Data Science & AI/ML Course in Cuttack
For Cuttack learners, this course goes from raw data to a deployed model — not just a notebook exercise.
- Live cohorts, not recordings
- Practitioner-taught
- Community & placement
- Lifetime access
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For Cuttack analysts and engineers
Live sessions cover Python, statistics, ML models and MLOps basics, with a capstone project you can show in interviews. This course goes from raw data to a deployed model for Cuttack students — not just a notebook exercise.
Curriculum breakdown
Module 1: Python and statistics foundations
Foundational skills Cuttack students need before touching a real model — Python fluency and core statistics.
Topics covered
- Python for data analysis (pandas, numpy)
- Probability and statistical inference
Module 2: Data wrangling and EDA
Cleaning and exploring real, messy data for Cuttack students — the part of the job that takes most of the actual time.
Module 3: Machine learning models
Building, validating and comparing models on real datasets.
Topics covered
- Classification and regression models
- Model evaluation and validation
Module 4: MLOps and deployment basics
Getting a model from a notebook into something running in production.
How the cohort runs
Format and schedule
Live, capstone-driven cohort
Live sessions for Cuttack students, building toward a capstone project from raw data to a deployed model.
Who this course is for
Analysts moving into data science
Cuttack analysts ready to move from reporting into predictive modelling.
Engineers adding ML to their toolkit
Cuttack engineers who want to add machine learning skills to an existing technical background.
Outcomes and support
Capstone project
A full project from raw data to a deployed model, built by Cuttack students during the cohort.
Tools used
Python, pandas, scikit-learn, SQL, plus an intro to PyTorch
The same tools used in real production data science work.
Note
Basic statistics helps, but the course builds up the concepts Cuttack students need as they go.
Quick answer
The Data Science & AI/ML Course in Cuttack takes you from raw data to a deployed machine learning model, covering Python, statistics, ML models and MLOps basics in one live cohort. It's for Cuttack analysts and engineers who want predictive modelling skills backed by a real capstone project, and it's worth it if you need proof you can ship a model, not just a notebook full of exploratory charts.
How this compares to a free Kaggle course or ML MOOC
- Ends with a deployed model, not just a notebook with a final accuracy score
- Live instruction and feedback on your own dataset, instead of pre-recorded lectures with an automated grader
- Covers MLOps and deployment basics alongside modelling, which most free courses skip entirely
- Taught by a practitioner who ships models to production for clients, not an academic curriculum written once and left static
Why Cuttack students choose Deepak Suhag
Taught by a practitioner who ships models to production for clients, not just an academic curriculum.
How it works
Simple, transparent process — from first contact to measurable results.
Enrol & Onboard
Instant portal access, cohort Slack invite, and full session calendar on day one.
Live Sessions
Weekly Zoom sessions with real campaign walkthroughs, live dashboard reviews, and Q&A.
Build & Get Feedback
Hands-on assignments on your own campaigns with direct 1:1 feedback from Deepak.
Graduate & Network
Industry certificate, alumni community, job board access, and ongoing placement support.
Tools & platforms
The exact stack I use daily across growth marketing, web development, AI, and automation — no guesswork, no vendor lock-in.
Why work with Deepak
Here's what makes this different from every other option in Cuttack.
Taught by a practitioner
Every module comes from live campaigns with real budgets — not textbook theory or outdated slides.
Live cohorts, not recordings
Ask questions in real time, get live feedback on your campaigns, and learn with a cohort of peers.
Practitioner-led curriculum
Real ad accounts, real case studies, real budgets — everything relevant to where you work, wherever that is.
Career-ready outcomes
Portfolio projects, alumni Slack, and direct referrals to companies actively hiring in your city.
Everything you need to know
Still have a question that isn't answered here? Reach out directly — I respond to every inquiry personally.
Ask a question01Do I need a math background to join from Cuttack?
Basic statistics helps, but the course builds up the concepts you need as you go.
02What tools does the course use?
Python, pandas, scikit-learn, and SQL, plus an intro to PyTorch.
03Is this different from the Data Analytics course?
Yes — this covers predictive modelling and ML; Data Analytics focuses on SQL, dashboards and reporting.
04Is there a capstone project for Cuttack students?
Yes — a full project from raw data to a deployed model.
05How much does this data science course cost for Cuttack students?
Exact fees are shared on a short intro call since pricing can vary by cohort and current offers. Cuttack students should book a call for current, accurate numbers.
06How is this different from a free Kaggle course or an online ML MOOC?
Free MOOCs typically stop at a notebook with a final accuracy score. This course pushes Cuttack students through the full path to a deployed model, with live feedback and MLOps basics included, so you finish with something closer to real production data science work.
07Do I need a math or programming background to join from Cuttack?
Basic statistics helps, but the course builds up the concepts Cuttack students need as they go. Some comfort with basic programming logic is useful before Module 1, though Python itself is taught from the ground up.
08Is there a certificate at the end of the course?
Yes — Cuttack students who complete the capstone project receive a certificate of completion, along with a portfolio project going from raw data to a deployed model.
09What if I miss a live session while working through the capstone?
Sessions are recorded, so Cuttack students can catch up before the next module. Since the capstone builds cumulatively, it's worth reviewing missed material promptly rather than falling multiple modules behind.
10What career outcomes can Cuttack students expect after this course?
The course is aimed at analysts moving into data science roles and engineers adding ML to their toolkit, both of which typically command a premium over pure reporting or general software roles. The deployed-model capstone project is designed to be a concrete talking point in interviews for Cuttack students changing roles.
I started teaching because I was frustrated seeing marketers memorise theory they'd never use. Every lesson I teach comes from a live campaign, a real mistake, or a real win. You'll leave with skills you can use tomorrow morning.