NLP · Intermediate
NLP & Language Intelligence
Text processing, embeddings, sequence models, attention and semantic search — the engineering of systems that understand and organize language.
- Level
- Intermediate
- Mathematics depth
- Working
- Engineering depth
- Systems
- Modality
- Cohort-based
- Duration
- Announced per cohort
- Status
- Open for inquiry
Audience
Who this is for
- Engineers building search, classification or extraction systems
- Developers preparing for foundation-model work
- Product engineers working on language features
Career paths
Prerequisites
- — Python fluency
- — Basic ML concepts
Outcomes
Skills acquired
- Build search and classification systems with measured quality
- Understand the path from embeddings to transformers to LLMs
- Design language features that degrade gracefully
Tools used
Curriculum Architecture
Module progression
Expandable, visual, ordered. Each module is a prerequisite-aware step, not an isolated video.
- 01Text Processing & Linguistic Structure
- 02Embeddings & Representation Spaces
- 03Sequence Models: RNN & LSTM
- 04Attention Mechanisms
- 05Transformers for Language
- 06Language Models & Pretraining
- 07Semantic Search & Grounding
- 08NLP Systems in Production
Projects
- A semantic search system with quality metrics
- A text classification pipeline with error analysis
Assessment philosophy
Assessment is engineering review: written error analyses, measured system behavior, defended design decisions. We evaluate whether you can explain and justify what you built — because production will.
Stack position: Language → Representations.
FAQ
Frequently asked questions
Do I need a mathematics background?
It depends on the program. Foundation-tier programs start from the mathematics itself; advanced tiers list working linear algebra as a prerequisite. The Mathematics for AI program exists precisely to close that gap.
Is this a bootcamp?
No. CAS Studies is an engineering institute. Programs are built around architectures, derivations and projects with written error analysis — not tutorial replays.
How long does a program take?
The two diploma tracks run on fixed lengths — AI Architectural Engineering spans 18 months, AI Application Engineering spans 1 year. All other program durations are announced per cohort, by modality.
Will I build real systems?
Yes. Every program ends in projects that resemble production work: evaluated models, grounded answer systems, supervised agents — with measurement, not vibes.