Uncodemy Big Data Course — Everything You Need to Know

Big Data · Course Guide

AK Ankit Kaushik · Lead Trainer, Data Engineering & AI | Updated 28 August 2026 | 20 min read Free · Course Guide

The Uncodemy Big Data Course — three modules from foundations to job-ready projects.

Quick summary — Uncodemy Big Data Course

The Uncodemy Big Data Course is a hands-on programme that teaches Hadoop, Spark, Kafka, SQL, and NoSQL through real datasets. It runs for 12-16 weeks, includes 8+ live projects, and comes with placement support, resume reviews, and mock interviews.

In this guide you will learn:

What the course covers — syllabus and tools.
Duration and format — weekday and weekend batches.
Fees and what's included — transparent pricing.
Projects and placement support — how you get job-ready.
Who should join and how to decide.

SECTION 01What the course covers

The programme is structured in three modules — foundations, processing, and projects. Here's the module breakdown:

Module	Focus	Topics	Outcome
Module 1	Foundations	Linux, SQL, Python basics, Hadoop HDFS & MapReduce	Comfortable with data systems
Module 2	Processing	Apache Spark, Kafka, Hive, NoSQL databases	Build data pipelines
Module 3	Projects	Real datasets, dashboards, deployment, capstone	Portfolio-ready projects

Uncodemy Big Data Course — Syllabus:

Module 1 — Foundations (Weeks 1-4)
- Linux basics and shell scripting
- SQL and relational databases
- Python for data engineering
- Hadoop ecosystem: HDFS, MapReduce, YARN

Module 2 — Processing (Weeks 5-10)
- Apache Spark: RDDs, DataFrames, Spark SQL
- Apache Kafka: streaming and event-driven pipelines
- Apache Hive: warehouse queries
- NoSQL: MongoDB, Cassandra

Module 3 — Projects (Weeks 11-16)
- Capstone project with a real dataset
- Data pipeline end-to-end
- Dashboard and reporting
- Deployment and portfolio review

Tools Covered:
- Hadoop (HDFS, MapReduce, YARN)
- Apache Spark (PySpark, Spark SQL)
- Apache Kafka
- Apache Hive
- MongoDB & Cassandra
- Python, SQL, Linux
- Git & GitHub for version control
- Cloud basics: AWS S3, EC2

Every tool is taught with hands-on labs.

big-data-syllabus.md

Key insight: Foundations matter. If you're new to Linux or SQL, spend extra time in Module 1 — everything else builds on it.

SECTION 02Duration, format & batches

The course runs for 12-16 weeks depending on the batch. Here's a typical weekly rhythm:

Week	Focus	Hours	Format
Week 1-4	Foundations	10-12 hrs/week	Live classes + labs
Week 5-10	Processing	12-14 hrs/week	Live classes + projects
Week 11-16	Projects	15 hrs/week	Mentor-guided capstone

Weekly Routine (typical):
Mon — Live class (2 hrs) + lab
Tue — Lab work (2 hrs)
Wed — Live class (2 hrs)
Thu — Project work (2 hrs)
Fri — Doubt-clearing session (1 hr)
Sat — Mentor-guided project (3 hrs)
Sun — Review and planning (1 hr)

Total: 12-15 hrs/week

Batch Options:
- Weekday morning batch (Mon-Fri, 8 AM IST)
- Weekday evening batch (Mon-Fri, 7 PM IST)
- Weekend batch (Sat-Sun, 10 AM IST)

All batches include:
- Live instructor-led sessions
- Recordings for revision
- Weekly doubt-clearing calls
- Mentor support on Slack/WhatsApp

course-duration-format.md

Key insight: Choose a batch you can actually attend. Consistency is the single biggest predictor of completion.

SECTION 03Fees & what's included

The programme is priced transparently, with flexible payment options. Here's what's included:

Item	Included?	Details
Live classes	Yes	Instructor-led, recorded
Labs & projects	Yes	8+ live projects
Certificate	Yes	Course completion certificate
Placement support	Yes	Resume, mock interviews, referrals
Batch repeats	Yes	Unlimited repeats within a year
Fees	—	₹28,000 · EMI options available

Fee Breakdown:
Full programme fee:      ₹28,000
Early-bird discount:     ₹4,000 off (limited)
Student discount:        ₹2,000 off
EMI (3 months):          ₹9,333 / month
EMI (6 months):          ₹4,667 / month

What's included:
- 16 weeks of live instruction
- Recorded sessions for revision
- Labs and capstone project
- Certificate of completion
- Placement support and mock interviews

Payment Options:
- Full payment (one-time)
- EMI (3, 6, or 9 months)
- Razorpay / UPI / cards / net banking
- Scholarship available for students

Contact the admissions team for:
- Current offers
- EMI eligibility
- Scholarship eligibility

course-fees.md

Key insight: Fees are an investment, not an expense. Compare the skills and placement support against your target salary.

SECTION 04Projects & placement support

The course is project-driven. You'll build a portfolio that hiring managers can actually review. Here are the projects and placement support:

Project	Skills	Tools	Outcome
Log analysis pipeline	Ingestion, transformation	Kafka, Spark	Real-time processing demo
Retail data warehouse	SQL, Hive, modelling	Hive, HDFS	Analytics-ready dataset
Clickstream analytics	Spark, MongoDB	Spark, Mongo	Behaviour insights
Capstone project	End-to-end pipeline	All tools	Deployed portfolio project

Project Workflow:
1. Choose a real dataset (logs, retail, clickstream)
2. Design the pipeline (ingest → store → process)
3. Implement with Spark / Kafka / Hive
4. Document the architecture and results
5. Push to GitHub with a clear README
6. Present to mentors and get feedback

Every project includes:
- Problem statement
- Architecture diagram
- Code repo
- README with results

Placement Support:
- Resume and LinkedIn review
- Portfolio review (GitHub + projects)
- Mock interviews (2 per month)
- Referrals to hiring partners
- Interview preparation sessions
- Salary negotiation guidance

Hiring partners: 14+
Roles targeted:
- Big Data Engineer
- Data Engineer
- ETL Developer
- Analytics Engineer

projects-placement.md

Key insight: Projects are your portfolio. Clean repositories and clear READMEs are what get callbacks.

SECTION 05Who should join

This course is designed for:

Freshers — graduates who want a structured path into data engineering.
Working professionals — analysts, testers, and developers moving into Big Data roles.
Career switchers — people from non-tech backgrounds with basic computer skills.
Data analysts — who want to add Spark and streaming to their toolkit.

Pro tip: If you already know Python and SQL, you can move faster through Module 1 and focus on Spark and projects.

SECTION 06Interview Q&A — Big Data course

Q1Do I need coding experience to join?

No. The course starts with Python and SQL basics. If you have some coding experience, you'll move faster, but beginners can complete it with consistent effort.

Q2How long does the course take?

12-16 weeks, depending on your batch and pace. Most learners finish in about 14 weeks with 12-15 hours per week.

Q3Is placement guaranteed?

No course can guarantee a job. What's offered is structured placement support — resume reviews, mock interviews, referrals, and interview prep. Your results depend on your effort and market conditions.

Q4Can I pay in installments?

Yes. EMI options are available for 3, 6, or 9 months. Contact the admissions team for current offers and eligibility.

Q5Will I get a certificate?

Yes. You'll receive a course completion certificate after finishing the modules and capstone project.

SECTION 07Test yourself — Big Data course

Five questions. No sign-up.

0 / 5

Pick an answer to see why it is right or wrong.

SECTION 08Frequently asked questions

What tools are covered in the course?

Hadoop (HDFS, MapReduce), Apache Spark, Kafka, Hive, NoSQL (MongoDB, Cassandra), Python, SQL, Linux, Git, and cloud basics (AWS S3, EC2).

Is the course online or classroom?

Both. Live online sessions are available with recordings, and classroom batches are available at our Noida centre.

What if I miss a class?

Every live session is recorded. You can catch up anytime, and weekly doubt-clearing sessions help you stay on track.

Do I need my own laptop?

Yes, a laptop with at least 8 GB RAM is recommended for running Spark and Hadoop labs locally. Cloud labs are also provided where needed.

What kind of jobs can I apply for after the course?

Big Data Engineer, Data Engineer, ETL Developer, Analytics Engineer, and related roles in data teams.

What I would do in the first 30 daysLayoff · 14 min Why sending 500 resumes won't workJob Search · 14 min Rebuild your resume for the AI job marketResume · 15 min Which skills to learn before applyingSkills · 14 min 90-day career recovery roadmapRecovery · 16 min How AI can help you prepare for interviewsAI · 11 min

Classroom & online · Noida

Join the Uncodemy Big Data Course

Learn Hadoop, Spark, Kafka, and SQL through hands-on projects — with placement support, resume reviews, and mock interviews.

₹28,000 · full programme ~~₹32,000~~

Explore the course Download the syllabus

16-week programme
8+ live projects
Placement support
Weekday & weekend batches

Uncodemy Big Data Course Everything You Need to Know