JavaScript Fundamentals: From Zero to Hero
Branch : CSE
This course provides a comprehensive introduction to Big Data and the Apache Hadoop ecosystem, empowering students with the skills to store, process, and analyze massive datasets efficiently. The course covers the fundamental concepts of distributed computing, explores the architecture of Hadoop, and introduces its core components including HDFS, MapReduce, YARN, and key ecosystem tools like Hive, Pig, Sqoop, and HBase.
Introduction to UAVs and Drone Technology
Anatomy of a Quadcopter: Frame, Motors, ESCs, Propellers, etc.
Working with Flight Controllers (e.g., KK2, APM, or Pixhawk)
Radio Communication and Remote Control Systems
Battery Management and Power Distribution
Assembling and Calibrating a Quadcopter
Basics of Drone Programming & Flight Tuning
Troubleshooting and Maintenance
Drone Safety Guidelines and DGCA (India) / FAA (U.S.) Regulations
Applications of Drones in Different Industries
Understand Big Data Concepts:
Define Big Data, its characteristics (Volume, Velocity, Variety, Veracity, Value), and its importance in modern data-driven applications.
Explain Hadoop Architecture:
Describe the core components of the Hadoop ecosystem including HDFS, YARN, and MapReduce.
Understand the master-slave architecture and the role of NameNode and DataNode.
Perform Distributed Data Storage:
Store and manage large datasets in the Hadoop Distributed File System (HDFS).
Apply replication and fault-tolerance mechanisms within HDFS.
Develop MapReduce Applications:
Write and execute MapReduce programs to perform parallel data processing on large-scale datasets.
Understand the life cycle of a MapReduce job.
Utilize Hadoop Ecosystem Tools:
Query and analyze data using Apache Hive (SQL-like interface).
Perform data transformations and scripting using Apache Pig.
Import and export data between Hadoop and RDBMS using Apache Sqoop.
Work with NoSQL-style data storage using Apache HBase.
Manage Hadoop Clusters:
Monitor and manage resources using YARN (Yet Another Resource Negotiator).
Understand cluster setup, configuration, and troubleshooting basics.
Implement Real-World Projects:
Apply Hadoop tools and techniques to real-world datasets and case studies.
Build end-to-end data processing pipelines using Hadoop ecosystem components.
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