// Curriculum Highlights
What You'll Learn
Python FundamentalsVariables, loops, functions, OOP — the right way
NumPy & ArraysVectorised operations, broadcasting, linear algebra basics
Pandas for Data WranglingDataFrames, merging, groupby, cleaning messy datasets
Data VisualisationMatplotlib, Seaborn — charts that tell real stories
Exploratory Data AnalysisEDA workflow, outlier detection, feature understanding
Scikit-learn IntroYour first ML model — linear regression end-to-end
Working with Real DatasetsKaggle datasets, APIs, CSV/JSON/SQL ingestion
Dev Environment SetupJupyter, VS Code, Git, virtual environments, Colab
// After This Course
Career Outcomes
ML Engineer (Junior)
Foundation for all ML roles. Every ML job description starts with Python proficiency.
Data Analyst
Pandas + visualisation skills map directly to analyst roles at startups and enterprises.
Research Intern
University labs and AI research teams seek students who can prototype fast in Python.
AI Startup Contributor
Enough Python to contribute to real AI products from day one at early-stage startups.
// This course is for
🎓 B.Tech students in CSE, ECE, IT (2nd year onwards)
💼 Working professionals switching into data / AI roles
🔧 Non-IT professionals who want a career in AI
❌ Not for: those who already know Python & Pandas well
// Week by Week
Full Curriculum
- Setting up Python, Jupyter Notebook, VS Code & Git
- Data types: strings, lists, tuples, dicts, sets
- Control flow: if/else, for/while loops
- Functions, lambda, map/filter/zip
- File I/O: reading CSVs, JSON, text files
- OOP basics: classes, objects, inheritance
- NumPy arrays, shapes, broadcasting, vectorised ops
- Creating & importing DataFrames
- Indexing, slicing, boolean masking
- Handling missing data — fillna, dropna, imputation
- GroupBy, pivot tables, merging & joining
- String operations & datetime handling
- Matplotlib: line, bar, scatter, histogram, heatmap
- Seaborn: pairplot, boxplot, violinplot, correlation
- Plotly interactive charts
- EDA workflow on a real-world Kaggle dataset
- Outlier detection & distribution analysis
- Communicating insights with charts
- ML pipeline: train/test split, feature scaling
- Linear & Logistic Regression with Scikit-learn
- Model evaluation: accuracy, precision, recall, F1
- Cross-validation basics
- Capstone: End-to-end prediction project
- Code review, portfolio submission, badge issuance
// Hands-on Work
3 Real Projects
PROJECT 01
IPL Match Outcome Predictor
Clean and analyse 10 years of IPL data, engineer features, and build a logistic regression model to predict match results.
PROJECT 02
Zomato Restaurant EDA
Explore restaurant ratings, cuisine trends, and pricing across Indian cities. Build a full EDA report with visual storytelling.
PROJECT 03 — CAPSTONE
House Price Prediction — End-to-End
Full pipeline from raw data ingestion to a deployed prediction function. Includes data cleaning, feature engineering, model training, evaluation, and a Jupyter report suitable for portfolio use.
// Your Credential
Bronze Certificate Awarded
🥉
Newton JEE Bronze Badge
AI Foundations — Python & Data Science
Appears on your LinkedIn profile
How LinkedIn Badging Works
Upon successful completion of all projects and sessions, you receive a verifiable digital certificate that links directly to your LinkedIn profile under "Licenses & Certifications."
1
Complete all 4 weeks & submit 3 projects2
Mentor reviews and approves your capstone3
Receive credential link via email within 48hrs4
One-click add to your LinkedIn profile5
Recruiters can verify authenticity via the link// Your Mentor
Meet Your Instructor
RV
Ravi Varma
Senior Data Scientist · Ex-Flipkart & Ola
7 years in production ML systems at Flipkart's pricing team and Ola's demand forecasting. Ravi has taught Python to 600+ students and believes the biggest mistake beginners make is learning Python in isolation — which is why every session here is built around real data problems from Indian companies.
// Upcoming Batches
Pick Your Batch
Batch #12
Mar 8, 2025
Sat & Sun · 10:00–12:00 PM IST
4 seats left
Batch #13
Mar 22, 2025
Sat & Sun · 2:00–4:00 PM IST
11 seats open
Batch #14
Apr 5, 2025
Sat & Sun · 10:00–12:00 PM IST
15 seats open
// Ready to Start?
Enrol in This Course
₹4,999
₹8,000
Save ₹3,001 · 38% OFF
or ₹417/month · 12-month no-cost EMI via Razorpay
🔒 Secured by Razorpay · 100% refund after 2 sessions if unsatisfied
Everything included
✓ 12 live sessions (2hrs each) · 24 hrs total
✓ Lifetime recording access
✓ 3 real-world projects with mentor review
✓ LinkedIn-verified Bronze badge
✓ Mentor office hours (1hr/week)
✓ Private WhatsApp batch group
✓ Resume & LinkedIn profile review
✓ Placement referral support
// Alumni Feedback
What Students Say
★★★★★
I had tried learning Python from YouTube for 6 months and always got stuck. Ravi's approach of teaching through actual IPL and Zomato data made everything click. Completed in 4 weeks and already applying to internships.
AK
Aditya Kulkarni
B.Tech CSE · VIT Vellore
★★★★★
The batch size of 15 is real — my questions never got ignored. By week 3 I was writing Pandas code confidently. The capstone project went straight into my resume and my interviewer asked me about it.
SM
Shreya Menon
Mech Engg → Data Analyst · TCS
★★★★★
Best ₹5k I've ever spent on learning. The Discord group is still active months after the course and seniors help you even with interview questions. The LinkedIn badge legitimately got me recruiter DMs.
PG
Prashant Gupta
B.Tech IT → ML Intern · Sarvam AI
★★★★☆
Pace is fast in week 1 if you're a true beginner but the recordings saved me — I watched sessions twice. By week 2 it all made sense. The EDA project was genuinely fun. Would recommend anyone pivot into data roles.
DK
Divya Krishnan
Civil Engg → Data Analyst · Razorpay
// What's Next
Students Also Take