MS Word 기본 교육 과정

**Course Title: Introduction to Big Data and Hadoop****Course Duration:** 40 hours**Course Description:**This course provides an in-depth overview of big data concepts and the Hadoop ecosystem. Participants will gain hands-on experience with Hadoop tools and frameworks, enabling them to process and analyze large datasets efficiently.**Course Outline:****Module 1: Introduction to Big Data**- Understanding Big Data - Definition and characteristics - Importance of Big Data in today's world - Examples of Big Data use cases- Big Data Challenges - Volume, Velocity, Variety, Veracity - Traditional vs. Big Data processing- Big Data Technologies - Overview of Hadoop, Spark, and other tools - Big Data ecosystem components**Module 2: Introduction to Hadoop**- What is Hadoop? - History and evolution - Core components: HDFS, MapReduce, YARN- Hadoop Architecture - Cluster setup and configuration - Data storage and processing workflows- Setting Up Hadoop - Installation on Linux and Windows - Configuration files and settings**Module 3: Hadoop Distributed File System (HDFS)**- Introduction to HDFS - Architecture and components - Data replication and fault tolerance- HDFS Operations - File operations: read, write, delete - Directory operations: create, delete, list- HDFS Best Practices - Data organization and management - Performance tuning and optimization**Module 4: MapReduce Programming**- Introduction to MapReduce - Concepts and workflow - MapReduce programming model- Writing MapReduce Programs - Setting up the development environment - Writing and running MapReduce jobs- MapReduce Examples - Word count example - Custom MapReduce programs**Module 5: Advanced Hadoop Ecosystem**- Apache Hive - Introduction and architecture - Querying data with HiveQL- Apache Pig - Introduction and architecture - Data processing with Pig Latin- Apache HBase - Introduction and architecture - NoSQL database concepts- Apache Zookeeper - Introduction and architecture - Coordination and management services- Apache Sqoop - Introduction and architecture - Data import/export between Hadoop and relational databases- Apache Flume - Introduction and architecture - Data ingestion and streaming**Module 6: Hadoop Administration**- Hadoop Cluster Management - Cluster setup and configuration - Monitoring and maintenance- Security in Hadoop - Authentication and authorization - Data encryption and security best practices- Performance Tuning - Optimizing Hadoop performance - Troubleshooting common issues**Module 7: Real-world Use Cases and Projects**- Case Studies - Real-world applications of Big Data and Hadoop - Success stories and best practices- Hands-on Projects - Designing and implementing Big Data solutions - Working on real-world datasets**Assessment and Certification:**- Participants will be assessed through quizzes, assignments, and a final project.- Upon successful completion, participants will receive a certificate of achievement.

Marcin - Instytut Energetyki- Panstwowy Instytut Badawczy

Course - MS Word - poziom podstawowy

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