AI Engineering · Foundation
AI Engineering — Zero to Advanced
The full path: mathematical foundations through modern systems engineering, for people who want to build intelligent systems rather than call APIs.
- Level
- Foundation
- Mathematics depth
- Working
- Engineering depth
- Systems
- Modality
- Cohort-based · live engineering sessions
- Duration
- Announced per cohort
- Status
- Open for inquiry
Audience
Who this is for
- Developers moving into AI engineering roles
- Engineers who use model APIs but want to understand what they call
- Career changers with quantitative or programming backgrounds
Career paths
Prerequisites
- — No AI background required
- — Comfort with structured thinking
- — Willingness to write code from week one
Outcomes
Skills acquired
- Read and reason about modern architectures from first principles
- Design, train, evaluate and serve models with engineering discipline
- Build grounded and agentic systems that survive production constraints
Tools used
Curriculum Architecture
Module progression
Expandable, visual, ordered. Each module is a prerequisite-aware step, not an isolated video.
- 01Mathematical Foundations for AI
- 02Python & Data Systems for Engineering
- 03Machine Learning Foundations
- 04Neural Networks & Optimization
- 05Deep Learning Systems
- 06Representation Learning
- 07Perception & Language Architectures
- 08Foundation Models & LLM Engineering
- 09Grounded AI Systems
- 10Agentic Systems & Orchestration
- 11Evaluation, Serving & Production Architecture
Projects
- A trained and evaluated classifier with a written error analysis
- A grounded answer system over a real corpus
- A supervised agent workflow with tool calling and tracing
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: Mathematics → Machine Learning → Deep Learning → Foundation Models → Systems.
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.