Hadoop and Spark for Big Data Course

Course Cover

Register for this course

We are proud to offer this course in a variety of training formats to suit your needs. We use the highest quality learning facilities to make sure your experience is as comfortable as possible. Our face to face calendar allows you to choose any classroom course of your choice to be delivered at any venue of your choice - offering you the ultimate in convenience and value for money.

June 2024

Code Date Duration Mode Fee Action
HSD001 17 Jun 2024 - 28 Jun 2024 10 days Half-day KES 120,000 | USD 1,398 Register
I Want To See More Dates...

June 2024

Code Date Duration Mode Fee Action
HSD001 17 Jun 2024 - 28 Jun 2024 10 days Half-day KES 120,000 | USD 1,398 Register
I Want To See More Dates...


Welcome to the world of Big Data processing with Hadoop and Spark! In today's data-driven era, organizations across industries are grappling with the challenges posed by the ever-increasing volume, variety, and velocity of data. Traditional data processing systems are often inadequate to handle the scale and complexity of modern datasets. This is where Hadoop and Spark come into play.

Hadoop and Spark are two powerful frameworks designed to address the challenges of processing and analyzing large-scale datasets in a distributed and fault-tolerant manner. By leveraging these frameworks, organizations can unlock valuable insights from their data, enabling informed decision-making and driving innovation.


10 Days

Who Should Take This Course:

This course is ideal for data engineers, data scientists, software developers, and anyone interested in mastering the art of Big Data processing with Hadoop and Spark. Whether you're looking to enhance your skills or embark on a new career path, this course will provide you with the tools and knowledge needed to succeed in the fast-paced world of Big Data analytics.

Course Level:
  • Fundamentals of Big Data: Understand the key concepts and challenges of Big Data processing.
  • Introduction to Hadoop: Explore the Apache Hadoop ecosystem, including HDFS and MapReduce, for distributed data storage and processing.
  • Working with Spark: Dive into Apache Spark, learning about its architecture, RDDs, DataFrames, and advanced features.
  • Data Processing with Spark: Master Spark's powerful APIs for data manipulation, transformation, and analysis.
  • Integrating Hadoop and Spark: Learn how to leverage Hadoop's ecosystem tools (Hive, HBase) with Spark for seamless data processing.
  • Performance Optimization: Discover techniques for optimizing performance and scalability in Hadoop and Spark environments.
  • Real-world Applications: Explore real-world use cases and case studies demonstrating the practical applications of Hadoop and Spark across industries.
  • Future Trends: Stay abreast of the latest trends and emerging technologies in the field of Big Data analytics.

Module 1: Introduction to Big Data and Distributed Computing

  • Overview of Big Data concepts
  • Introduction to distributed computing
  • Understanding the need for frameworks like Hadoop and Spark

Module 2: Fundamentals of Hadoop

  • Introduction to Apache Hadoop ecosystem
  • Hadoop Distributed File System (HDFS)
  • MapReduce paradigm for parallel processing
  • Hadoop ecosystem components: YARN, HBase, Hive, etc.

Module 3: Working with Hadoop

  • Setting up a Hadoop cluster (local or distributed)
  • Hands-on exercises with Hadoop streaming and MapReduce jobs
  • Data ingestion and storage strategies in Hadoop

Module 4: Introduction to Spark

  • Overview of Apache Spark framework
  • Key features and advantages of Spark over Hadoop
  • Spark architecture: RDDs, DAGs, and execution model

Module 5: Spark Programming Fundamentals

  • Working with Spark using Scala or Python
  • Understanding Spark Context and SparkSession
  • Basic transformations and actions in Spark RDDs

Module 6: Data Processing with Spark

  • Exploring Spark's DataFrame API
  • Data manipulation and transformation using Spark DataFrames
  • Introduction to Spark SQL for querying structured data

Module 7: Advanced Spark Concepts

  • Introduction to Spark Streaming for real-time data processing
  • Machine learning with Spark MLlib
  • Graph processing with Spark GraphX

Module 8: Integrating Hadoop and Spark

  • Leveraging HDFS for data storage in Spark
  • Running Spark on YARN for resource management
  • Interacting with Hadoop ecosystem tools from Spark (e.g., Hive, HBase)

Module 9: Performance Optimization and Scalability

  • Techniques for optimizing performance in Hadoop and Spark
  • Scaling Hadoop and Spark clusters for large-scale data processing
  • Monitoring and tuning Spark applications for efficiency

Related Courses

Course Administration Details:


The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.


Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).


The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.


Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected]/[email protected]

Mob: +254 715 077 817/+250789621067


This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817/+250789621067

Mob: +254 792516000+254 792516010 , +250 789621067 ,or mail [email protected]/[email protected]


Payment should be transferred to IRES account through bank on or before start of the course.

Send proof of payment to [email protected]/[email protected]

Share this course:

Related Courses

People who took this course also viewed: