-scale audio understanding, and discrete latent representations.

• YouTube
• 48 minutes
• Self-Paced
• Free Online Course

Deep Generative Models - Discrete Latent Variable Models - Lecture 17

Explore discrete latent variable models in deep generative modeling, covering key concepts and applications in AI and machine learning.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video