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Taught in Stage 2
Last Updated: August 2026
Tokenization & NLP
Bridging human language and machine representation.
Overview
Tokenization is the process of breaking text into smaller units (tokens) such as words, subwords, or characters. It is a crucial preprocessing step for language models. Modern LLMs use subword tokenization algorithms like Byte-Pair Encoding (BPE) or WordPiece to handle large vocabularies efficiently.
Why Learn This in 2026?
Understanding tokenization is essential for managing context limits, calculating API costs, and debugging issues where language models fail on specific words, non-English languages, or code syntax.
How We Teach This
Module 10: Tokenization
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Market Trajectory
Stable & Essential
Core knowledge required for any serious work with language models.
- Fundamental for optimizing LLM inference costs.
Hiring Landscape
Demand LevelMedium-High
Typical Salary Impact₹10L - ₹25L+ (India)
Top Employers Seeking This
NLP StartupsTech Giants
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