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Big Data for Beginners 2026|Spark, Hadoop, kafka and more

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  • 2,980 Students
  • Updated 3/2026
4.4
(348 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
22 Hour(s) 26 Minute(s)
Language
English
Taught by
Deesa Technologies
Rating
4.4
(348 Ratings)
1 views

Course Overview

Big Data for Beginners 2026|Spark, Hadoop, kafka and more

Start your Big Data career from scratch. Build pipelines using Spark, Hadoop, Kafka, and more - no experience needed

Big Data feels overwhelming for most beginners.

You learn Spark… then Hadoop… then Kafka…
But no one shows you how everything actually fits together.

That’s why many learners struggle to build real-world systems — even after completing multiple courses.

This course is different.

Instead of just teaching tools, this course teaches you how to think like a Big Data engineer.

You won’t just run commands — you’ll understand:

  • Why each technology exists

  • When to use it

  • How everything connects into a real production system

Learn by building real systems

This is a complete, end-to-end learning path where you will:

  • Start from fundamentals (even if you’re a beginner)

  • Gradually move into real-world use cases

  • Build batch and streaming pipelines

  • Work with multiple tools together (not in isolation)

  • Learn debugging, performance tuning, and production concepts

By the end of this course, you will be able to design, build, debug, and optimize Big Data pipelines with confidence.

What you’ll achieve

  • Understand how modern Big Data platforms are designed

  • Build end-to-end pipelines using real industry tools

  • Work with distributed systems from the ground up

  • Handle both batch and real-time data processing

  • Move data between databases and big data systems

  • Write production-ready, scalable code

  • Deploy applications and understand real-world environments

  • Debug failures and optimize performance effectively

  • Prepare for Big Data/Data Engineering interviews

Why this course stands out

  • Focus on understanding, not memorizing commands

  • Covers the complete lifecycle: development → debugging → deployment

  • Teaches real-world decision-making, not just theory

  • Includes troubleshooting and performance tuning (missing in most courses)

What students are saying

“Everything worked perfectly — installations, files, and explanations were clear and easy to follow.”

“Excellent course with detailed explanations. One of the best for Data Engineering concepts.”

“Comprehensive learning from zero — highly recommended for beginners.”

“Great course for beginners!”

Course Content

  • 18 section(s)
  • 214 lecture(s)
  • Section 1 Introduction to the course
  • Section 2 Introduction to the Big Data World
  • Section 3 Setting up Cluster and doing hands on with Hadoop
  • Section 4 Sqoop
  • Section 5 Hive
  • Section 6 Installation for Spark and Scala
  • Section 7 Let's learn Scala
  • Section 8 Introduction to Spark
  • Section 9 Spark RDDs
  • Section 10 Spark DataFrames
  • Section 11 Spark Advance
  • Section 12 Productionalizing your Code
  • Section 13 Complex Data Processing
  • Section 14 NOSQL Databases
  • Section 15 Apache NIFI
  • Section 16 Working with Streaming Data
  • Section 17 Extra
  • Section 18 Section 18: Spark Interview Questions and Answers

What You’ll Learn

  • Understand how the Big Data ecosystem fits together (not just individual tools), Build real-world Big Data pipelines using Spark, Hadoop, Kafka, and Hive, Process and analyze large-scale datasets efficiently using industry practices, Work with both batch and real-time (streaming) data systems, Move data between databases and distributed systems (MySQL to HDFS), Design and choose the right storage formats and architectures for different use cases, Write production-ready code and deploy applications to real environments, Use Spark (beginner → advanced) for scalable data processing, Learn Scala from scratch and apply it in Big Data workflows, Integrate tools like Kafka, Cassandra, HBase, and NiFi into complete pipelines, Debug failures and optimize performance like a real Big Data engineer, Work with complex data structures and handle real-world scenarios, Gain a clear understanding of end-to-end data engineering workflows, Prepare for Big Data interviews (Spark, Hadoop, Hive, Scala)


Reviews

  • T
    Thilagam S
    3.5

    good

  • S
    Sharon Wanjala
    4.5

    amazing

  • P
    Pronab Howlader
    4.5

    very good ,and informative learning

  • S
    Sivakumar
    5.0

    good

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