Course Content
1. Introduction To Big Data And Hadoop

•  Hadoop Installation and Hortonworks Sandbox Demo 

•  Using Hadoop on single node cluster 

•  Introduction to Hadoop Ecosystem 

•  HDFS and Map Reduce 

•  HDFS and MRv1 Architecture 

•  Introduction to YARN 

•  YARN and Resource Manager UI 

•  Working with Ambari 

•  Map Reduce word count example 

•  Integrating Python with Hadoop 

•  Working on Movies dataset 

2. Introduction to Apache PIG

•  PIG Installation and commands 

•  Working on Million songs dataset 

3. Introduction to Apache HIVE

•  HIVE Queries 

•  Working on Twitter data 

4. Introduction to Apache Spark

•  Spark Installation and Word Count example 

•  Setting up Python with Spark 

•  Spark RDD (Resilient Distributed Dataset) 

•  Introduction to Spark ML Lib (Machine Learning Library) 

•  Movie Recommendation with ML Lib 

•  Spark Streaming with Python 

•  Advanced Examples of Spark 

5. Using Non-Relational Data Stores with Hadoop

•  Using NoSQL 

•  Introduction to HBase 

•  HBase Tables 

•  HBase Read Write 

•  Using HBase with PIG 

•  Cassandra Overview 

•  Installing Cassandra 

•  Write Spark output to Cassandra 

•  Mongo DB Overview 

6. Querying Data Interactively

•  Overview of Drill 

•  Setting up Drill 

•  Overview of Phoenix 

•  Overview of Presto 

•  Querying both Cassandra and Hive using Presto 

7. Managing Clusters

•  Mesos and Zookeeper Introduction 

•  Oozie introduction 

•  Setup a simple Oozie workflow 

•  Using Zepplin to analyze movie reviews 

8. Introduction to Apache Kafka

•  Feeding data to your cluster 

•  Setting up Kafka 

•  Kafka Use cases 

•  Streaming with Kafka 

9. Analyzing Streams of Data

•  Spark Streaming 

•  Apache Storm Introduction 

•  Flink Overview 

10. Introduction to Flume and Sqoop

•  Setting up Flume 

•  Replication 

•  Streaming Twitter with Flume 

•  Sqoop Imports 

•  Sqoop File Formats 

•  Hive Exports 

COURSE OVERVIEW

Big data refers to the large volumes of data that are generated from various sources at a high velocity, variety, and complexity. It includes structured, semi-structured, and unstructured data.

Big data poses challenges in terms of storage, processing, analysis, and visualization due to its scale and diversity. However, when effectively managed and analyzed, big data can provide valuable insights and drive informed decision-making.

COURSE OBJECTIVES

Develop a solid understanding of the Unity game development engine and its core features.

Learn to create interactive and visually appealing games using Unity's tools and components.

Gain proficiency in game physics, scripting, and implementing game mechanics.

Understand the process of designing game levels and user interfaces for optimal player experience.

Course Instructors
Instructor 1

Ravikant Tyagi

Hello everyone, I am Ravikant Tyagi and I do have experience of 8+ years in IT as a developer and trainer. I have more than 100 websites live on internet and I have taught thousands of students, teachers & developers to learn to code and how to become professional developer with 100% practical knowledge.

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Frequently Asked Questions
Can I attend a demo session before enrolment?

•  Yes! You can attend a One Demo class free of Cost.

What if I miss a class?

•  All Classes sessions are recorded in HD Quality , so if you miss a class so you can watch the recordings.

Will I get placement assistance?

•  100 % Placement Assistance.

Who are the Trainers at Brain Mentors?

•  All our Trainers are Software Professionals, Having 7 to 15 Years’ of Experience. All Trainers worked with Top Brands.

What if I have more queries?

•  Feel free to contact us on :7042434524 01145138947

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