Know it suits you before you pay
Talk to a mentor first — we check whether Data Science & ML matches your background, time and goal, and tell you honestly if it doesn't.
Hottest
Data Science Course — Learn Python, ML and AI by Building Real Analytics Projects
Learn Python, analytics, machine learning and AI workflows through guided projects that help you build a portfolio with substance.
See the full syllabus, fees and what you'll build before you pay a rupee. Live online classes with a personal mentor, small batches, and projects that go straight onto your portfolio.
4 Months guided project path
4.8/5 learner feedback
Roadmap and outcome fit explained
Classes in English, Hindi & Marathi
See the structure, mentor support and next steps in one clear conversation.
Choose with human context, not a generic catalogue grid. A learning advisor helps you compare your goal, current level, time comfort and project expectations before you decide.
4 Months to structured project proof
25 learner groups for feedback
4.8 learner confidence score
Know what to build before you startGet feedback before your portfolio goes publicChoose the learning mode that fits your week
Next cohort starts 27 June 2026 · only 25 seats
Small groups of 25 learners so mentors can review work properly.
INR 25,000 INR 40,000 38% OFF
- Included Applied Projects
- Included Career Context Included
- Included Kaggle Competitions
- Included Continued Learning Support
Free demo class before you pay · EMI options · 7-day money-back guarantee
Roadmap support is available from your first enquiry to live start.
Free roadmap check before you paySyllabus, pricing and live-start clarity in one callPortfolio proof you can explainMentor-reviewed project workLive online across India with optional Pune supportSmall groups for better feedbackFree roadmap check before you paySyllabus, pricing and live-start clarity in one callPortfolio proof you can explainMentor-reviewed project workLive online across India with optional Pune supportSmall groups for better feedback
Outcome-first learning path
Move from interest to useful Data Science & ML proof
SourceKode helps you decide whether this route is worth your time, then gives you a practical path to build, practise and show work with mentor feedback. The goal is not to collect another certificate. The goal is to become easier to trust, interview and hire.
Build things you can show
Every module ends in a real project for your portfolio — the thing interviewers, clients and recruiters actually ask to see.
Never get stuck alone
Small live batches mean your doubts get answered in class, and your project work gets personal feedback before it goes public.
Fees, dates and syllabus upfront
Exact fees with EMI options, the next batch date and the full syllabus — all before you commit a single rupee.
3 Months guided path to visible project proof
6 + data science projects you can discuss
25 learners per group for better feedback
1 clear pricing, roadmap and syllabus plan before payment
Available across India Join Data Science & ML live online from anywhere in India, with optional Pune support if you prefer in-person help. Ask for the syllabus, pricing plan and live-start advice before you decide.
What does the Data Science & ML course cover?
The Data Science & ML path is a 3 Months, mentor-led program covering Data Science & ML, Applied Projects, Career Context Included, Kaggle Competitions — built around 6+ data science projects you can show in interviews.
Who is the Data Science & ML course for?
It suits beginner to advanced learners — students, working professionals and career switchers who want practical proof, not just a certificate. We check fit on a free roadmap call before you pay.
What are the fees and next batch for Data Science & ML?
Fees are INR 25,000 (from INR 40,000) with EMI options and a GST invoice. Live online in small batches of 25 — ask for the next start date and the full syllabus.
Course Overview
Become a Data Scientist and unlock insights from data using Python, Machine Learning, and AI. Master data analysis, visualization, statistical modeling, and deep learning to solve real-world business problems.
Data Science learning path at SourceKode covers the complete data science pipeline from data collection to model deployment. Learn Python libraries like Pandas, NumPy, Scikit-learn, TensorFlow, and build a portfolio of industry-relevant projects.
Why Learn Data Science?
- Hottest Career: #1 job in America (Glassdoor)
- Highest Salaries: Data Scientists earn ₹8-30 LPA
- Universal Demand: Every industry needs data insights
- Future-Proof: AI/ML is the future of technology
- Problem Solving: Use data to drive business decisions
- Research Opportunities: Academia and R&D roles
- Freelance Potential: High-paying consulting projects
What You’ll Learn
- Python for Data Science: Pandas, NumPy, Matplotlib
- Statistics & Math: Probability, hypothesis testing, linear algebra
- Machine Learning: Supervised, unsupervised, ensemble methods
- Deep Learning: Neural networks, TensorFlow, Keras
- Data Visualization: Tableau, PowerBI, Seaborn
- Big Data: Spark basics, handling large datasets
- Deployment: Flask APIs, cloud deployment
Course Syllabus (100+ Hours)
Module 1: Python Programming (15 hours)
- Python basics and data structures
- NumPy for numerical computing
- Pandas for data manipulation
- Data cleaning and preparation
Module 2: Data Visualization (10 hours)
- Matplotlib and Seaborn
- Interactive plots with Plotly
- Tableau fundamentals
- PowerBI basics
- Storytelling with data
Module 3: Statistics & Mathematics (15 hours)
- Descriptive statistics
- Probability distributions
- Hypothesis testing
- Correlation and regression
- Linear algebra essentials
- Calculus basics for ML
Module 4: Machine Learning (30 hours)
- Supervised Learning:
- Linear/Logistic Regression
- Decision Trees, Random Forest
- SVM, Naive Bayes
- KNN, Gradient Boosting
- Unsupervised Learning:
- K-Means Clustering
- Hierarchical Clustering
- PCA (dimensionality reduction)
- Association Rules
- Model Evaluation:
- Train-test split, cross-validation
- Metrics: Accuracy, Precision, Recall, F1, ROC-AUC
- Confusion matrix
- Hyperparameter tuning
Module 5: Deep Learning (20 hours)
- Neural network fundamentals
- TensorFlow and Keras
- CNN for image classification
- RNN and LSTM for sequences
- Transfer learning
- Model optimization
Module 6: Natural Language Processing (8 hours)
- Text preprocessing
- Sentiment analysis
- Word embeddings (Word2Vec, GloVe)
- Text classification
Module 7: Time Series Analysis (6 hours)
- ARIMA models
- Forecasting techniques
- Seasonality and trends
Module 8: Deployment & Tools (6 hours)
- Flask API for models
- Docker basics
- Cloud deployment (AWS, Azure)
- Git and version control
- Jupyter notebooks and Google Colab
Major Projects
- Customer Churn Prediction (Classification)
- House Price Prediction (Regression)
- Image Classification (Deep Learning)
- Sentiment Analysis (NLP)
- Sales Forecasting (Time Series)
- Recommendation System (Collaborative Filtering)
Career Opportunities
Data Science offers the highest-paying tech roles:
- Data Scientist - Average: ₹8-20 LPA
- Machine Learning Engineer - Average: ₹10-25 LPA
- Data Analyst - Average: ₹5-12 LPA
- AI Engineer - Average: ₹12-30 LPA
- Research Scientist - Average: ₹15-35 LPA
Data Scientist Salary in India (2026)
| Experience | Typical Role | Salary Range (₹ / year) |
|---|---|---|
| Fresher (0–1 yr, with projects) | Data Analyst / Junior DS | ₹5,00,000 – ₹10,00,000 |
| 2–4 years | Data Scientist | ₹12,00,000 – ₹22,00,000 |
| 5–8 years | Senior DS / ML Engineer | ₹24,00,000 – ₹40,00,000 |
| 8+ years | Lead / Principal Data Scientist | ₹40,00,000 – ₹70,00,000+ |
Indicative ranges for India in 2026. Data science and ML remain among the highest-paid tech tracks; a portfolio of 5–6 real projects (plus Kaggle) is the strongest lever on a fresher offer.
Is Data Science Worth Learning in 2026?
Yes — and the rise of AI has made it more valuable, not less:
- AI runs on data: every company adopting AI needs people who can collect, clean, model and interpret data.
- High, durable pay: data science and ML consistently sit among the top-paid tech roles in India.
- Cross-industry demand: finance, healthcare, e-commerce, logistics and SaaS all hire data talent.
- Clear portfolio path: Kaggle plus 5–6 end-to-end projects make freshers hireable without a fancy degree.
Strengthen it by pairing data science with Python fundamentals, AWS Cloud for deployment, our big data Hadoop course for large-scale data engineering, or AI Tools Mastery for modern AI workflows.
Companies Hiring
- Tech Giants: Google, Microsoft, Amazon, Meta
- Indian Startups: Ola, Swiggy, Zomato, CRED
- Analytics: Mu Sigma, Fractal Analytics, Latentview
- E-commerce: Flipkart, Amazon India
- Finance: Banks, fintech companies
- Consulting: McKinsey, BCG, Deloitte
Prerequisites
- Required: Basic Python (covered in course)
- Recommended: 12th grade mathematics
- Helpful: Statistics basics (taught in course)
- Analytical mindset and problem-solving skills
Meet your mentors
Real people teach this course — and review your work
Teaches data pipelines, cloud deployment and system design.
Maps your portfolio to analyst, scientist and engineer roles.
Will this fit you?
- Language English, Hindi, Marathi
- Duration 3 Months
- Lectures 100+ Hours
- Projects 6+ Data Science Projects
- Skill level Beginner to Advanced
- Certification Yes
- Max learners 25
Plan your next step
Get pricing, start dates, project roadmap and mentor support explained before you commit.
Small groups for proper mentor feedback
Get pricing and roadmap Call SourceKode: +91 77688 68948- Project work reviewed before you showcase it
- Career, creator or business use case mapped to your goal
- Flexible start timing with pricing clarity
Mentor-led Small groups EMI support
Get fees & the next batch date
Share four quick details and we will call you with fees, the next Saturday batch date and a roadmap. No spam.
Prefer WhatsApp? Message us on WhatsApp
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Common Questions
Frequently Asked Questions
Do I need a PhD or advanced degree for Data Science?
No! While PhDs help in research roles, most Data Science jobs need strong skills, not advanced degrees. Our practical, project-based course prepares graduates/undergraduates for industry roles. Portfolio with projects matters more than degrees.
Python vs R - which is better for Data Science?
Python is more versatile, easier to learn, better for production deployment, and has more job opportunities (80%+). R is great for statistics but limited scope. We teach Python - the industry standard.
Can non-IT graduates become Data Scientists?
Absolutely! Many successful Data Scientists come from Mathematics, Statistics, Economics, Engineering backgrounds. Strong analytical thinking matters more than IT degree. We teach programming from scratch.
Is mathematics necessary for Data Science?
Basic math (12th grade) is sufficient to start. We teach required statistics, linear algebra, and calculus as part of the course. Don't let math fear stop you - we make it practical and understandable.
Data Science vs Machine Learning - what is the difference?
Data Science is broader - includes data analysis, visualization, statistics, business intelligence, and ML. Machine Learning is a subset focused on predictive models. Our course covers complete Data Science including ML and Deep Learning.
What salary can Data Scientists earn in India?
Entry-level ₹6-12 LPA. With 2-3 years experience: ₹12-20 LPA. Senior Data Scientists/ML Engineers: ₹20-35 LPA. Data Science commands the highest tech salaries after Cloud Architects.
Is Kaggle important for Data Science jobs?
Kaggle competitions build skills and portfolios. Not mandatory but highly beneficial for freshers. We guide you through Kaggle competitions and building strong GitHub portfolio with 5-6 projects - crucial for Data Science interviews.
How long does it take to become job-ready in Data Science?
Our intensive 4-month course (100+ hours) with 6 projects prepares you well. Plan additional 2-3 months for deep practice, Kaggle, interview prep. Total 6-7 months from beginner to job-ready is realistic.
Is data science still in demand in 2026, or is it saturated?
Demand is strong and growing, especially as companies adopt AI — which depends entirely on good data work. Entry-level roles are competitive, so a portfolio of real projects (and Kaggle) is what separates hired candidates from the crowd. Mid and senior data/ML roles remain well-paid and hard to fill.
Should I become a Data Scientist or an AI/ML Engineer?
They overlap. Data Scientists focus more on analysis, statistics and insight; ML/AI Engineers focus more on building and deploying models in production. This course covers the full pipeline (analysis to ML to deep learning to deployment) so you can move toward either based on what you enjoy.
Learning path check
Want to know if Data Science & ML is the right next step?
We will help you compare syllabus depth, project proof, pricing and live-start fit so you can decide with confidence.
Small groups for feedback Live online across India; optional Pune support EMI and roadmap support
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