information Retrieval Course
This course covers foundational and advanced techniques in information retrieval, from keyword-based methods like TF-IDF and BM25 to semantic search using embeddings and approximate nearest neighbors. Participants will learn to analyze datasets, model user intent, evaluate search performance with metrics like precision@5, and implement improvements through A/B testing and learning-to-rank principles.
4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Information Retrieval Course provides a swift, practical route to developing high-quality search. You will investigate baseline keyword techniques, TF-IDF, and BM25, then progress to semantic retrieval using embeddings, ANN, and scalable indexing. Learn to analyse datasets, model user intent, design test queries, label relevance, compare precision@5, and plan genuine improvements with monitoring, A/B tests, and learning-to-rank fundamentals.
Elevify advantages
Develop skills
- Build semantic search: design embedding indexes for fast, relevant results.
- Implement TF-IDF and BM25: tune ranking models for higher search precision.
- Analyse search data: explore tags, content fields, and quality to refine recall.
- Model user intent: craft realistic queries and map them to the right resources.
- Evaluate search quality: run A/B tests, label relevance, and compare precision@5.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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