Big Data & Spark Boot Camp

About Course

Course Overview

This course is designed to provide in-depth knowledge of Big Data technologies, including Hadoop, Spark, NoSQL databases, and more. It prepares learners to work effectively with large datasets, leveraging tools and technologies used in industry for processing, querying, and analyzing Big Data.

Course Duration:

The course spans 8 modules, with each module designed to take 2-3 weeks of study and practical exercises, for a total of 16-24 weeks.

What Will You Learn?

Master Java essentials for Big Data tools like Hadoop and Spark.
Gain hands-on experience with Hadoop, Spark, and NoSQL databases like HBase, Cassandra, and MongoDB.
Learn to create and manage data pipelines, perform real-time data processing, and integrate cloud platforms for Big Data solutions.
Complete a capstone project to apply your knowledge in real-world scenarios.

Material Includes

Lecture notes and presentations.
Sample code and hands-on exercises.
Access to Big Data tools for practical learning.
Capstone project resources for hands-on experience.

Course Curriculum

Module 1: Java Essentials

Learn the foundational Java programming skills needed for working with Big Data technologies like Hadoop and Spark. Topics include Java architecture, OOP concepts, collections, exception handling, multithreading, I/O, and JDBC.

Module 2: SQL (Structured Query Language)

Module 3: Linux Essentials

Module 4: Big Data Hadoop

Module 5: Apache Spark

Module 6: NoSQL Databases

Module 7: Advanced Topics in Big Data

Module 8: Capstone Project

Your Instructors

kodestree

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Big Data & Spark Boot Camp

kodestree

Bootcamp Courses

February 23, 2025

About Course

What Will You Learn?

Material Includes

Course Curriculum

Module 1: Java Essentials

Learn the foundational Java programming skills needed for working with Big Data technologies like Hadoop and Spark. Topics include Java architecture, OOP concepts, collections, exception handling, multithreading, I/O, and JDBC.

Module 2: SQL (Structured Query Language)

Master SQL for efficient data querying, manipulation, and optimization in relational databases. Topics cover database design, basic and advanced SQL queries, indexing, performance tuning, and transaction management.

Module 3: Linux Essentials

Understand the basics of working in Linux-based environments, a key skill for managing Big Data systems. Learn shell commands, file management, process management, system monitoring, and troubleshooting.

Module 4: Big Data Hadoop

Explore the core components of the Hadoop ecosystem, including HDFS and MapReduce. Topics include Hadoop architecture, ecosystem tools like Hive, Pig, and HBase, and data ingestion with Sqoop and Flume.

Module 5: Apache Spark

Dive into Apache Spark, the next-generation data processing engine. Learn Spark architecture, RDDs, DataFrames, Spark Streaming, and MLlib for machine learning applications.

Module 6: NoSQL Databases

Understand the advantages of NoSQL databases in Big Data environments. Learn about HBase, Cassandra, and MongoDB, including their architecture, CRUD operations, and integration with Big Data technologies.

Module 7: Advanced Topics in Big Data

Master advanced Big Data concepts including data pipelines, real-time processing with Kafka, and cloud integration. Topics include end-to-end data pipelines, Kafka for streaming, and cloud platforms like AWS, Azure, and Google Cloud.

Module 8: Capstone Project

Apply all the skills learned throughout the course in a real-world project. Build an end-to-end data processing pipeline using Hadoop/Spark, implement machine learning models, and deploy the solution.

Your Instructors

kodestree

This course includes:

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Contact Us

Contact US

Follow Us

Big Data & Spark Boot Camp

February 23, 2025

About Course

What Will You Learn?

Material Includes

Course Curriculum

Module 1: Java Essentials

Learn the foundational Java programming skills needed for working with Big Data technologies like Hadoop and Spark. Topics include Java architecture, OOP concepts, collections, exception handling, multithreading, I/O, and JDBC.

Module 2: SQL (Structured Query Language)

Master SQL for efficient data querying, manipulation, and optimization in relational databases. Topics cover database design, basic and advanced SQL queries, indexing, performance tuning, and transaction management.

Module 3: Linux Essentials

Understand the basics of working in Linux-based environments, a key skill for managing Big Data systems. Learn shell commands, file management, process management, system monitoring, and troubleshooting.

Module 4: Big Data Hadoop

Explore the core components of the Hadoop ecosystem, including HDFS and MapReduce. Topics include Hadoop architecture, ecosystem tools like Hive, Pig, and HBase, and data ingestion with Sqoop and Flume.

Module 5: Apache Spark

Dive into Apache Spark, the next-generation data processing engine. Learn Spark architecture, RDDs, DataFrames, Spark Streaming, and MLlib for machine learning applications.

Module 6: NoSQL Databases

Understand the advantages of NoSQL databases in Big Data environments. Learn about HBase, Cassandra, and MongoDB, including their architecture, CRUD operations, and integration with Big Data technologies.

Module 7: Advanced Topics in Big Data

Master advanced Big Data concepts including data pipelines, real-time processing with Kafka, and cloud integration. Topics include end-to-end data pipelines, Kafka for streaming, and cloud platforms like AWS, Azure, and Google Cloud.

Module 8: Capstone Project

Apply all the skills learned throughout the course in a real-world project. Build an end-to-end data processing pipeline using Hadoop/Spark, implement machine learning models, and deploy the solution.

Your Instructors

kodestree

This course includes:

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