Semantic Search Courses and Certifications

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
• Self-Paced
• Paid Course

Advanced Retrieval for AI with Chroma

11 ratings at Coursera

Enhance AI retrieval with advanced techniques: query expansion, cross-encoder reranking, and embedding adapters. Improve relevance and accuracy of retrieved information for more effective AI applications.

• Coursera
• 1 hour 3 minutes
• Self-Paced
• Paid Course

Large Language Models (Using Huggingface) (Live Online)

8 ratings at CourseHorse

Tap into the capabilities of large language models using Hugging Face in this comprehensive 3-day course.

• CourseHorse
• 20 hours
• Self-Paced
• $1,495.00

Embedding Models: From Architecture to Implementation

Explore embedding models' evolution, architecture, and implementation. Learn to build and train dual encoders, understand BERT, and apply models in semantic search and RAG pipelines.

• Coursera
• 1 hour 30 minutes
• Self-Paced
• Paid Course

LangChain Course for LLM Application Development

Master LangChain to build scalable retrieval-augmented applications with LLMs, covering Model I/O, embeddings, vector stores, chains, memory, and agents for real-world GenAI workflows.

• Coursera
• 8 hours 6 minutes
• Self-Paced
• Paid Course

Quick Start Guide to Large Language Models (LLMs): Unit 1

Explore NLP evolution, master attention mechanisms, and build RAG systems using ChatGPT, Llama, and T5 while developing prompt engineering skills for effective LLM communication.

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

Build AI Agents with Enterprise Databases

Discover how to build AI agents that securely connect to enterprise databases using Google Cloud's MCP Toolbox, implementing intelligent querying with vector embeddings.

• Coursera
• 6 hours 27 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

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/week
• Self-Paced
• Paid Course

Packt

Natural Language Processing - Transformers with Hugging Face

Master Hugging Face Transformers for NLP tasks including sentiment analysis, text generation, and named entity recognition through hands-on Python implementations and real-world applications.

• Coursera
• 5 hours 53 minutes
• Self-Paced
• Paid Course

Coursera

Grasp Vector DB Basics

Discover how vector databases enable semantic search and AI applications through embeddings, similarity-based retrieval, and strategic decision-making for modern data solutions.

• Coursera
• 1 hour 43 minutes
• Self-Paced
• Paid Course

Starweaver

GenAI Data Engineering and RAG Systems

Master advanced data engineering techniques to build enterprise-grade RAG systems that transform raw data into intelligent, context-aware AI applications with vector databases.

• Coursera
• 6 hours 49 minutes
• Self-Paced
• Paid Course

Programming Generative AI: Unit 3

Master multimodal AI by exploring contrastive language-image pre-training, latent diffusion models, and text-to-image generation with hands-on fine-tuning techniques.

• Coursera
• 8 hours 17 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

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

Coursera Career Certificate

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