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Syllabus Guide · Big Data · 2026

Uncodemy Big Data Course Syllabus Explained in Detail

A detailed breakdown of the Big Data syllabus within Uncodemy's Data Science program — Hadoop, Spark, cloud, and a 90-day learning plan.

Tracks
Big Data Syllabus · Live Interactive
Focus
—
Monthly theme
Key Goal
—
Primary objective
Checkpoint
—
End of month outcome
Month 1 → Month 2 → Month 3 → Job Ready
Click a month to see the syllabus. Track your progress daily, weekly, and monthly to stay on course.

Home / Tutorials / Career Guides / Uncodemy Big Data Course Syllabus Explained in Detail

Syllabus Guide · Big Data · 2026

Uncodemy Big Data Course Syllabus Explained in Detail

MONTH 1 MONTH 2 MONTH 3 JOB READY Month 1 Hadoop & HDFS Days 1-30 Foundation Month 2 Spark & MapReduce Days 31-60 Build Month 3 Cloud & Projects Days 61-90 Launch Job Ready Big Data Engineer Career Ready Success
A 90-day Big Data syllabus path — Month 1: Hadoop & HDFS, Month 2: Spark & MapReduce, Month 3: Cloud & Projects.

Quick summary — Uncodemy Big Data syllabus

Big Data is a module within Uncodemy's Data Science program, covering Hadoop, Spark, and cloud services. This guide breaks down every day, week, and month of the Big Data portion — with checklists, goals, and tracking to keep you on course.

In this guide you will learn:

  1. Month 1: Hadoop & HDFS — distributed storage and processing.
  2. Month 2: Spark & MapReduce — in-memory processing and batch jobs.
  3. Month 3: Cloud & Projects — cloud services and capstone.
  4. Tracking templates — track your progress.
  5. Accountability tips — stay on track.

SECTION 01Month 1: Hadoop & HDFS (Days 1-30)

The first month is about building your Big Data foundation. Hadoop and HDFS are the bedrock of distributed data processing. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 1 Big Data Fundamentals What is Big Data, 5 Vs, ecosystem overview Understand the Big Data landscape
Week 2 HDFS NameNode, DataNode, replication, block storage Set up a single-node HDFS
Week 3 MapReduce Basics Mapper, Reducer, shuffle and sort Write a word count program
Week 4 Hive & Pig SQL-like queries, scripting Query a dataset with Hive
Month 1 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 1: Big Data fundamentals
   - Week 2: HDFS
   - Week 3: MapReduce basics
   - Week 4: Hive and Pig
12:00 PM — Lunch break
1:00 PM — Hands-on labs (Hadoop setup, HDFS commands)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read documentation (30 min)
10:00 PM — Wind down
month1-planner.md
Key insight: Month 1 is about building your foundation. Uncodemy's PG Program in Data Science covers "Big Data and Cloud Technologies" including Hadoop and Spark for large-scale data management [citation:1]. The program spans 6–12 months [citation:1], and the Big Data module is a key component of the broader Data Science curriculum.

SECTION 02Month 2: Spark & MapReduce (Days 31-60)

The second month is about Spark — the modern in-memory processing engine that replaced much of MapReduce. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 5 Spark Basics RDDs, DataFrames, lazy evaluation Run Spark locally
Week 6 Spark SQL DataFrames, SQL queries, schema inference Query a dataset with Spark SQL
Week 7 Spark Streaming DStreams, structured streaming Build a simple streaming job
Week 8 Build Project 1 End-to-end Spark pipeline Complete Project 1
Month 2 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 5: Spark basics
   - Week 6: Spark SQL
   - Week 7: Spark Streaming
   - Week 8: Project 1
12:00 PM — Lunch break
1:00 PM — Hands-on labs (Spark jobs, SQL queries)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read Spark docs (30 min)
10:00 PM — Wind down
month2-planner.md
Key insight: Month 2 is about building evidence. The Uncodemy PG Program lists Spark as a core Big Data tool [citation:1]. Spark has largely replaced MapReduce for new projects due to its speed and ease of use. Your project is the proof that you can use it.

SECTION 03Month 3: Cloud & Projects (Days 61-90)

The third month is about cloud services and completing your capstone project. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 9 Cloud Big Data Services AWS EMR, S3, Glue, Azure HDInsight Run a job on cloud
Week 10 Build Project 2 End-to-end cloud Big Data pipeline Complete Project 2
Week 11 Interview Prep Mock interviews, Hadoop/Spark concepts 10 mock interviews
Week 12 Target & Apply 5 applications daily, research companies 25 quality applications
Month 3 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 9: Cloud Big Data services
   - Week 10: Project 2
   - Week 11: Interview prep
   - Week 12: Applications and research
12:00 PM — Lunch break
1:00 PM — Networking and follow-ups
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Interview prep (30 min)
10:00 PM — Wind down
month3-planner.md
Key insight: Month 3 is about execution. Uncodemy's PG Program covers "Big Data and Cloud Technologies" together [citation:1], reflecting how modern Big Data work is done. Cloud services like AWS EMR and Azure HDInsight are where Hadoop and Spark jobs actually run in production.

SECTION 04Tracking templates

Use these templates to track your 90-day progress:

Daily Tracker:
Date: _________
☐ Morning routine completed
☐ Deep work session 1 (3 hours)
☐ Deep work session 2 (2 hours)
☐ Hands-on lab completed
☐ Project work completed
☐ Exercise completed
☐ Reviewed progress
☐ Planned tomorrow

Today's Accomplishments:
1. 
2. 
3. 

Tomorrow's Priorities:
1. 
2. 
3. 
tracking-templates.md

SECTION 05Accountability tips

Here are tips to stay accountable during your 90-day learning journey:

  • Find an accountability partner — share your weekly goals with someone who will check in.
  • Track daily wins — write down 3 wins each day, no matter how small.
  • Join a community — connect with other Big Data learners.
  • Celebrate milestones — reward yourself at 30, 60, and 90 days.
  • Review weekly — every Sunday, review your progress and plan the week ahead.
Pro tip: Consistency beats intensity. Even 2-3 hours of focused work daily is enough to complete this 90-day learning plan.

SECTION 06Interview Q&A — Uncodemy Big Data Syllabus

Q1Does Uncodemy offer a standalone Big Data course?

Based on the available information, Big Data is covered as a module within Uncodemy's PG Program in Data Science, not as a standalone course [citation:1]. The program covers "Big Data and Cloud Technologies" including Hadoop, Spark, and cloud services.

Q2What does the Big Data module cover?

The Big Data module covers Hadoop, Spark, and cloud services for large-scale data management [citation:1]. This includes distributed storage (HDFS), distributed processing (MapReduce, Spark), and querying tools (Hive, Spark SQL).

Q3How long is the full PG Program?

The PG Program in Data Science typically spans 6 to 12 months, depending on the mode of study (full-time or part-time) and your learning pace [citation:1]. The Data Science course in Kolkata runs 8–9 months with 150+ hours [citation:6].

Q4What is the fee for the Data Science program?

Fees vary by location and program. The Data Science course in Kolkata is listed at ₹21,500 + 18% GST = ₹25,370 total [citation:6]. A third-party listing mentions ₹50,000 for a 5–6 month program in Bhubaneswar [citation:8]. Confirm the exact fee for your chosen program during counselling.

Q5Is Big Data still relevant in 2026?

Yes. While the term "Big Data" has faded from hype cycles, the underlying skills — distributed processing, Spark, cloud data services — are more relevant than ever. Modern data engineering roles require these skills for handling large-scale datasets [citation:1].

SECTION 07Test yourself — Uncodemy Big Data Syllabus quiz

Five questions. No sign-up.

0 / 5

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

SECTION 08Frequently asked questions

Is Big Data a standalone course at Uncodemy?

Based on available information, Big Data is a module within the PG Program in Data Science, not a standalone course [citation:1].

What tools are covered in the Big Data module?

Hadoop, Spark, and cloud services for large-scale data management [citation:1]. This includes HDFS, MapReduce, Hive, Spark SQL, and cloud platforms.

How long does the PG Program take?

6 to 12 months, depending on full-time or part-time study [citation:1].

What is the fee?

Kolkata Data Science course: ₹21,500 + GST = ₹25,370 [citation:6]. Other locations may vary. Confirm during counselling.

Is Spark covered?

Yes. Spark is listed as a core Big Data tool in the program [citation:1].

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Explore the Uncodemy PG Program in Data Science

Our PG Program in Data Science covers Big Data, Hadoop, Spark, cloud, and more — with projects and placement support.

6–12 months · 150+ hours
  • Big Data & Cloud Technologies
  • Hadoop, Spark, and more
  • Live projects
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