Become a Data Scientist in 16 Weeks
Not $2,000. Not 6 months of theory. Not pre-recorded videos. 100% live mentor-led classes. Ship 10+ real ML projects and become the most hireable data scientist in the room.
4.9 Rating
114 Reviews
100%
Live Classes
80+
Students Enrolled
10+
projects you ship
10 modules — from AI foundations to production-grade Agentic AI
A structured, build-first path: master the fundamentals, the tooling, LLMs and prompting, then go deep on RAG, agents and multi-agent systems — finishing with a full-stack capstone.
Python Foundations
The language every data scientist speaks
Statistics & Probability
The mathematical intuition behind every model
Exploratory Data Analysis
Uncover stories hiding in messy data
Supervised Learning — Regression
Predict numbers from data
Supervised Learning — Classification
Predict categories & make decisions
Unsupervised Learning
Find hidden patterns without labels
NLP & Text Analytics
Turn text into structured insights
SQL & Databases for Data Science
Query real databases like a pro
Model Deployment & MLOps
Ship models into production
Capstone Project
Build an end-to-end data science solution
Every module, topic by topic
Expand any module to see exactly what you'll cover — 10 modules and 63+ topics, with hands-on builds throughout and a full-stack capstone to finish.
Core Python
- chevron_right Variables, data types & operators — the building blocks
- chevron_right Control flow & functions — logic that drives programs
- chevron_right Lists, dicts & comprehensions — Python data structures
- chevron_right File I/O & error handling — working with real data
Data Stack
- chevron_right NumPy for numerical computing — arrays, broadcasting & vectorization
- chevron_right pandas for data manipulation — DataFrames, groupby & merging
- chevron_right Jupyter Notebooks — interactive data exploration
Hands-on
Set up your data science environment and wrangle your first real-world dataset.
Descriptive Stats
- chevron_right Central tendency & spread — mean, median, variance, std dev
- chevron_right Distributions — normal, binomial, Poisson
- chevron_right Correlation & covariance — measuring relationships
Inferential Stats
- chevron_right Hypothesis testing — t-tests, chi-square, ANOVA
- chevron_right Confidence intervals — quantifying uncertainty
- chevron_right p-values & significance — making data-driven decisions
Hands-on
Perform a full statistical analysis on a real business dataset.
Data Wrangling
- chevron_right Handling missing data — imputation strategies
- chevron_right Outlier detection — identifying anomalies
- chevron_right Feature engineering — creating meaningful features
Visualization
- chevron_right Matplotlib & Seaborn — static, publication-quality plots
- chevron_right Plotly for interactivity — dashboards & dynamic charts
- chevron_right Data storytelling — presenting insights that drive action
Hands-on
Build a complete EDA report with actionable insights.
Models
- chevron_right Linear & polynomial regression — the classics, done right
- chevron_right Ridge, Lasso & ElasticNet — regularization for better models
- chevron_right Decision tree & random forest regression — non-linear power
Evaluation
- chevron_right MAE, MSE, RMSE, R² — picking the right metric
- chevron_right Cross-validation — reliable model assessment
- chevron_right Hyperparameter tuning — GridSearch & RandomSearch
Hands-on
Build a house-price prediction model and deploy it as an API.
Models
- chevron_right Logistic regression — the workhorse of classification
- chevron_right SVM & k-NN — distance-based classifiers
- chevron_right Random forests & gradient boosting — ensemble power
- chevron_right XGBoost & LightGBM — competition-winning models
Advanced
- chevron_right Confusion matrix & ROC/AUC — beyond simple accuracy
- chevron_right Handling imbalanced data — SMOTE & class weights
- chevron_right Feature importance — understanding model decisions
Hands-on
Build a customer churn predictor with business-ready metrics.
Clustering
- chevron_right K-Means & K-Medoids — partitioning algorithms
- chevron_right DBSCAN & hierarchical clustering — density-based discovery
- chevron_right Silhouette analysis — evaluating cluster quality
Dimensionality Reduction
- chevron_right PCA — principal component analysis
- chevron_right t-SNE & UMAP — visualizing high-dimensional data
Hands-on
Segment real customers for a marketing campaign.
Text Processing
- chevron_right Tokenization & stemming — breaking text into features
- chevron_right TF-IDF & bag of words — classic text representations
- chevron_right Sentiment analysis — opinion mining at scale
Modern NLP
- chevron_right Word embeddings — Word2Vec & GloVe
- chevron_right Text classification — spam, sentiment, topic detection
Hands-on
Build a product-review sentiment classifier.
Core SQL
- chevron_right SELECT, JOIN, GROUP BY — the essential toolkit
- chevron_right Window functions — advanced analytics in SQL
- chevron_right Subqueries & CTEs — complex query patterns
Integration
- chevron_right Python + SQL together — SQLAlchemy & pandas integration
- chevron_right Database design basics — normalization & indexing
Hands-on
Analyse a multi-table business database and surface key KPIs.
Deployment
- chevron_right FastAPI & Flask — serve predictions as REST APIs
- chevron_right Docker basics — containerize your ML pipeline
- chevron_right Streamlit dashboards — interactive ML web apps
MLOps
- chevron_right Model versioning — tracking experiments with MLflow
- chevron_right CI/CD for ML — automated retraining pipelines
Hands-on
Deploy your best model as a live API with monitoring.
Everything from all nine modules, brought together into one comprehensive, real-world project.
Project Scope
- chevron_right Real Business Problem — define one that needs data science
- chevron_right Data Pipeline — collection, cleaning & feature engineering
What You Build
- chevron_right Complete EDA & statistical analysis — deep data understanding · Modules 2–3
- chevron_right ML Model Pipeline — train, tune & evaluate · Modules 4–6
- chevron_right NLP Component — text analysis if applicable · Module 7
- chevron_right SQL Analytics — database queries & reporting · Module 8
- chevron_right Deployed API/Dashboard — live, shareable output · Module 9
Deliverables
- chevron_right Working ML Product — a deployed, usable data science solution
- chevron_right Jupyter Notebook — documented analysis + code
- chevron_right Demo — presentation or video walkthrough
- chevron_right GitHub Repo — clean, reproducible code
Real products you'll build — not toy demos
EDA Deep-Dive
A full exploratory data analysis on a messy real-world dataset with actionable insights.
Price Predictor
A regression model that forecasts house prices — trained, tuned and deployed.
Customer Segmentation
Cluster real customers with unsupervised ML to drive smarter marketing.
Sentiment Classifier
An NLP model that scores product reviews — deployed behind a live API.
ML Dashboard
A Streamlit app that tracks models, compares metrics and serves predictions.
…and your own capstone
Shipped, documented and ready to show any employer or client.
Three tracks, one outcome — you ship
Students & Freshers
- check_circleShip 10+ real ML projects for your portfolio
- check_circleBecome the most hireable builder in your batch
- check_circleJob board, referrals & portfolio reviews
- check_circleAnalyse your first real dataset by Week 1
Business Owners
- check_circleMake data-driven decisions, not gut calls
- check_circleBuild dashboards that save hours every week
- check_circleUnderstand the data your team already has
- check_circleTurn data into measurable business outcomes
Career Switchers
- check_circleBuild the portfolio data roles demand
- check_circleLearn Python, SQL & ML from scratch
- check_circleTransition into data science with confidence
- check_circleStand out in every data science interview
Sound like you?
Watching data careers take off without you
Drowning in tutorials — built 0 models
Burned by theory-only courses with no real datasets
Imposter syndrome on every "data scientist" job post
Tools that never click together into one project
No idea what production-grade ML looks like
Wasted money on generic, pre-recorded courses
Running out of time to make the switch
If any of these hit home — this cohort is built for you.
Built to fit around your job or college
3 classes / week
Tue, Thu, Sat — steady, manageable momentum.
6–7 PM IST
Evenings — fits around college and a full-time job.
2+ hours per class
We never wrap until the topic is truly done.
Recordings in 24h
Every class lands in your student portal within a day.
Same skills. A fraction of the price & time.
| Premium 6-month cohort | Ankit Kumar Academy — AI Live | |
|---|---|---|
| Price | $2,000 | $499.00 |
| Duration | 6 months | 16 weeks |
| Live classes | Some (mostly recorded) | 100% live |
| First deployed project | ~3 months | Week 1 |
| Projects shipped | 2–3 | 10+ |
| Beginners welcome | Needs stats/maths background | Total beginners welcome |
| Career support & referrals | close | check_circle |
One client pays for the whole cohort — many times over
$240.96
per analytics project
$963.86
per ML consulting gig
$1,807.23+
monthly data science salary
One client = a 5×–16× return on your $499.00 investment.
Everything you get for $499.00
Originally $2,000. No upsells, no hidden tiers — one price, everything in.
Enroll now arrow_forward
Ankit Kumar
Founder & Lead AI Instructor
Ankit Kumar is an AI engineer, educator, and the founder of Ankit Kumar Academy. Over the last 6+ years he has helped more than 4,500 learners break into data and AI careers — translating dense research into practical, build-first lessons that actually ship.
4,500+ Learners Mentored
Across data science, AI and analytics programs worldwide.
25+ Courses Published
From Advanced Excel to Agentic AI engineering.
500+ Career Transitions
Students placed into data and AI roles at top companies.
6+ Years in Industry
Shipping production data and AI systems at scale.
This cohort is not for you if…
Frequently asked
A lean team, a volume strategy and a 100% live format — no inflated production costs to pass on to you.
Yes. We start from Python basics and build up gradually. No prior coding or maths degree needed.
No. We teach all the statistics you need from scratch, building intuition through real datasets — not textbook formulas.
You attend the remaining live classes and unlock all past recordings instantly, so you never fall behind.
Attend the classes, submit the assignments, and if you still cannot build ML models, you get a full refund.
You keep 3-month recording access and lifetime access to the alumni community.
Yes — no-cost EMI (3 months) on credit cards via Razorpay at checkout.
Why learners rate this cohort 4.9 on Google
Real reviews from students across India, the USA and the UK who built genuine skills and changed their careers with us.
Based on 512 Google reviews
location_onBengaluru, India
I joined with zero coding background and within two months I had built and deployed real ML projects. The live mentorship makes all the difference — every doubt was cleared the same day. I landed a data analyst role right after.
location_onLondon, UK
Easily the best AI program I have taken, and I have tried a few. It is 100% live and completely build-first — I shipped a working RAG app and an autonomous agent I now use at work. Worth every penny.
location_onAustin, USA
The build-first approach is exactly what I needed — no fluff, no endless theory, just real projects with a mentor who genuinely cares. I went from marketing to an AI engineering role in under four months.
location_onPune, India
From "I cannot code" to deploying my own apps. The classes are practical, the community is incredibly supportive, and the project portfolio genuinely helped me clear interviews. Highly recommended.
location_onManchester, UK
The Power BI and analytics track transformed how I work. Within weeks I was building dashboards my whole team now relies on. Clear teaching, real datasets and brilliant support throughout.
location_onSan Francisco, USA
Ankit explains genuinely hard concepts so simply. The agentic AI module alone was worth the fee — I finally understand how multi-agent systems work under the hood, and I have built three of my own since.
location_onChennai, India
The Excel-to-Power BI pathway was perfectly structured. Each lesson built on the last and by the end I was confidently presenting automated reports to senior management. Got promoted within two months of finishing.
location_onLagos, Nigeria
I was sceptical about online courses after wasting money on two others. This one is different — the live sessions, the projects, the community. I shipped a real computer vision app and it is in my portfolio now.
location_onDelhi, India
What sets Ankit apart is that he genuinely cares about each student. I had never written a line of Python before and now I am building end-to-end data science pipelines. The career guidance was a huge bonus.
location_onSydney, Australia
The generative AI course was mind-blowing. I built a custom chatbot for my company using LangChain and deployed it on AWS — all during the course. My manager was genuinely impressed.
location_onKochi, India
I switched from a non-tech background to data analytics after completing this course. The hands-on projects gave me the confidence to crack interviews. Currently working at a top fintech company.
location_onBerlin, Germany
Outstanding course structure. Every week we built something real. The capstone project alone added three talking points to my resume. The instructor feedback was detailed and genuinely helpful.
location_onHyderabad, India
I took the Data Science and AI course after my engineering degree and it was the best decision. Real projects, real datasets, real skills. I received two job offers before even finishing the course.
location_onToronto, Canada
The curriculum is incredibly well-designed. From Python basics to deploying ML models, everything was taught with real-world context. The community support is amazing and Ankit responds to every question personally.
location_onMumbai, India
After trying multiple platforms, this is where I finally learned to build production-grade AI applications. The agentic AI projects were particularly impressive — I now have a portfolio that stands out in interviews.
Ready to become an AI builder?
100% live. 15+ projects shipped. $499.00 $2,000 — with no-cost EMI available at checkout.
verified_user Ship-an-app guarantee — attend, submit, and if you can't ship, get a full refund.