Embeddings Courses and Certifications

Text Representation Techniques for RAG Systems

Explore essential text representation techniques for RAG systems, from Bag-of-Words to embeddings, and learn how to visualize and compare these methods for effective document retrieval and semantic search.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Vector Databases for Embeddings with Pinecone

Discover how the Pinecone vector database is revolutionizing AI application development!

• DataCamp
• 3 hours
• On-Demand
• Free Trial Available

Storing and Managing Embeddings in PostgreSQL with pgvector

Master pgvector for embedding storage and similarity search in PostgreSQL, from setup through practical nearest neighbor queries using various distance metrics.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Scrimba

Retrieval-Augmented Generation (RAG) with Embeddings & Vector Databases

57 ratings at Coursera

Master AI embeddings and vector databases for advanced applications, from setup to semantic searches and chatbot development. Gain practical skills in creating, managing, and querying embeddings for real-world AI solutions.

• Coursera
• 3 hours 34 minutes
• On-Demand
• Paid Course

Vector Databases: from Embeddings to Applications

11 ratings at Coursera

Explore vector databases, embeddings, and their applications in NLP, image recognition, and semantic search. Learn to build RAG applications and conduct fast searches in vast datasets.

• Coursera
• 1 hour 3 minutes
• On-Demand
• Paid Course

Create Embeddings, Vector Search, and RAG with BigQuery

Master building RAG pipelines in BigQuery to reduce AI hallucinations through vector search and embeddings, using Gemini and other generative AI models for improved accuracy.

• Coursera
• 2 hours 30 minutes
• On-Demand
• Paid Course

Packt

NLP – Embeddings & Text Preprocessing in Python

Master the essentials of NLP with text preprocessing techniques, vector models, and neural word embeddings. Learn to transform raw text into usable formats for machine learning through hands-on Python implementations.

• Coursera
• 9 hours 22 minutes
• On-Demand
• Paid Course

Introduction to Vertex AI Embeddings: Text and Multimodal

Explore Vertex AI Embeddings API for text, image, and video use cases in Google Cloud console, gaining hands-on experience with advanced AI technologies.

• Coursera
• 1 hour 30 minutes
• On-Demand
• Paid Course

Coursera Microcredential

Vector DB Foundations, Embeddings & Search Algorithms

Master vector databases, embeddings, and semantic search algorithms to build advanced retrieval systems and multimodal search applications with hands-on Python projects.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course

Coursera

Integrate Embeddings and Chroma

Master automated vectorization pipelines by integrating embedding models with ChromaDB, troubleshooting common failures, and building production-ready ML systems.

• Coursera
• 2 hours 46 minutes
• On-Demand
• Paid Course

Vector Search and Embeddings

Learn how to build powerful search applications with LLM APIs for embeddings using Vertex AI Vector Search. Explore vector search concepts, watch practical demos, and apply your skills in a hands-on lab.

• edX
• 1 week, 1-2 hours a week
• On-Demand
• Free Online Course (Audit)

The Machine Learning Engineer

MLOps: Cómo Generar Vectores de Embeddings para Machine Learning

Descubre cómo generar y utilizar vectores de embeddings en aplicaciones de machine learning, desde la teoría básica hasta la implementación práctica con LLMs y modelos especializados.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Introduction to Embeddings with the OpenAI API

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAI's embedding model!

• DataCamp
• 3 hours
• On-Demand
• Free Trial Available

AI Engineer

How Codeium Breaks Through the Ceiling for Retrieval

Discover how Codeium revolutionizes retrieval beyond embeddings, serving 1M+ developers with AI autocomplete, chat, and search while addressing benchmark limitations and scaling challenges.

• YouTube
• 19 minutes
• On-Demand
• Free Video

Enterprise AI Tutorial - Embeddings, RAG, and Multimodal Agents Using Amazon Nova and Bedrock

Master enterprise AI engineering with Amazon Nova and Bedrock, building multimodal agents, RAG systems, and end-to-end applications for real-world automation like insurance claims.

• freeCodeCamp
• 5 hours 36 minutes
• On-Demand
• Free Video