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Data Science & AI · Masterclass
From Notebook to Production: ML Deployment 101
Your model works in a Jupyter notebook — now what? Turn it into a service real users and apps can call.
Sat, 12 Jul 2026 11:00 AM IST 2 hrs Hindi + English
SR
Dr. Sneha Rao
ML Engineer, ex-Swiggy
4.7(320)
250 already registered · Recording + deployment template shared with registrants
Data Science & AI
Starts in
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--Hrs
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Sat, 12 Jul 2026 11:00 AM IST
Level
Intermediate
Duration
2 hrs
Mode
Online · Live
Language
Hindi + English
Certificate
Yes
Price
Free
About this masterclass
There's a huge gap between a model that scores 95% accuracy in a notebook and one that actually helps anyone. Most data-science learning stops at the notebook — this masterclass is about everything that happens after.
We take a trained model and turn it into a real service: wrapping it in an API, packaging it with Docker, thinking about latency and versioning, and deploying it so an app or website can call it. You will also see the practical concerns nobody mentions in tutorials — input validation, monitoring and model drift.
This is the skill that turns a data-science learner into someone a company can hire, because you can actually ship.
#Machine Learning #MLOps #APIs #Docker #Deployment
What you'll learn
How to expose a trained model as a clean API
Packaging a model + dependencies with Docker so it runs anywhere
Latency, batching and versioning basics for real traffic
Input validation and error handling for model endpoints
What monitoring and model drift mean in practice
A deployment template you can reuse for your own models
What we'll cover
A live, 2 hrs run-through — with time to ask questions.
0–15 min
The notebook-to-production gap
Why a great model isn't a product yet.
15–45 min
Wrapping a model in an API
Serving predictions over HTTP with FastAPI, cleanly.
45–75 min
Packaging with Docker
Reproducible containers so it runs the same everywhere.
75–105 min
Deploy, monitor & drift
Shipping it live, then keeping an eye on it.
105–120 min
Live Q&A
Your models, your deployment questions.
Who is this for?
Data science learners
You can train models but have never deployed one.
Python developers
You want to add ML services to your toolkit.
Aspiring ML engineers
You want the "engineering" half of the ML-engineer role.
Final-year & career switchers
You want a portfolio project that actually runs.
What you need to know
- Basic Python and familiarity with training a simple model
- You have used Jupyter or Colab before
- No prior deployment or DevOps experience needed
Tools & technologies
What we'll touch during the session.
Python FastAPI Docker scikit-learn Monitoring Cloud Deploy
After this masterclass, you'll be able to
- Serve any trained model behind a real API
- Containerise a model so it runs identically anywhere
- Reason about latency, versioning and validation
- Deploy a model service and monitor it
- Ship a portfolio project that is genuinely production-shaped
Meet your mentor
10+ yrs experience
Dr. Sneha Rao
ML Engineer · ex-Swiggy
Sneha holds a PhD in machine learning and spent years at Swiggy putting models into production — from ETA prediction to recommendations serving millions of orders a day. She lives in the space between research and real systems.
She is passionate about closing the gap for data-science learners who can model but have never shipped, and mentors career switchers into ML-engineering roles.
- Deployed ETA & recommendation models at Swiggy scale
- PhD in Machine Learning
- Mentored 150+ learners into ML-engineering roles
MLOpsPythonModel ServingDockerCloud
Keep building
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Why attend
A masterclass, not a webinar
Every Universal CodeBox masterclass is live, practical and genuinely free — built to leave you with something you can use.
Live, not pre-recorded
Ask questions in real time and get them answered on the spot — this is a conversation, not a video.
Taught by a practitioner
Learn from an engineer who does this at scale in production — not a full-time trainer reading slides.
Certificate of participation
Get a shareable certificate you can add to your LinkedIn and résumé after attending.
Lifetime recording
Can't make it live? Register anyway — the full recording and resources land in your inbox.
Takeaways you can use
Leave with patterns, checklists and code you can apply to your own work the very same week.
100% free
No fee, no card, no catch. Reserve a seat, show up, and bring your questions.
Certificate
Get a certificate you can show off
Attend the live session and receive a verifiable certificate of participation — add it to your LinkedIn profile and résumé.
- Shareable on LinkedIn in one click
- Your name and the session title
- Issued by Universal CodeBox
Certificate of ParticipationThis certifies that
Your Name
attended the live masterclass
From Notebook to Production: ML Deployment 101
Dr. Sneha Rao
Loved by learners
What past attendees say
Rated 4.7/5 by 320 learners across this series.
"I'd trained dozens of models and never deployed one. Now I have a template I reuse for every project."
Vivek N
ML Engineer · analytics startup
"The Docker + API part demystified everything. My portfolio finally has something that actually runs online."
Pooja L
Career switcher
"Sneha explains the boring-but-crucial parts — validation, drift — that tutorials skip. Hugely practical."
Aman D
Data Scientist
FAQs
Questions, answered
Do I need a powerful GPU or paid cloud account?
No. We use a small model and free-tier friendly tools so you can follow along on any laptop. The concepts apply the same way at larger scale.
Is this about building models or deploying them?
Deploying them. We assume you can already train a basic model and focus entirely on turning it into a service you can ship.
Is this masterclass really free?
Yes — completely free. There is no fee and no card required. Just reserve your seat and join live.
Will I get a recording if I can't attend live?
Absolutely. Every registrant gets the full session recording along with the slides and resources by email, so register even if you can only catch it later.
Do I get a certificate?
Yes. Attendees receive a certificate of participation that you can download and share on LinkedIn once the session wraps up.
How do I join the session?
After you register, we email you the joining link and a calendar invite. You'll also get a reminder shortly before the session starts.
Can I ask the mentor questions?
Yes — there is a dedicated live Q&A. Bring your questions (or drop them in the chat) and the mentor will answer as many as time allows.
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From Notebook to Production: ML Deployment 101 · Sat, 12 Jul 2026 · 11:00 AM IST. Free to attend, recording included. Only 150 seats left.
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Sat, 12 Jul 2026 · 150 seats left