Course Information
Course Overview
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)
Skills covered in this course
Reviews
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TThilagam S
good
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SSharon Wanjala
amazing
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PPronab Howlader
very good ,and informative learning
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SSivakumar
good