Embeddings Courses and Certifications

Coursera

Text Generation with Cohere: Recognizing Similarities

Learn to analyze semantic similarity and generate text using Cohere's API. Integrate AI-driven language models into Python scripts for practical text analysis and creative content generation.

• Coursera
• 2 hours 30 minutes
• Self-Paced
• Paid Course

Create a RAG Application with BigQuery

Master building RAG pipelines by implementing embeddings, vector search, and Gemini integration within BigQuery to create powerful AI-driven data solutions.

• Coursera
• 1 hour
• Self-Paced
• Paid Course

Scrimba

Build a Support Agent with Vercel AI SDK

Discover how to build a production-ready customer support AI agent using Vercel AI SDK, integrating retrieval, web search, and structured outputs for reliable responses.

• Coursera
• 2 hours 23 minutes
• Self-Paced
• Paid Course

Board Infinity

Transformers in Action: A Practical Approach to NLP and AI

Master Transformer architectures for NLP through hands-on coding with BERT, GPT, and T5. Build real-world applications using Hugging Face tools for classification, summarization, and deployment.

• Coursera
• 18 hours 37 minutes
• Self-Paced
• Paid Course

Coursera

Understand RAG Basics

Discover how to build reliable AI applications using Retrieval-Augmented Generation to ground LLMs with external data and eliminate hallucinations through hands-on Python development.

• Coursera
• 1 hour 39 minutes
• Self-Paced
• Paid Course

RAG: Vector Databases and Retrievers

Master advanced RAG techniques using FAISS, ChromaDB, and modern retrievers while building high-performance search applications with LangChain and LlamaIndex, and Gradio.

• edX
• 5 hours
• Self-Paced
• Free Online Course (Audit)

Packt

RAG-Driven Generative AI

Master RAG pipelines using LlamaIndex, Deep Lake, and Pinecone to build scalable, context-aware AI systems that minimize hallucinations and optimize performance for real-world applications.

• Coursera
• 15 hours 59 minutes
• Self-Paced
• Paid Course

Coursera Credential

Vector Databases for Machine Learning: A Comprehensive Guide

Master vector databases, build semantic search and RAG systems, and implement Chroma & Weaviate to advance careers in ML engineering, AI infrastructure, and data science.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

LearnKartS

Build Production AI Agents with RAG & MCP

Master building production-ready AI agents using RAG & MCP, integrating Gemini and OpenAI with Node.js backends, embeddings, semantic search, and scalable architectures for real-world applications.

• Coursera
• 11 hours 31 minutes
• Self-Paced
• Paid Course

Coursera

Vector Database Foundations and Core Concepts

Master vector database technologies, from generating embeddings and similarity metrics to implementing ANN search and HNSW optimization for semantic search and RAG systems.

• Coursera
• 12 hours
• Self-Paced
• Paid Course

LearnKartS

Advanced Agentic AI: Production Data Architecture

Master building production-ready Agentic AI systems with RAG pipelines, pgVector, PostgreSQL, and MongoDB—creating scalable, end-to-end architectures for real customer and order workflows.

• Coursera
• 8 hours 9 minutes
• Self-Paced
• Paid Course

Coursera

Databricks GenAI Engineering

Master building production-grade GenAI apps on Databricks by constructing RAG pipelines, fine-tuning models with MLflow, and evaluating responses for relevance, hallucination rate, and latency.

• Coursera
• 3 hours 23 minutes
• Self-Paced
• Paid Course

Board Infinity

RAG Systems & Agentic Workflows with Pinecone and LangGraph

Master RAG pipelines, vector databases, and agentic workflows using Pinecone, LangChain, and LangGraph to build production-ready AI systems with memory, semantic search, and observability.

• Coursera
• 19 hours 21 minutes
• Self-Paced
• Paid Course

RAG: Vector Databases with ChromaDB

Learn vector databases, similarity search, and ChromaDB operations to build recommendation systems, and improve AI retrieval performance in GenAI applications using embeddings.

• edX
• 18 hours
• Self-Paced
• Free Online Course (Audit)

Configuring Vector Search in AlloyDB

Discover how to set up and implement vector search capabilities in AlloyDB through hands-on practice in the Google Cloud console.

• Coursera
• 1 hour
• Self-Paced
• Paid Course