AI/ML Foundations & Python
Python for data, the maths that matters, and your first trained models. The launch pad for every other track.
Admissions open · Cohort starting soon
Learn to build with AI — not just talk about it.
CapabilityNext is a hands-on training institute for technical students and working engineers. You ship real projects every week, mentored by people who do this for a living.
4specialisation tracks
90%project-based hours
1:8mentor-to-student ratio
Specialisation tracks
Four routes into a career in applied AI
Start with foundations, then go deep in the track that matches the role you want. Every track is capstone-driven and portfolio-ready.
Generative AI & LLM Engineering
Prompting, RAG, agents, evaluation and fine-tuning — build production LLM applications end to end.
Data Engineering & MLOps
Pipelines, feature stores, model serving, monitoring and CI/CD for ML on the cloud.
Computer Vision & NLP
Deep-learning specialisations: image models, transformers, and applied language systems.
Featured courses
Popular right now
GenAI & LLM
LLM Application Engineering
Design, build, evaluate and ship an LLM product: retrieval, tool use, agents, guardrails and cost control.
IntermediateDetails →
Foundations
Python & Maths for Machine Learning
From NumPy to gradient descent. Build the intuition and the toolkit every AI engineer relies on daily.
BeginnerDetails →
Data & MLOps
MLOps on the Cloud
Package, deploy, monitor and retrain models with pipelines, containers and CI/CD you can reuse at work.
AdvancedDetails →
Why CapabilityNext
Built like an engineering team, not a lecture hall
Project every week
You leave each module with something that runs — code, a model, a deployment — reviewed by a mentor.
Practitioner mentors
Small groups, live reviews, and office hours with engineers shipping AI systems in industry.
Job-ready portfolio
Graduate with 3–5 documented projects, a capstone, and interview prep tuned to AI roles.
Fits around your job
Evening and weekend cohorts, recorded sessions, and a pace designed for working students.
Modern stack
Current tools: PyTorch, Hugging Face, vector databases, LangChain-style orchestration, cloud GPUs.
Learn responsibly
Evaluation, safety, bias and cost are part of every build — not an afterthought.
How it works
From application to portfolio in four steps
Apply & assess
A short form and a 20-minute call to place you in the right track and cohort.
Foundations sprint
Two weeks levelling everyone on Python, tooling and workflow before the track begins.
Build weekly
Live sessions, guided labs and a mentor-reviewed project every module.
Capstone & showcase
Ship a real project, present it, and walk away with a portfolio and reference.
120+hours of guided build time per track
4tracks from beginner to advanced
1:8mentor-to-student ratio
100%online, evening & weekend friendly
Mentors
Taught by people who ship
Our mentors work in ML engineering, data platforms and applied research. They bring current problems into the classroom.
AK
A. Krishnan
ML Engineer · Recommender systemsRM
R. Mehta
LLM Engineer · RAG & agentsSN
S. Nair
Data Platform Lead · MLOpsPT
P. Thomas
Applied Researcher · Computer vision
Student stories
What graduates say
"I came in writing scripts and left having deployed a monitored model on the cloud. The weekly reviews are what made it stick."
"The LLM track was exactly the practical grounding I needed. My capstone became a demo I now show in interviews."
"As a final-year student this bridged the gap between coursework and what teams actually expect. Worth every evening."
The next cohort is filling up
Tell us where you are and what you want to build. We'll help you pick a track and hold your seat.
Apply now