Project 1
Data cleaning and EDA
Take a messy public dataset, clean it and deliver a full exploratory analysis with visualisations.
- pandas
- EDA
- Viz
Data, AI & Cloud · Job-ready
Data Science Course with Placement Support
Turn raw data into decisions. Six months of Python, statistics, machine learning, SQL and visualisation on real datasets, ending with a portfolio of analyses and models and placement support into data roles.
Work on real, messy datasets
Build and deploy real ML models
Placement support included
Program snapshot
Admissions open- Duration
- 6 months · 240 guided hours
- Mode
- Online live or classroom, Aligarh
- Level
- Beginner to job-ready
- Schedule
- Evening & weekend batches
- Certificate
- Cyber Warrior Certified Data Scientist
- Tools
- Python, pandas, scikit-learn, SQL, Power BI
Fees from
₹49,000 incl. GST, full program
What a data science course teaches
A data science course teaches you to extract insight and predictions from data: collecting and cleaning it, analysing it with statistics, visualising it, and building machine learning models that predict outcomes. This six-month program covers Python, statistics, SQL, data wrangling, machine learning and business intelligence, all on real datasets, ending with a deployed capstone model.
240h
Guided Hours
8+
Datasets & Models
4.9/5
Rating, 153 Reviews
100%
Real-World Data
Who this data science course is for
Data science rewards curiosity and persistence more than a specific degree.
Graduates aiming for data roles
Students and graduates from engineering, science, commerce or maths who want an analytics or data science career.
Analysts wanting to level up
Business, MIS and Excel analysts who want to move into Python, machine learning and higher-paid roles.
Developers moving into ML
Programmers who want to add data science and machine learning to their skill set.
Professionals making a career switch
People from any field willing to put in project work to enter one of the highest-paid tracks in tech.
Learning outcomes
What you can do after this data science course
Outcomes are analyses and models you will produce, because the course is graded on real deliverables.
01
Clean and wrangle real data
Load, clean, merge and reshape messy datasets with pandas so they are ready to analyse.
02
Analyse and visualise
Explore data with statistics and build clear visualisations that communicate findings.
03
Apply statistics correctly
Use distributions, hypothesis testing and correlation without the common mistakes.
04
Build machine learning models
Train, evaluate and tune regression, classification and clustering models with scikit-learn.
05
Query data with SQL
Write SQL to pull and aggregate data from databases, a non-negotiable data skill.
06
Tell a data story
Build dashboards in Power BI and present insight to non-technical stakeholders.
Syllabus
Request the detailed syllabus PDF
Data science course syllabus
Nine modules over six months, all on real datasets. The final month is a deployed capstone model and presentation.
9
Modules
240
Guided hours
The Python foundation every data tool depends on, focused on data work.
- Python essentials
- Jupyter and notebooks
- NumPy arrays
- Working with files and data
- Functions and reusable code
- Virtual environments
- Reading CSV, JSON, Excel
- Intro to pandas
Module outcome: You load and manipulate a real dataset in pandas.
The 80% of data science that is cleaning and preparing data.
- Series and DataFrames
- Filtering, sorting, grouping
- Handling missing data
- Merging and joining
- Reshaping and pivoting
- Dates and time series
- Feature engineering
- Cleaning messy real data
Module outcome: You turn a messy dataset into an analysis-ready one.
The statistical foundation that separates real analysis from guessing.
- Descriptive statistics
- Distributions
- Probability basics
- Sampling and bias
- Hypothesis testing
- Confidence intervals
- Correlation vs causation
- Statistical pitfalls
Module outcome: You run and interpret a hypothesis test on real data.
Exploring data visually and communicating what you find.
- Matplotlib and Seaborn
- Choosing the right chart
- Exploratory data analysis
- Distributions and outliers
- Relationships between variables
- Dashboards intro
- Storytelling with data
- Avoiding misleading charts
Module outcome: You deliver a full EDA report on a real dataset.
Getting data out of databases, an everyday data-science task.
- Relational databases
- SELECT, WHERE, ORDER BY
- Joins
- Aggregations and GROUP BY
- Subqueries and CTEs
- Window functions
- Connecting SQL to Python
- Query optimisation basics
Module outcome: You extract and aggregate data with SQL for analysis.
Building models that predict, the heart of data science.
- Supervised vs unsupervised
- Train/test split and validation
- Linear and logistic regression
- Decision trees and random forests
- Model evaluation metrics
- Overfitting and regularisation
- Feature scaling and selection
- scikit-learn pipelines
Module outcome: You build and evaluate classification and regression models.
Better models: ensembles, clustering and getting them production-ready.
- Gradient boosting (XGBoost)
- Clustering (K-means)
- Dimensionality reduction (PCA)
- Hyperparameter tuning
- Cross-validation
- Handling imbalanced data
- Intro to neural networks
- Model interpretability
Module outcome: You tune an ensemble model and explain its predictions.
Delivering insight to a business and putting models into use.
- Power BI dashboards
- DAX basics
- KPIs and business metrics
- Deploying a model as an API
- Streamlit apps
- Model monitoring basics
- Communicating to stakeholders
- Ethics and data privacy
Module outcome: You build a dashboard and deploy a model as an app.
An end-to-end data science project plus interview and portfolio preparation.
- Capstone: full project on a real dataset
- Problem framing to deployed model
- Presentation to a panel
- Portfolio and GitHub
- Data science interview prep
- SQL and case-study practice
- Resume and LinkedIn review
- Placement pipeline onboarding
Module outcome: You deliver a deployed capstone project and presentation.
The data science toolkit
The industry-standard Python data stack plus BI, all free and set up in week one.
Core
- Python
- Jupyter
- NumPy
- pandas
Analysis & Viz
- Matplotlib
- Seaborn
- SciPy
- Statsmodels
Machine Learning
- scikit-learn
- XGBoost
- TensorFlow (intro)
Data & BI
- SQL / MySQL
- Power BI
- Excel
- Streamlit
Workflow
- Git & GitHub
- Google Colab
- Kaggle
Portfolio work
Data science projects for your portfolio
Eight real analyses and models employers can inspect on your GitHub.
Project 2
House price prediction
Build and tune a regression model to predict prices, with feature engineering and evaluation.
- Regression
- scikit-learn
Project 3
Customer churn model
Predict which customers will leave using classification, and explain the drivers to a business.
- Classification
- Interpretability
Project 4
Customer segmentation
Cluster customers into segments for targeting using unsupervised learning.
- Clustering
- PCA
Project 5
Sales dashboard in Power BI
Build an interactive business dashboard with KPIs and DAX measures.
- Power BI
- DAX
- BI
Project 6
Deployed ML app
Deploy a trained model as a Streamlit app that anyone can use in the browser.
- Streamlit
- Deploy
Project 7
SQL analytics case study
Answer business questions from a database using advanced SQL queries.
- SQL
- Analytics
Project 8
Capstone end-to-end project
A full project from problem to deployed model, presented to a review panel.
- Capstone
- ML
- Presentation
How the data science course runs
Six steps from enquiry to a deployed capstone. The first two are free.
-
1
Book a counselling call
Twenty minutes with a data professional who checks your background and confirms the fit.
-
2
Complete the readiness check
A short check on maths comfort and logic that sets your week-one foundation sessions.
-
3
Learn on real data
Every module uses real, messy datasets, not clean textbook examples.
-
4
Build models and dashboards
Graded projects every fortnight covering analysis, ML and BI.
-
5
Deploy the capstone
A full end-to-end project deployed as an app and presented to a panel.
-
6
Placement support
Case-study and SQL interview prep, portfolio review, mock interviews and referrals.
Career outcomes
Data science jobs and salaries
Data roles are among the highest-paid in Indian tech, and they hire on demonstrated projects far more than on certificates.
| Role | Typical salary (India) | What the job involves |
|---|---|---|
| Data Analyst | ₹3.5 to 8 LPA | Analyse data, build dashboards and answer business questions. A common first role. |
| Data Scientist | ₹6 to 18 LPA | Build predictive models and derive insight from data end to end. |
| Machine Learning Engineer | ₹7 to 20 LPA | Build and deploy ML models in production systems. |
| Business Intelligence Analyst | ₹4 to 10 LPA | Turn data into dashboards and reports that drive decisions. |
| Data Engineer | ₹6 to 16 LPA | Build the pipelines that move and prepare data at scale. |
| Analytics Consultant | ₹5 to 14 LPA | Solve business problems with data across client projects. |
Where graduates of this track get hired
- Analytics firms
- Product startups
- Banks & fintech
- E-commerce
- Consulting firms
- Healthcare analytics
- IT services majors
- Research teams
Salary bands are indicative for India in 2026 and rise sharply with portfolio strength and specialisation. Placement support is active help until hired, not a guarantee.
Placement support includes
- Resume, LinkedIn and GitHub portfolio review
- Mock technical and HR interviews with our engineers
- Referrals into our client and partner network
- Priority consideration for the Cyber Warrior internship
Choosing a format
Same datasets and syllabus across every format.
| Criterion | Online live | Classroom, Aligarh | Self-paced | Corporate batch |
|---|---|---|---|---|
| Live sessions per week | 3, evening or weekend | 3 at our Aligarh centre | Recorded only | Scheduled with team |
| Project review | Weekly, by a data pro | Weekly, in person | Self-submitted | Tailored |
| Doubt clearing | Saturday clinic + chat | Daily, in person | Weekly office hours | Dedicated trainer |
| Capstone review | Yes, with a panel | Yes, in person | Self-submitted | Tailored |
| Placement support | Included | Included | Add-on | Not applicable |
| Best for | Anyone in India | Aligarh students | Budget self-starters | Company teams |
| Typical duration | 6 months | 6 months | Up to 12 months access | 4 to 12 weeks |
Want to go deeper into modelling? Pair this with the AI & machine learning course.
Fees & batches
Data science course fees
One fee covering live teaching, datasets, cloud tools and placement support.
Next batches
New batches on the first Monday of every month, evening and weekend options.
Pay in instalments
Pay in 3 or 6 monthly instalments at no extra cost; the first confirms your seat.
Scholarships
Up to 25% merit scholarship based on the readiness check.
Data Science Course · full program
₹49,000incl. GST, full program
Everything included
- 240 hours of live, practitioner-led sessions
- Recordings for 12 months
- Real datasets and cloud notebooks
- Project review on every submission
- Eight portfolio analyses and models
- Deployed capstone project
- Data science interview and SQL prep
- Cyber Warrior Certified Data Scientist certificate
- Placement support until hired
Fees are indicative for the current cycle. Refunds follow our refund policy: full refund before the second live session.
Why learn data science with Cyber Warrior
We build predictive analytics and ML systems for clients. You learn the workflow that produces models people actually deploy.
Real data, not toy sets
You work with messy, real datasets, because cleaning data is most of the job.
Models that get deployed
You learn to ship a model as an app, not just score it in a notebook.
Interview-focused prep
Case studies, SQL rounds and take-homes practised in the final month.
Taught by practitioners
Instructors who build analytics and ML for real clients.
Aligarh classroom, India-wide online
In-person data days in Aligarh and live online batches nationwide.
Small batches, individual review
Capped at 25 so every model you build gets reviewed.
Programs learners pair with this one
Every track in the Cyber Warrior programs catalogue shares the same faculty and project standard, so stacking two is common.
3 months
Python Course
Python programming from first script to automation and APIs.
Explore program
5 months
AI & Machine Learning Course
Supervised, unsupervised and deep learning, deployed as APIs.
Explore program
3 months
Generative AI Course
LLMs, prompt engineering, RAG and AI agents for builders.
Explore program
4 months
AWS Cloud Computing Course
Cloud Practitioner to Solutions Architect on live AWS accounts.
Explore program
4 months
Digital Marketing Course
SEO, Google Ads, social, analytics and AI marketing tools.
Explore program
2 to 6 months
Internship Program
Paid and certificate internships on live agency projects.
Explore program
Clear answers
Data Science Course questions
The questions every applicant asks on the first counselling call.
Six months, about 240 guided hours, with three live sessions a week plus graded projects. Most learners spend 10 to 12 hours a week including project work.
The full program fee is ₹49,000 including GST, payable in 3 or 6 monthly instalments at no extra cost. It covers live teaching, datasets, cloud tools, interview prep and placement support. Merit scholarships of up to 25% are available.
No. The first module covers the Python you need for data science. If you are completely new to programming, our Python course is a gentler start, but it is not required.
No. We teach the statistics and maths you need as part of the course, focused on application rather than proofs. Comfort with school-level maths is enough.
Yes. The online live format has the same datasets, syllabus, project review and placement support as the Aligarh classroom, with recorded sessions.
Python, data wrangling with pandas, statistics, visualisation and EDA, SQL, machine learning fundamentals and advanced ML, business intelligence with Power BI and model deployment, ending with an end-to-end capstone.
Yes. You produce at least eight analyses and models plus a deployed capstone, all on GitHub. Portfolio quality is what gets data professionals hired.
Data analyst, data scientist, machine learning engineer, BI analyst and data engineer, with starting salaries in India generally between ₹3.5 and 8 LPA for analysts and much higher for data scientists, depending on portfolio and city.
Start your data science career
Book a call with a data professional. We will check your background, recommend whether to start with Python first, and tell you when the next batch begins.
Prefer WhatsApp or email? Contact the admissions team and we reply in under 3 minutes during working hours.