Training Completion
For completing the mentor-led training month and shipping your core project.
Unique verifiable ID← All programs
Computer Science / ITBeginner → Intermediate
Machine Learning Engineering
Go beyond notebooks. Build ML systems the way engineers do — clean data pipelines, models trained in PyTorch, honest evaluation, and a trained model served behind an API. You'll finish with a deployed model and the judgement to know when it's actually working.
The program
What you'll build
From classic algorithms to deep learning — and a trained model you actually deploy.
01
ML Foundations
The workflow, metrics and honest evaluation.
02
Deep Learning
Neural nets in PyTorch, trained by you.
03
Feature & Data Pipelines
Clean, reproducible data for real models.
04
Serving & MLOps
Ship a model behind an API and monitor it.
On the curriculum
The learning path
A structured route from the very fundamentals to a shipped capstone — built for beginners, paced for real progress.
01
Module 1: The ML Workflow
- Framing a problem as supervised / unsupervised
- Train/validation/test and leakage — done right
- Classic models: linear, trees, gradient boosting
- Metrics that match the business goal
02
Module 2: Deep Learning with PyTorch
- Tensors, autograd and training loops from scratch
- CNNs for images, embeddings for text
- Transfer learning with pre-trained models
- Regularisation and fighting overfitting
03
Module 3: Evaluation & Tuning
- Honest metrics for real problems
- Hyperparameter tuning
- Cross-validation & avoiding leakage
- Diagnosing under/overfitting
04
Module 4: MLOps Foundations
- Experiment tracking (MLflow)
- Versioning data & models
- Packaging a model for serving
- Reproducible training runs
05
Module 5: Ship & Operate
- Packaging a model and serving it via an API
- Experiment tracking and versioning (MLflow)
- Monitoring drift and retraining triggers
- Capstone: a deployed, monitored model
Hands-on
What you'll ship
Real, guided builds that become portfolio proof — every one starts beginner-friendly and steps up. Open one to see what's inside.
Teach a model to recognise what's in a photo by fine-tuning a pre-trained network. You'll feed it labelled images and watch its accuracy climb. A hands-on, visual intro to deep learning.
Tech Stack
Tools
Skills
Spot the rare suspicious transaction hiding in a sea of normal ones. You'll learn why 'accuracy' can lie when the data is imbalanced. Practical, and a favourite talking point in interviews.
Tech Stack
Tools
Skills
Take a trained model and put it behind a simple web endpoint others can call. You'll package it so it runs the same everywhere. This is the step that turns a notebook into a real product.
Tech Stack
Tools
Skills
Suggest what a user might want next from their past behaviour. You'll build a simple recommender and evaluate how good its picks are. Approachable and genuinely satisfying to demo.
Tech Stack
Tools
Skills
Build a model that reads text and judges whether it's positive or negative. You'll fine-tune a language model on real reviews. A friendly first step into natural-language processing.
Tech Stack
Tools
Skills
Watch a running model and catch it when its accuracy quietly slips. You'll set up a simple dashboard and alerts. It shows you understand that shipping a model is only the start.
Tech Stack
Tools
Skills
What's included
Domain features
Everything you need — structured learning, real projects, mentor support and a verifiable certificate.
Live + Recorded Sessions
Learn live, then rewatch any session whenever you need it.
- Live, interactive sessions
- Recorded for easy revision
- Led by working professionals
Full LMS Access
Every video, file and quiz in one place, on your schedule.
- Complete course materials
- Self-paced revision
- Downloadable resources
Hands-on Projects
Build real, industry-level work you can actually show.
- Real-world scenarios
- Mentor-guided builds
- Step-by-step walkthroughs
Verifiable Certificate
Proof you can show — with a unique, checkable ID.
- Publicly verifiable ID
- Easy to share anywhere
- Tied to your own project
Doubt Solving
Never stay stuck — get help over the LMS or chat.
- Mentor-led doubt clearing
- Quick response times
- Clear, detailed answers
Career Support
Get yourself interview-ready with real, practical help.
- Resume review
- Mock interviews
- Job-readiness plan
Certificates
Two certificates. Both verifiable.
Finish and you don't just walk away with a plain PDF — you earn two certificates: a Training Completion certificate for your training month and an Internship Completion certificate for your internship, each tied to the real work you did and each with a unique ID a recruiter can actually check.
Internship Completion
For your month of real, project-based internship work, reviewed by the same mentors.
Unique verifiable ID
Samples — your copies carry your name, Computer Science / IT and a unique ID.
Where it takes you
Who's hiring for this
Employers across the industry are actively recruiting people with these skills. These are examples of companies hiring in this field — a signal of demand, not a placement guarantee.
Pricing
One price. Everything included.
Pick a plan and get everything you need to go from zero to job-ready.
Core
Enroll now →What's included₹6,000₹7,500
One-time · per programEverything you need to learn a skill end to end.
- Live + Recorded Sessions
- Full LMS Access
- Hands-on Projects
- Verifiable Certificate
- Doubt Solving
- Career Support
- 1:1 mentor code reviews
- Free offline workshop
- Lifetime LMS access
Most popular
Pro
Enroll now →What's included₹8,000₹10,000
One-time · per programCore, plus live mentorship and a free offline workshop.
- Live + Recorded Sessions
- Full LMS Access
- Hands-on Projects
- Verifiable Certificate
- Doubt Solving
- Career Support
- 1:1 mentor code reviews
- Free offline workshop
- Lifetime LMS access
From the audience
What students say afterwards
Real words from students who took this program and walked out with something to show.
★★★★★
“Training a model in PyTorch from scratch, not just calling .fit(), changed how I think. The deployed API sold my resume.”
★★★★★
“The evaluation module alone was worth it — I finally understand why accuracy can lie.”
★★★★★
“Intense but rewarding. Wanted more time on MLOps, otherwise excellent.”
★★★★★
“The hands-on, in-person format is unmatched. I built more in two days than in a whole semester of theory.”
★★★★★
“Mentors who actually work in the field made all the difference — real answers, not textbook ones.”
★★★★★
“Walking out with a project I could actually demo completely changed how my interviews went.”
★★★★★
“The open-stage session gave me my first real experience presenting. Nerve-wracking, and so worth it.”
★★★★★
“Small batch, lots of attention. Nobody got left behind, even the total beginners like me.”
★★★★★
“Genuinely the most practical thing I've done in college. Worth every rupee.”
★★★★★
“Training a model in PyTorch from scratch, not just calling .fit(), changed how I think. The deployed API sold my resume.”
★★★★★
“The evaluation module alone was worth it — I finally understand why accuracy can lie.”
★★★★★
“Intense but rewarding. Wanted more time on MLOps, otherwise excellent.”
★★★★★
“The hands-on, in-person format is unmatched. I built more in two days than in a whole semester of theory.”
★★★★★
“Mentors who actually work in the field made all the difference — real answers, not textbook ones.”
★★★★★
“Walking out with a project I could actually demo completely changed how my interviews went.”
★★★★★
“The open-stage session gave me my first real experience presenting. Nerve-wracking, and so worth it.”
★★★★★
“Small batch, lots of attention. Nobody got left behind, even the total beginners like me.”
★★★★★
“Genuinely the most practical thing I've done in college. Worth every rupee.”
FAQ
Questions, answered
Everything you need to know about the program. Can't find your answer? Reach out to our team.
You need comfort with basics; we build intuition for the rest as you go. The focus is engineering working models, not proofs.
PyTorch for deep learning, plus scikit-learn and XGBoost for classic models — the current industry standard.
Yes — your capstone is a trained model served behind an API and monitored, not just a notebook.
ML engineering is among the most in-demand roles in tech. The logos shown are examples of employers actively recruiting for these skills.
Yes — bring a laptop and charger. We provide the workspace, Wi-Fi, starter files and all the tools you'll use on the day.
You leave with real, demonstrable projects and a verifiable certificate that make you a stronger candidate. We don't promise a job — no honest program can — but everything is built to help you land one.
Perfect — every program starts from the fundamentals and is paced for beginners. Bring your curiosity and we'll handle the rest.
Still have questions?Can't find the answer you're looking for? Chat with our friendly team.Get in touch →
Computer Science / IT
Ready to build & ship?
Grab a seat in Machine Learning Engineering and walk out with a project you can show.