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Data Science & AIBestsellerBeginner to Advanced
Data Science with AI
Master data analysis, machine learning and generative AI with Python — from statistics and pandas to deep learning and LLMs — through real datasets and industry projects.
4.8(1,560 ratings)
6,100 learners enrolled
7 months 340+ hours Online · Live + Recorded Hindi + English
7-day no-questions-asked refund · Verified certificate on completion
Data Science & AI
Limited-time price
₹29,999₹69,999
Offer ends in
--Days
--Hrs
--Min
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EMI from ₹2,500/mo 240 lessons
Level
Beginner to Advanced
Duration
7 months
Content
340+ hours
Lessons
240
Projects
12
Language
Hindi + English
About this course
Data Science with AI is an applied, project-first program that turns beginners into job-ready data professionals. You learn by building real models on real datasets, not by memorising theory.
You start with Python and statistics, move through data wrangling and visualisation, then core machine learning, deep learning and natural language processing — finishing with the generative-AI and LLM skills every team now wants, plus how to deploy models.
With live mentorship, weekly problem-solving and a capstone reviewed by practising data scientists, you graduate with a portfolio of 12 projects and the ability to clear analytics and ML interviews.
What you'll learn
Program confidently in Python for data work
Wrangle and clean data with pandas and NumPy
Explore and visualise data to find real insights
Apply statistics and probability to decisions
Query data at scale with SQL
Build and evaluate machine-learning models
Train neural networks for vision and text
Work with NLP, embeddings and transformers
Build apps on top of LLMs and generative AI
Deploy and serve models behind an API (MLOps)
Skills you'll gain
Python NumPy & pandas Data Visualisation Statistics SQL Machine Learning Deep Learning NLP Generative AI LLMs TensorFlow MLOps
Course curriculum
9 modules · 240+ lessons
Module 1 · Python for Data Science
The language and tooling of data work.
3 weeks 5
Module 1 · Python for Data Science
The language and tooling of data work.
- Python essentials & environments
- Jupyter notebooks & Colab
- NumPy arrays & vectorised computing
- Working with files & APIs
- Clean, reusable data code
Module 2 · Data Wrangling with pandas
Turn messy data into analysis-ready tables.
3 weeks 5
Module 2 · Data Wrangling with pandas
Turn messy data into analysis-ready tables.
- Series & DataFrames
- Cleaning & handling missing data
- Merging, grouping & pivoting
- Time-series basics
- Feature engineering
Module 3 · Visualisation & EDA
See the story in your data.
2 weeks 4
Module 3 · Visualisation & EDA
See the story in your data.
- Matplotlib & Seaborn
- Exploratory data analysis
- Dashboards with Power BI/Tableau
- Communicating insights
Module 4 · Statistics & SQL
The maths and querying every analyst needs.
3 weeks 4
Module 4 · Statistics & SQL
The maths and querying every analyst needs.
- Descriptive & inferential statistics
- Probability & distributions
- Hypothesis testing & A/B tests
- SQL joins, windows & aggregations
Module 5 · Machine Learning
Build models that predict and classify.
5 weeks 5
Module 5 · Machine Learning
Build models that predict and classify.
- Regression & classification
- Trees, forests & boosting
- Model evaluation & tuning
- Clustering & dimensionality reduction
- Pipelines with scikit-learn
Module 6 · Deep Learning
Neural networks for vision and text.
4 weeks 5
Module 6 · Deep Learning
Neural networks for vision and text.
- Neural network fundamentals
- TensorFlow/Keras & PyTorch basics
- CNNs for images
- RNNs & sequence models
- Transfer learning
Module 7 · NLP & Generative AI
Language models and the modern AI stack.
4 weeks 5
Module 7 · NLP & Generative AI
Language models and the modern AI stack.
- Text processing & embeddings
- Transformers explained
- Working with LLMs & prompting
- Retrieval-augmented generation (RAG)
- Building an AI-powered app
Module 8 · MLOps & Deployment
Take models to production.
2 weeks 4
Module 8 · MLOps & Deployment
Take models to production.
- Serving a model behind an API
- Experiment tracking
- Docker for ML
- Monitoring models in production
Module 9 · Capstone & Placement Prep
Prove it and get hired.
2 weeks 4
Module 9 · Capstone & Placement Prep
Prove it and get hired.
- End-to-end capstone project
- Portfolio & Kaggle profile
- Case-study & ML interviews
- Resume & referrals
Tools & technologies
The real-world stack you'll be fluent in by the end.
Python Jupyter NumPy pandas scikit-learn TensorFlow PyTorch SQL Power BI Hugging Face OpenAI / LLMs Docker
Projects you'll build
A portfolio of 12 real, resume-ready projects — here are the highlights.
Sales & Revenue Analytics
Clean, analyse and visualise a retail dataset to surface business insights and a dashboard.
pandasEDAPower BI
Customer Churn Prediction
Build and tune a classification model that predicts which customers will leave.
scikit-learnML
House Price Regression
Feature-engineer and model housing data to predict prices with strong accuracy.
RegressionFeature Eng.
Image Classifier (CNN)
Train a convolutional network to classify images with transfer learning.
Deep LearningTensorFlow
Sentiment & NLP App
Analyse text sentiment and build an NLP pipeline with embeddings.
NLPTransformers
Capstone: RAG Chatbot with an LLM
Build a retrieval-augmented AI assistant over your own documents and serve it via an API.
LLMsRAGDeployment
Who is this course for?
Beginners & students
You want a structured path into data science and AI without a maths PhD.
Working professionals
You want to add data & AI skills to move into analytics or ML roles.
Engineers & analysts
You already work with data and want to level up to machine learning.
Career switchers
You are moving into one of the fastest-growing fields in tech.
What you need to start
- A laptop and a stable internet connection
- Basic maths comfort (we revise what you need)
- No prior programming required
- Around 8–10 hours a week to learn and practise
After this course, you'll be able to
- Analyse and visualise real datasets end to end
- Build, evaluate and tune machine-learning models
- Train deep-learning models for vision and text
- Build applications powered by LLMs and generative AI
- Deploy and monitor models in production
- Present a portfolio of 12 data & AI projects
Meet your instructors
Learn from engineers who've shipped at scale.
12+ yrs
Dr. Ananya Iyer
Lead Data Scientist · ex-Myntra
Ananya built recommendation and demand-forecasting systems at Myntra and has published applied-ML research. She leads the ML, deep learning and generative-AI tracks.
- Built recommender systems at Myntra
- Published applied-ML research
Machine LearningDeep LearningNLP
9+ yrs
Karthik Rao
Senior ML Engineer · ex-Ola
Karthik productionised pricing and ETA models at Ola. He teaches the Python, data-wrangling and model-deployment (MLOps) parts of the program.
- Productionised pricing & ETA models at Ola
- Mentored 200+ aspiring data scientists
PythonMLOpsTensorFlow
Career outcomes
Where this course can take you
Graduates land roles across product companies, with an average package of ₹10 LPA.
₹10 LPA
Avg package
6,100+
Learners
6+
Role tracks
Data Analyst
₹4–10 LPA
Data Scientist
₹8–22 LPA
Machine Learning Engineer
₹8–24 LPA
AI Engineer
₹10–28 LPA
Business/BI Analyst
₹5–12 LPA
Data Engineer
₹7–20 LPA
Our learners work at
MyntraOlaFlipkartAmazonFractalMu SigmaSwiggyPhonePe
Certificate
Earn a certificate that gets noticed
Complete the program and receive a verified certificate with a unique ID and a public verification link — add it to your LinkedIn profile and résumé to prove your skills.
- Unique ID with public verification
- Shareable on LinkedIn in one click
- Issued by Universal CodeBox
Certificate of CompletionThis certifies that
Your Name
has successfully completed
Data Science with AI
Program Director
Loved by learners
What our learners say
Rated 4.8/5 by 1,560 learners.
4.8
1,560 ratings
5
84%
4
11%
3
3%
2
1%
1
1%
"The projects made all the difference. I could talk about real models in interviews, not just theory. Got a 2x salary jump."
Pooja Lodha
Data Analyst → Data Scientist
"The deep learning and LLM modules are genuinely current. Building a RAG chatbot as my capstone got me shortlisted everywhere."
Imran Khan
ML Engineer · fintech
"I came from a non-maths background and the mentors never made me feel behind. The stats and SQL modules were gold."
Sneha R.
Business Analyst
"Ananya and Karthik teach from real production experience. The MLOps module is something most courses completely skip."
Aditya Nair
AI Engineer
FAQs
Questions, answered
Do I need a maths or coding background?
No. We teach the Python and the statistics you need from scratch, at a pace beginners can follow.
Does this cover generative AI and LLMs?
Yes — a full module on NLP, transformers, prompting, RAG and building an AI-powered app on top of LLMs.
Are classes live or recorded?
Both. Live mentor-led classes with Q&A, plus lifetime recordings you can revisit anytime.
What projects will I build?
Twelve, from analytics dashboards to a CNN image classifier and a capstone RAG chatbot served via an API.
Will I get placement support?
Yes — portfolio building, Kaggle guidance, case-study & ML interview prep and hiring-partner referrals.
Is there a refund policy?
Yes, a 7-day no-questions-asked refund window so you can start risk-free.
Can I pay in instalments?
Yes, no-cost EMI from about ₹2,500/month, shown at checkout.
Not sure if this is right for you?
Talk to a counsellor, free
Tell us your goals and current skill level — our academic counsellors will tell you honestly whether this program fits, and how to make the most of it. No sales pitch.
- One-on-one session with a senior counsellor
- Course roadmap tailored to your goals
- Placement & career path clarity
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Data Science with AI · 7 months · 240 lessons. Enrol at ₹29,999 (57% off) while the offer lasts.
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₹29,999 ₹69,999
57% off · EMI from ₹2,500/mo