Why learn Data Science
with EduMonk?
Work through the complete data-science lifecycle—from asking a testable question and cleaning data to statistical reasoning, predictive modelling and decision-ready communication.
The online syllabus follows a deliberate rhythm: learn the underlying concept, apply it in guided practice, confirm it with a checkpoint, and connect it to a project decision. By the end, you will have more than lesson completion—you will have evidence you can discuss.
Start learning for ₹1,650 today.
For the Data Science Certificate of Specialisation, pay ₹1,650 now and the remaining ₹1,500 next month. The two payments together cover the complete ₹3,150 programme fee.
Build the skills
behind your career.
Technical knowledge is only one part of becoming career-ready. Your Data Science enrolment also includes a focused professional-development journey at no additional cost.
FREE
EduMonk Career Edge
60-Day Soft Skills & Career Readiness Program
Spend approximately 20 minutes every day developing the communication, confidence, workplace and career-readiness skills that complement your technical education.
What you'll learn in Data Science.
Every outcome uses an observable action—something you can build, evaluate, explain or improve.
Where Data Science is used
Use the programme workflow to frame, build and evaluate product experimentation.
Use the programme workflow to frame, build and evaluate customer and market insight.
Use the programme workflow to frame, build and evaluate forecasting.
Use the programme workflow to frame, build and evaluate operational decision support.
Data Science skills
you'll build.
The programme develops eight connected skills and gives each one a place in the syllabus, lab work or assessment.
Your 2-month Data Science
learning plan.
A sustainable sequence that gives you time to understand, practise and produce useful work.
Enter AI foundations
Complete Introduction to Data Science and Python for Data Science.
Build with data and ML
Complete NumPy for Numerical Computing, Pandas for Data Analysis and the Level 1 projects.
Apply modern AI
Work through Modules 5–8 and complete the applied AI projects.
Understand generative systems
Complete Data Visualization and SQL for Data Science.
Build AI applications
Practise Introduction to Machine Learning and Regression.
Integrate, evaluate & demonstrate
Complete the remaining Level 3 modules and deliver the final specialisation capstone.
Data Science syllabus:
24 modules, 30 hours.
This is the complete planned syllabus for the Data Science Certificate of Specialisation. The 24 focused modules combine concept learning, hands-on practice and completion checks across the two-month journey.
Build practical capability in introduction to data science.
01What is Data Science?Lesson
02Data Science lifecycleLesson
03Data Science vs Data AnalyticsLesson
04Data Science vs Machine LearningLesson
05Role of a Data ScientistLesson
06Types of dataLesson
07Structured dataLesson
08Semi-structured dataLesson
Time includes lesson study, guided practice, checkpoint preparation and project integration. Learners may spend longer when extending project work.
Hands-on Data Science
course projects.
Build 9 practical applications across the syllabus's progressive levels. The 3 capstones ask you to combine each level's skills, evaluate the result and explain the decisions behind it.
E-Commerce Sales Analysis
Build, test and document a practical e-commerce sales analysis using the skills developed in Level 1.
Student Performance Analytics
Build, test and document a practical student performance analytics using the skills developed in Level 1.
Retail Business Performance Analysis
Build, test and document a practical retail business performance analysis using the skills developed in Level 1.
Customer Segmentation Analysis
Build, test and document a practical customer segmentation analysis using the skills developed in Level 2.
House Price Prediction
Build, test and document a practical house price prediction using the skills developed in Level 2.
Customer Churn Analytics & Prediction System
Build, test and document a practical customer churn analytics & prediction system using the skills developed in Level 2.
Sales Forecasting System
Build, test and document a practical sales forecasting system using the skills developed in Level 3.
Marketing Campaign Analytics
Build, test and document a practical marketing campaign analytics using the skills developed in Level 3.
Intelligent Business Analytics & Predictive Insights Platform
Build, test and document a practical intelligent business analytics & predictive insights platform using the skills developed in Level 3.
Data Science tools you'll work with
How the Data Science
course is assessed.
Your result reflects steady application across the programme—not one high-pressure exam.
Module checkpoints
24 focused checks confirm that core concepts and terminology are secure.
Hands-on labs
Every module includes a guided lab tied directly to the syllabus.
Level projects
Complete 6 focused Data Science builds across the three levels.
Capstone projects
Plan, build, test and explain 3 progressively more complete solutions.
Certificate eligibility
Complete all required modules, submit the assignments and capstone, and achieve at least 60% overall.
Who should take this
Data Science course?
College students
Build practical Data Science evidence alongside your academic work.
Working professionals
Use Data Science to strengthen your current role or move towards data work.
Builders & analysts
Turn concepts into a guided project, capstone and documented decisions.
Career switchers
Follow a clear starting path with no assumption of professional experience.
Data Science course prerequisites
- Basic arithmetic and percentages
- Some Python helpful but reviewed
- No statistics degree required
- A willingness to practise and complete the capstone
Data Science career paths
and applications.
This programme does not promise a job. It helps you build relevant capability and evidence for conversations around roles such as:
Data Science guides,
roadmaps and comparisons.
Use these editorial resources to understand where Data Science fits, what a sensible learning path looks like and how to turn the subject into project evidence.
ComparisonData · Comparison · 8 min readData Science vs Data AnalyticsCompare data science and data analytics by the questions they answer, the tools they use, their projects and the best entry point for beginners.
Read the guide ↗
ComparisonData · Comparison · 9 min readData Engineering vs Data ScienceCompare data engineering and data science by daily work, tools, project evidence, prerequisites and the kind of problems each field solves.
Read the guide ↗Project guideData · Project guide · 10 min readData portfolio project guideBuild a credible data portfolio project with a decision-focused question, validated data, reproducible analysis, honest evaluation and clear communication.
Read the guide ↗Salary guideData · Salary guide · 10 min readData Scientist Salary in IndiaUnderstand data scientist salary in India through a dated market snapshot, role scope, pay drivers, portfolio evidence and a practical learning roadmap—without treating an average as a promise.
Read the guide ↗Your Data Science
Certificate & LOR.
Learners who successfully meet all programme completion requirements receive an EduMonk Certificate of Specialisation and a programme-specific Letter of Recommendation. Both documents are issued as soft copies, and hard copies are dispatched by post to the learner address on record.
Data Science Certificate of Specialisation
Data Science Letter of Recommendation
About these samplesFinal documents are personalised with the completed learner's name, programme record, dates and identifiers. Sample names and details are illustrative. Please keep the postal address in your learner record accurate for hard-copy dispatch.
Data Science course FAQs.
Is this specialisation beginner friendly?+
Data Science is marked intermediate. The syllabus begins with foundations and states any useful prior knowledge clearly. Professional experience is not required.
Is this a real 30-hour syllabus?+
Yes. The programme contains 24 focused modules with concept learning, hands-on practice and knowledge checks, planned across 30 learning hours in total.
What will I build?+
You will complete 9 projects across three levels, including 3 capstones. The sequence begins with E-Commerce Sales Analysis and culminates in the Intelligent Business Analytics & Predictive Insights Platform.
How are learners assessed?+
Completion combines module checkpoints, hands-on labs, a guided project and the final capstone. A minimum overall score of 60% is required for certificate eligibility.
What support is included?+
Your enrolment includes the complete sequenced learning experience, downloadable resources, project guidance and learner support through the connected external learner portal.
Is EduMonk Career Edge included?+
Yes. This Certificate of Specialisation includes complimentary access to EduMonk Career Edge, a 60-day Soft Skills & Career Readiness Program with one focused lesson of approximately 20 minutes each day. Career Edge adds ₹0 to your ₹3,150 programme fee.
How do payment and programme access work?+
The Enrol Now button opens this specialisation’s secure Razorpay Payment Page. EduMonk does not collect card, UPI or bank credentials. After the payment is confirmed, access to this specialisation and EduMonk Career Edge is prepared manually and sent to your registered email within 4 hours.
What certificate will I receive?+
After meeting the completion requirements, you will earn a verifiable EduMonk Certificate of Specialisation in Data Science.
Which completion documents are issued?+
Learners who successfully meet the Data Science completion requirements receive a soft-copy Certificate of Specialisation and programme-specific Letter of Recommendation. Hard copies of both documents are also dispatched by post to the learner address on record.
How long can I access the programme?+
The structured learning journey lasts 2 Months. Access details, completion records and earned credentials are managed through the connected external learner portal.
