Awakening
Go from AI curiosity to clean mental models, prompting habits, and working prototypes.
You learn how LLMs behave, where they fail, and how to turn vague intent into structured outputs.
Model intuition
Prompt literacy
Prototype speed
AI learning lab for builders
You don’t learn AI here. You build intelligence.
Unpuzzle It
From your first prompt to autonomous AI agents, CodeCkt is where engineers stop consuming AI and start creating it.
Lab Transmission
From prompt to product. From user to builder to architect.
Build-first programs for learners who want real systems, strong execution habits, and a credible path into AI engineering.
0days to shipping your first AI systems
0days to production-grade agentic engineering
0+portfolio-ready builds across real AI patterns
Journey Map
Move through the circuitry of becoming an AI builder.
This is not a timeline. It is a progression of systems capability, where each layer unlocks a more intelligent way to build.
Control
Move beyond chat interfaces into APIs, evaluation loops, and deterministic product behavior.
We teach orchestration, guardrails, retrieval, and developer workflows that make AI usable.
API wiring
Guardrails
Structured outputs
Intelligence
Design memory, retrieval, tools, and system prompts that make apps feel genuinely capable.
This is where assistants become products and isolated features become systems.
Retrieval systems
Memory design
Tool usage
Autonomy
Build agents that can plan, call tools, recover from failure, and operate within constraints.
We focus on agentic workflows that are impressive for users and responsible in production.
Planning loops
Agent orchestration
Recovery logic
Deployment
Ship with observability, UX, APIs, and an engineer's understanding of what survives outside demos.
You leave with systems you can show, explain, defend, and extend.
Observability
Product UX
Production behavior
Programs
Choose the track that matches your current altitude.
Full week-by-week syllabus, phase breakdown, capstone options, and differentiation live on the Programs page.
8 weeks / 40 days
Freshers, students, and early AI learners
AI Builder Bootcamp
Become capable of building AI apps, RAG assistants, and basic agents.
Build prompt-powered apps with structured outputs
Ship a RAG assistant backed by real documents
Understand APIs, model selection, and eval basics
Graduate with a visible portfolio instead of only notes
150 days / 6 months
Working engineers moving into AI
Agentic AI Engineer Fellowship
Become an AI engineer capable of production systems, agents, automation, and AI products.
Architect multi-step agentic workflows
Build RAG pipelines with retrieval quality controls
Ship automation systems, internal copilots, and AI products
Think like a systems engineer, not a demo assembler
Full curriculum & syllabus
Explore the full curriculum, phase-by-phase progression, and what makes each path right for where you are now.
What You Build
Projects that look more like shipping than studying.
Why CodeCkt
Most places help you understand AI. CodeCkt helps you become dangerous with it.
The difference is not branding. It is what you practice, what you ship, and what kind of builder you become by the end.
Avoided lane What most do
CodeCkt lane What CodeCkt does for you
We do not optimize for this
Most programs explain AI concepts, tools, and trends, but leave you unsure how to build something end to end.
What you get instead
CodeCkt makes you build working AI systems from day one with engineering structure, review loops, and clear implementation thinking.
You leave knowing how to turn AI ideas into actual products, not just how to talk about them.
We do not optimize for this
A lot of learning stops at notebooks, toy prompts, and isolated demos that never become usable software.
What you get instead
We push you into apps, APIs, agents, workflows, and product-style builds that feel closer to real-world engineering.
You build portfolio proof that employers, collaborators, and clients can actually understand.
We do not optimize for this
Typical institutes sell confidence through certificates, completion badges, and generic placement language.
What you get instead
CodeCkt builds confidence through shipped work, technical clarity, sharper judgment, and visible proof of capability.
You become easier to trust because your work shows what you can do before you ever claim it.
We do not optimize for this
Most learners are taught to think in isolated features, prompts, or shortcuts instead of full system behavior.
What you get instead
We train you to think in system flows: context, retrieval, tools, UX, failure states, deployment, and iteration.
That is what helps you grow from learner to builder to serious AI engineer.
Experience / Lab
A build space for people who want engineering instincts, not just AI vocabulary.
Studio-style learning
Short theory bursts, guided builds, critique loops, and product-style iteration.
System thinking
Prompts matter, but so do APIs, retrieval, evaluation, state, and user experience.
Proof over promise
Each phase pushes toward artifacts you can demo, discuss, and turn into career leverage.
Small cohort energy
High-signal feedback loops, build reviews, and sharper engineering decisions at every stage.
Outcomes
Two timelines. One goal: become someone who can build real AI systems.
You can ship useful AI apps
Prompted workflows, retrieval-backed assistants, and practical product thinking.
You can architect agentic systems
Production-minded workflows with orchestration, observability, and sharper engineering judgment.
Enquiry
Need clarity before you commit?
Use this quick form if you want help choosing the right track, understanding readiness, or figuring out whether CodeCkt matches where you are right now.
- Get a direct answer on which program fits your current level.
- Ask about prerequisites, timeline, and how intense the learning path is.
- Move to the full application only when you are ready.
Most enquiries get a response within 24 hours.
Build your edge
Stop consuming AI. Start creating it.
Unpuzzle It
Join CodeCkt if you want a serious, modern path into building intelligence with products, systems, and visible proof of work.