information Retrieval Course
This course teaches practical information retrieval techniques, from basic keyword search and ranking models like TF-IDF and BM25 to advanced semantic search using embeddings and efficient indexing. Learners will gain skills in data analysis, user intent modeling, and search evaluation through metrics like precision@5, A/B testing, and learning-to-rank methods to build effective search systems.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Information Retrieval Course provides a quick and practical way to build good search systems. You will learn basic keyword approaches, TF-IDF, and BM25, then move to advanced semantic search using embeddings, ANN, and efficient indexing. You will also learn to examine datasets, understand what users want, create test searches, mark relevant results, measure precision at 5, and make real improvements using monitoring, A/B testing, and basic learning-to-rank methods.
Elevify advantages
Develop skills
- Build semantic search: design embedding indexes for fast and relevant results.
- Implement TF-IDF and BM25: tune ranking models for better search accuracy.
- Analyze search data: explore tags, content fields, and quality to improve recall.
- Model user intent: create realistic queries and link them to appropriate resources.
- Evaluate search quality: conduct 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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