Big Data Hadoop and Spark Developer Training - $0

Bangalore, Karnataka, India


Big Data Hadoop and Spark Developer Training is designed to equip individuals with the skills needed to handle, process, and analyze large datasets using Hadoop and Spark frameworks. These frameworks are essential tools in the big data ecosystem, widely used in industry for their ability to process vast amounts of data quickly and efficiently.
Overview of Big Data Hadoop and Spark Developer Training
Key Components of the Training
Introduction to Big Data and Hadoop Ecosystem

Understanding Big Data concepts and challenges.
Overview of Hadoop and its ecosystem components: HDFS, MapReduce, YARN, and related tools (Hive, Pig, HBase, etc.).
Hadoop Distributed File System (HDFS)
HDFS architecture and components.
File storage and data replication in HDFS.
Performing basic file operations in HDFS.
MapReduce Programming
Fundamentals of the MapReduce programming model.
Writing MapReduce jobs in Java.
Understanding job scheduling and resource management.
YARN (Yet Another Resource Negotiator)
YARN architecture and its role in resource management.
Application deployment and job execution in YARN.
Apache Spark Overview:
Introduction to Apache Spark and its advantages over Hadoop MapReduce.
Spark ecosystem components: Spark SQL, Spark Streaming, MLlib, GraphX.
Spark Core and RDDs (Resilient Distributed Datasets)
Spark architecture and execution model.
Creating and manipulating RDDs.
RDD transformations and actions.
Spark SQL and DataFrames
Introduction to Spark SQL and DataFrames.
Querying structured data using Spark SQL.
Integration with Hive and other data sources.
Spark Streaming
Real-time data processing with Spark Streaming.
DStream (Discretized Stream) and window operations.
Handling streaming data from various sources (Kafka, Flume, etc.).
Machine Learning with Spark MLlib
Overview of Spark MLlib for machine learning.
Implementing common machine learning algorithms.
Building and evaluating machine learning models.
Integration with Other Big Data Tools
Using Hadoop ecosystem tools (Hive, Pig, HBase) with Spark.
Data ingestion tools like Apache Flume and Apache Kafka.
Workflow management with Apache Oozie.
Hands-on Projects and Case Studies
Real-world projects involving data ingestion, processing, and analysis using Hadoop and Spark.
Case studies to understand practical applications and industry use cases.
Benefits of the Training
Comprehensive Skill Development: Learn the complete Hadoop and Spark ecosystems, preparing you to handle large-scale data processing tasks.
Hands-on Experience: Practical exercises and projects provide hands-on experience with real-world datasets and scenarios.
Industry Relevance: Gain knowledge of tools and technologies that are widely used in the industry, enhancing job prospects.
Certification: Obtain a certification that validates your skills and knowledge, increasing your credibility with employers.
Preparation Tips
Prerequisites: Familiarity with basic programming concepts (Java, Python, or Scala), and an understanding of SQL and Linux commands.
Online Resources: Utilize online tutorials and courses to get a foundational understanding before diving into advanced topics.
Practice Coding: Regularly practice coding in Java, Python, or Scala to build familiarity with writing Hadoop and Spark applications.
Stay Updated: Follow industry blogs, participate in webinars, and join online communities to stay informed about the latest trends and updates.
Recommended Courses and Resources
Coursera: Courses like "Big Data Specialization" by the University of California San Diego, and "Hadoop Platform and Application Framework" by the University of California Irvine.
edX: Offers "Big Data with Apache Spark" by the University of California Berkeley and "Introduction to Big Data" by the University of Adelaide.
Udacity: Provides nanodegree programs such as "Data Engineer" and "Machine Learning Engineer" that include Hadoop and Spark training.
LinkedIn Learning: Courses on "Hadoop Fundamentals," "Learning Hadoop," and "Learning Spark" provide comprehensive training.
Books: Recommended books include "Hadoop: The Definitive Guide" by Tom White and "Learning Spark: Lightning-Fast Data Analytics" by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia.
By completing a Big Data Hadoop and Spark Developer Training course, you will gain the expertise needed to effectively manage and analyze big data, making you a valuable asset in the field of data engineering and analytics.