Module 1: Introduction to Big Data
- Definition and Characteristics of Big Data
- Challenges and Opportunities
- Evolution of Big Data Technologies
Module 2: Basics of Hadoop
- Introduction to Hadoop Ecosystem
- Hadoop Distributed File System (HDFS)
- MapReduce Programming Model
Module 3: Hadoop Ecosystem Components
- Apache Hive for Data Warehousing
- Apache Pig for Data Flow
- Apache HBase for NoSQL Databases
- Apache Spark for In-Memory Processing
Module 4: Data Ingestion and Processing
- Apache Flume for Log Collection
- Apache Sqoop for Data Import/Export
- Real-time Data Processing with Apache Kafka
Module 5: Hadoop Cluster Management
- Setting Up and Configuring a Hadoop Cluster
- Cluster Monitoring and Maintenance
- High Availability and Fault Tolerance
Module 6: Advanced Hadoop Concepts
- YARN (Yet Another Resource Negotiator)
- Hadoop Security and Authorization
- Hadoop Performance Tuning
Module 7: Introduction to Big Data Analytics
- Overview of Big Data Analytics
- Batch and Real-time Processing
- Use Cases and Applications
Module 8: Machine Learning with Big Data
- Introduction to MLlib (Machine Learning Library)
- Building and Evaluating Machine Learning Models
- Integrating Machine Learning with Hadoop
Module 9: Big Data in the Cloud
- Cloud Computing Basics
- Big Data Solutions on Cloud Platforms (AWS, Azure, GCP)
Module 10: NoSQL Databases
- Introduction to NoSQL Databases
- Types of NoSQL Databases (e.g., MongoDB, Cassandra)
- Integrating NoSQL with Hadoop
Module 11: Big Data Security and Governance
- Security Challenges in Big Data
- Implementing Security Measures
- Data Governance and Compliance
Module 12: Real-world Big Data Projects
- Case Studies and Project Examples
- Hands-on Project Work
Module 13: Future Trends in Big Data
- Emerging Technologies (e.g., Apache Flink, Apache Beam)
- Industry Trends and Innovations
Module 14: Tools and Development Environment
- Setting Up a Hadoop Development Environment
- Using Development Tools (e.g., Apache Zeppelin, Jupyter)
Module 15: Career Development in Big Data
- Job Roles in Big Data
- Building a Career Path
- Networking and Professional Development
Bigdata and Hadoop Training Certification
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Bigdata and Hadoop Course Fee and Duration in Jalandhar
| Track | Regular Track | Weekend Track | Fast Track |
|---|---|---|---|
| Course Duration | 45 – 60 Days | 8 Weekends | 5 Days |
| Hours | 2 hours a day | 3 hours a day | 6+ hours a day |
| Training Mode | Live Classroom | Live Classroom | Live Classroom |