Program Overview
The Certificate in AI-Powered Search & Information Retrieval is designed for developers, content strategists, and product teams who want to dramatically improve how users find information on websites and applications. The program covers the full arc from TF-IDF and BM25 through dense retrieval, hybrid search, and modern AI-enhanced search systems like Scolta.
The Scolta Case Study
Throughout the program, students analyze and extend Scolta — Tag1 Consulting's AI-powered search enhancement that layers query expansion, semantic reranking, and AI-generated overviews onto existing search infrastructure without requiring vector databases or embedding pipelines. Scolta's architecture is used as the primary case study for practical, production-ready AI search.
Curriculum Highlights
- Classical IR: TF-IDF, BM25, inverted indexes, Pagefind and static site search
- Neural IR: Dense retrieval (DPR, E5, BGE), bi-encoders vs. cross-encoders, semantic similarity
- Query Understanding: Query expansion, spell correction, synonym expansion, AI-powered query rewriting
- Hybrid Search: Combining lexical and semantic signals, reciprocal rank fusion, learned sparse retrieval (SPLADE)
- AI Overviews & Summarization: Using LLMs to synthesize search results, RAG for search, citation generation
- Case Studies: Scolta on Drupal, Elasticsearch + LLM, Algolia AI, Typesense
Sample Courses
- IR-101: Information Retrieval Fundamentals: BM25 to Modern Search
- IR-201: Neural Retrieval: Embeddings and Dense Search
- IR-210: Query Expansion and AI-Powered Query Understanding
- IR-220: Hybrid Search and Reranking
- IR-230: AI Overviews and Retrieval-Augmented Generation
- IR-290: Capstone: Deploy an AI-Enhanced Search System