Softlogic is one of the Top Training institutes for Hadoop. Learn how to use Hadoop, from beginner basics to advanced techniques. Our Hadoop Syllabus covers the Hadoop architecture, HDFS, MapReduce, data ingestion, and ecosystem tools like Hive, Pig, Sqoop, Flume, and HBase. We offer a Hadoop Course with Placement Assistance, Mock interviews, Resume building, and certification.
Hadoop Certification Course
DURATION
1 Month
EMI
0% Interest
Mode
Live Online / Offline
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Course Syllabus
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Fees, Duration & Batch Timings for Hadoop
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2026
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
July 2026
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
Save up to 20% in your Course Fee on our Job Seeker Course Series
Syllabus of Hadoop
Introduction to Hadoop
- Hadoop Distributed File System
- Hadoop Architecture
- MapReduce & HDFS
Hadoop Eco Systems
- Introduction to Pig
- Introduction to Hive
- Introduction to HBase
- Other eco system Map
Hadoop Developer
- Moving the Data into Hadoop
- Moving The Data out from Hadoop
- Reading and Writing the files in HDFS using java program
- The Hadoop Java API for MapReduce
- Mapper Class
- Reducer Class
- Driver Class
- Writing Basic MapReduce Program In java
- Understanding the MapReduce Internal Components
- Hbase MapReduce Program
- Hive Overview
- Working with Hive
- Pig Overview
- Working with Pig
- Sqoop Overview
- Moving the Data from RDBMS to Hadoop
- Moving the Data from RDBMS to Hbase
- Moving the Data from RDBMS to Hive
- Flume Overview
- Moving The Data from Web server Into Hadoop
- Real Time Example in Hadoop
- Apache Log viewer Analysis
- Market Basket Algorithms
Big Data Overview
- Introduction In Hadoop and Hadoop Related Eco System.
- Choosing Hardware For Hadoop Cluster nodes
- Apache Hadoop Installation
- Standalone Mode
- Pseudo Distributed Mode
- Fully Distributed Mode
- Installing Hadoop Eco System and Integrate With Hadoop
- Zookeeper Installation
- Hbase Installation
- Hive Installation
- Pig Installation
- Sqoop Installation
- Installing Mahout
- Horton Works Installation
- Cloudera Installation
- Hadoop Commands usage
- Import the data in HDFS
- Sample Hadoop Examples (Word count program and Population problem)
- Monitoring The Hadoop Cluster
- Monitoring Hadoop Cluster with Ganglia
- Monitoring Hadoop Cluster with Nagios
- Monitoring Hadoop Cluster with JMX
- Hadoop Configuration management Tool
- Hadoop Benchmarking
Objectives of Hadoop
The Hadoop Training will cover all the topics ranging from fundamental to advanced concepts, which will make it easy for students to grasp Hadoop. The Hadoop Course Curriculum is composed of some of the most useful and rare concepts that will surely give students a complete understanding of Hadoop as well. So, some of those curriculum are discussed below as objectives:
- To make students well-versed fundamental concepts of Hadoop like – Hadoop Distributed File System, Hadoop Architecture, Introduction to Pig, Introduction to Hive etc.
- To make students more aware of Hadoop by making them explore concepts like – Introduction to HBase, Other ecosystem Map, Hive Overview, Working with Hive, Pig Overview etc.
- To make students knowledgeable of advanced concepts in Hadoop like – Apache Log viewer Analysis, Market Basket Algorithms, Cloudera Installation, Hadoop Commands usage, Import the data in HDFS etc.
Why Softlogic Systems is the Best Choice for Hadoop – Learn, Practice, and Get Placed!
Online & Offline Training Options
Learn from 100+ Real-Time Developers
Hands-on Projects & Codeathons
0% EMI Fee Options
Resume & Interview Support
Placement with Top IT Firms
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No Backdoor Jobs
Highlights of Hadoop
What is Hadoop?
Hadoop is an open-source platform designed for the distributed storage and processing of extensive datasets across clusters of computers. It scales efficiently and handles big data by dividing tasks into manageable chunks processed in parallel. Key components include HDFS for storage, MapReduce for data processing, and YARN for resource management, supported by a rich ecosystem of tools.
What is Hadoop Full Stack?
The Hadoop Full Stack includes a range of tools and technologies for handling big data within the Hadoop ecosystem. It covers components for data storage (HDFS), processing (MapReduce, Spark), querying (Hive, Pig), storage access (HBase), ingestion (Flume, Sqoop), resource management (YARN), security (Ranger), visualization (Zeppelin), workflow management (Oozie), and monitoring (Ambari, Cloudera Manager), enabling comprehensive big data management.
What are the reasons for learning Hadoop?
The following are the reasons for learning Hadoop:
- Scalability: Hadoop efficiently handles and processes massive datasets across distributed clusters, making it well-suited for big data challenges.
- Budget-Friendly Infrastructure: Utilizing commodity hardware and open-source software, Hadoop significantly lowers the cost of data storage and processing compared to traditional systems.
- Parallel Computing: Hadoop’s MapReduce framework facilitates the parallel processing of large datasets, enabling quicker computation and analysis.
- Diverse Data Types: Hadoop supports various formats, including structured, semi-structured, and unstructured data, making it adaptable to different data sources.
What are the prerequisites for learning Hadoop?
The following are the prerequisites for learning Hadoop, but they are not mandatory:
- Languages: Proficiency in programming languages such as Java, Python, or Scala is useful, as these languages are frequently employed in Hadoop and its related tools.
- SQL and Relational Databases: Understanding SQL and experience with relational databases will aid in comprehending data storage and querying within Hadoop.
- Data Structures and Algorithms: Knowledge of basic data structures and algorithms is crucial for understanding how Hadoop manages and processes data.
- Command Line Skills: Basic skills in Linux/Unix command-line operations are essential, as Hadoop is typically deployed on Linux-based systems.
What are the course fees and duration?
Our Hadoop Course Fees may vary depending on the specific course program you choose (basic / intermediate / full stack), course duration, and course format (remote or in-person). On an average the Hadoop Course Fees range from 25k to 30k, for a duration of 1 month total with international certification.
What are some of the jobs related to Hadoop?
The following are the jobs related to Hadoop:
- Data Engineer
- Data Scientist
- Big Data Developer
- Hadoop Developer
- Hadoop Administrator
- Data Architect
- Business Intelligence (BI) Analyst
List a few real time Hadoop applications.
The following are the real-time Hadoop applications:
- Fraud Detection
- Real-time Analytics for e-commerce
- Social Media Monitoring
- Internet of Things
- Real time Ad Targeting
- Network Security and Monitoring
Boost Your Skills with Our Hadoop Experts
Our Mentors are from Top Companies like:
- Our trainers are seasoned professionals with over 8 years of experience in the IT industry and hold certifications in Hadoop.
- They specialize in crafting Big Data and Hadoop training solutions designed to tackle complex data analytics challenges. With a strong background in mentoring and training aspirants across various data science modules using Hadoop, they offer tailored guidance in Hadoop administration and development.
- They excel in breaking down intricate concepts into easily digestible content for a global audience and have a proven track record of delivering innovative and comprehensive teaching materials.
- Our trainers are adept at aligning learning objectives to enhance the effectiveness of Hadoop training.
- Passionate about the latest trends in Big Data and Hadoop, they help learners stay current with emerging technologies.
- They are committed to guiding beginners and enthusiasts through core technologies and cutting-edge tools, and they focus on equipping students with skills to analyze, troubleshoot, and optimize Hadoop implementations.
- Additionally, our trainers assist students in crafting tailored resumes that meet industry standards and provide expert support for interview preparation to boost placement opportunities.
- Their dedication to introducing new technologies and achieving learning goals makes them a valuable resource for aspiring Hadoop professionals.
What Modes of Training are available for Hadoop?
Offline / Classroom Training
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Training
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
Corporate Training
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
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Hands-on Project Practices in Hadoop
Healthcare Data Analysis
Real-Time Analytics Dashboard
E-commerce Data Analysis
IoT Data Processing
Customer Segmentation
Fraud Detection System
Social Media Sentiment Analysis
Recommendation Engine
Log Analysis System
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Scopes available in the future for learning Hadoop
The following are the scopes available in the future for learning Hadoop Course:
- Rising Demand for Analytics: As the volume and diversity of data increase, Hadoop expertise becomes crucial for roles in big data analytics. Companies need professionals who can analyze extensive datasets and derive actionable insights.
- Growing Need for Data Engineers: Hadoop is central to data engineering, which involves creating systems for data collection, storage, and processing. Data engineers skilled in Hadoop are in high demand for developing and maintaining data pipelines and workflows.
- Integration with Cloud Platforms: Hadoop is being integrated with major cloud services like AWS, Google Cloud, and Microsoft Azure. Familiarity with Hadoop’s cloud-based implementations (such as Amazon EMR and Google Cloud Dataproc) can lead to roles in cloud data management and architecture.
- Importance of Real-Time Processing: With the growing need for real-time data analysis, skills in Hadoop’s ecosystem tools like Apache Spark and Apache Storm are essential for roles focused on real-time analytics and processing.
- Machine Learning Capabilities: Hadoop supports various machine learning frameworks and libraries (e.g., Apache Mahout, Spark MLlib). Future roles may involve leveraging Hadoop to build and implement machine learning models and AI technologies.
- Handling IoT Data: As the Internet of Things (IoT) expands, Hadoop is increasingly used for managing and analyzing large volumes of IoT data. Professionals with Hadoop skills can engage in projects related to smart technology and industrial IoT.
- Emphasis on Data Security: With rising concerns about data breaches and regulatory compliance, expertise in Hadoop’s security tools (such as Apache Ranger and Apache Sentry) will be valuable for roles focused on data security and governance.
- Advancing BI Solutions: Hadoop integrates with business intelligence tools for detailed analytics and reporting. Understanding Hadoop can open doors to roles that enhance business intelligence and data visualization.



















