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Backend Engineers & Information Retrieval Students

Building a Search Engine: Inverted Indexes & TF-IDF

6 weeks
0 Learners
Jul 23

The fundamentals behind Elasticsearch and Meilisearch: built from first principles. This comprehensive curriculum is designed to give you hands-on experience with Building a Search Engine: Inverted Indexes & TF-IDF.

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About this Course

The fundamentals behind Elasticsearch and Meilisearch: built from first principles. This comprehensive curriculum is designed to give you hands-on experience with Building a Search Engine: Inverted Indexes & TF-IDF. This Backend Engineers & Information Retrieval Students curriculum is designed to give you hands-on experience and deep conceptual understanding. Across 6 intensive modules, you'll tackle real-world challenges and build practical projects that reinforce your learning. By the end of this journey, you'll have the skills and proof of work to demonstrate your expertise.

What you'll learn

Master the core concepts of document processing, tokenization & stemming.
Gain hands-on experience with inverted index architecture & postings lists.
Understand the architecture behind relevance scoring with tf-idf & okapi bm25.
Implement production-grade index updates, positional search & evaluation.

Prerequisites

intermediate Level

Requires basic familiarity with the tech stack.

  • Familiarity with core concepts

Ideal for

Backend Engineers & Information Retrieval Students

Backend Engineers & Information Retrieval Students Professionals
Tech Enthusiasts
W1

Document Processing, Tokenization & Stemming

Master the core concepts of document processing, tokenization & stemming.

3 videos65m
3 readings
3 topics
1 homework
Learn

Topics

1.1
Text Tokenization, Lowercasing & Stopword Filtering
8 minutes
1.2
Stemming Algorithms (Porter Stemmer) & Lemmatization
13 minutes
1.3
Building N-gram Tokenizers for Substring Search
44 minutes
W2

Inverted Index Architecture & Postings Lists

Gain hands-on experience with inverted index architecture & postings lists.

3 videos40m
3 readings
3 topics
1 homework
Learn
W3

Relevance Scoring with TF-IDF & Okapi BM25

Understand the architecture behind relevance scoring with tf-idf & okapi bm25.

3 videos47m
3 readings
3 topics
1 homework
Learn
W4

Index Updates, Positional Search & Evaluation

Implement production-grade index updates, positional search & evaluation.

3 videos98m
3 readings
3 topics
1 homework
Learn
W5

Web Crawling and Graph Processing

Build a scalable, polite web crawler and analyze the link graph (PageRank).

3 videos38m
3 readings
3 topics
1 homework
Learn
W6

Ranking and Query Processing

Implement relevance ranking models like BM25 and optimize query execution.

3 videos57m
3 readings
3 topics
1 homework
Learn
01

Learn

Watch curated videos and read study resources

02

Practice

Practice what you learned

03

Build Projects

Build projects using your new gained knowledge

04

Submit & Verify

Submit your project and get verified by our system

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