Why learn Big Data Fundamentals
with EduMonk?
Understand how distributed data systems store, process and govern datasets that exceed a single machine. Build a small batch-and-stream pipeline using industry-standard concepts.
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 Big Data Fundamentals 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 Big Data Fundamentals 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 Big Data Fundamentals.
Every outcome uses an observable action—something you can build, evaluate, explain or improve.
Where Big Data Fundamentals is used
Use the programme workflow to frame, build and evaluate large-scale etl.
Use the programme workflow to frame, build and evaluate event analytics.
Use the programme workflow to frame, build and evaluate data lake platforms.
Use the programme workflow to frame, build and evaluate operational monitoring pipelines.
Big Data Fundamentals 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 Big Data Fundamentals
learning plan.
A sustainable sequence that gives you time to understand, practise and produce useful work.
Enter AI foundations
Complete Introduction to Big Data and Big Data Architecture.
Build with data and ML
Complete Distributed Computing Fundamentals, Introduction to Hadoop and the Level 1 projects.
Apply modern AI
Work through Modules 5–8 and complete the applied AI projects.
Understand generative systems
Complete Working with Spark Data and Spark Transformations & Actions.
Build AI applications
Practise Spark SQL and Data Partitioning.
Integrate, evaluate & demonstrate
Complete the remaining Level 3 modules and deliver the final specialisation capstone.
Big Data Fundamentals syllabus:
28 modules, 30 hours.
This is the complete planned syllabus for the Big Data Fundamentals Certificate of Specialisation. The 28 focused modules combine concept learning, hands-on practice and completion checks across the two-month journey.
Build practical capability in introduction to big data.
01What is Big Data?Lesson
02Evolution of data systemsLesson
03Traditional data vs Big DataLesson
04Why Big Data emergedLesson
05Structured dataLesson
06Semi-structured dataLesson
07Unstructured dataLesson
08Big Data lifecycleLesson
Time includes lesson study, guided practice, checkpoint preparation and project integration. Learners may spend longer when extending project work.
Hands-on Big Data Fundamentals
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.
Large Dataset Exploration
Build, test and document a practical large dataset exploration using the skills developed in Level 1.
Distributed Word Frequency Analysis
Build, test and document a practical distributed word frequency analysis using the skills developed in Level 1.
Large-Scale E-Commerce Data Processing System
Build, test and document a practical large-scale e-commerce data processing system using the skills developed in Level 1.
Spark-Based Sales Analytics
Build, test and document a practical spark-based sales analytics using the skills developed in Level 2.
Large-Scale Customer Behaviour Analysis
Build, test and document a practical large-scale customer behaviour analysis using the skills developed in Level 2.
Big Data Retail Analytics Platform
Build, test and document a practical big data retail analytics platform using the skills developed in Level 2.
Real-Time Event Analytics Pipeline
Build, test and document a practical real-time event analytics pipeline using the skills developed in Level 3.
Cloud Data Lake Analytics System
Build, test and document a practical cloud data lake analytics system using the skills developed in Level 3.
Enterprise Big Data Analytics & Streaming Platform
Build, test and document a practical enterprise big data analytics & streaming platform using the skills developed in Level 3.
Big Data Fundamentals tools you'll work with
How the Big Data Fundamentals
course is assessed.
Your result reflects steady application across the programme—not one high-pressure exam.
Module checkpoints
28 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 Big Data Fundamentals 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
Big Data Fundamentals course?
College students
Build practical Big Data Fundamentals evidence alongside your academic work.
Working professionals
Use Big Data Fundamentals 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.
Big Data Fundamentals course prerequisites
- Basic Python or SQL
- Comfort with files and tables
- No cluster administration required
- A willingness to practise and complete the capstone
Big Data Fundamentals 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:
Big Data Fundamentals guides,
roadmaps and comparisons.
Use these editorial resources to understand where Big Data Fundamentals fits, what a sensible learning path looks like and how to turn the subject into project evidence.
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 ↗
ComparisonData · Comparison · 10 min readSQL vs NoSQLCompare SQL and NoSQL databases through structure, relationships, transactions, scale, query patterns and beginner project decisions.
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 ↗Your Big Data Fundamentals
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.
Big Data Fundamentals Certificate of Specialisation
Big Data Fundamentals 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.
Big Data Fundamentals course FAQs.
Is this specialisation beginner friendly?+
Big Data Fundamentals 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 28 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 Large Dataset Exploration and culminates in the Enterprise Big Data Analytics & Streaming 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 Big Data Fundamentals.
Which completion documents are issued?+
Learners who successfully meet the Big Data Fundamentals 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.
