Big Data

Takashi offers monthly Hadoop and Big Data training classes at our office located in Fremont, CA. The duration is 2 days, one weekend.

  • Our training program is never static and always evolves as Big Data technologies do.
  • You can attend training two more times at no additional cost (it’s because new tools and technologies get added every few months in Big Data eco-system and it’s unfair to charge students for those incremental changes)
  • Lifetime access to latest slides and virtual machine Reasonably priced
  • This training is primarily for techies who want to get into Big Data space. Our training is one comprehensive training which cover the whole spectrum of Big Data as you can see in course outline down.
Weekend: October 4th & October 5th 2014
8:00 AM – 12:00 PM – Class Instructions
12:00 PM – 1:00 PM – Lunch Break
1:00 PM – 5:00 PM – Hands on and Q&As

You can always give us a call at Phone: 510 943 5968

Frequently Asked Questions:

Will There Be Job Opportunities afterwards?
We are a consulting company and would love to help you get placed.

Hands On?
Yes! Theory and practice go hand-in-hand

Do I need to bring my own device?
Yes! Please make sure your computer has at least 4GB of RAM, preferably 8

What is prerequisite for this course?
You must have done programming at some point in your career.

High Level Course Structure (7 Course Hadoop Meal):

Course 1: Hadoop Overview

  • Why Hadoop?
  • What is Hadoop?
  • Hadoop Distributed File System (HDFS)
  • Introduction to Map Reduce

Course 2: Hadoop Deep Dive

  • Hadoop Architecture
  • Developing a Map Reduce Application
  • Map Reduce File I/O
  • Features and Optimizations
  • YARN
  • Unit Testing Map Reduce Programs

Course 3: Hive & Pig

  • Why Hive and Pig?
  • Hive Overview
  • Hive Usage
  • Pig Overview
  • Pig Usage

Course 4: Flume, Sqoop & Oozie

  • Flume Overview
  • Flume Usage
  • Sqoop Overview
  • Sqoop Usage
  • Hadoop Workflow
  • Job Control
  • Oozie

Course 5: HBase and NoSql

  • Limitations so far
  • What’s needed?
  • Challenges with RDBMS’s
  • HBase overview
  • HBase Usage

Course 6: Apache Spark

  • Spark Basics
  • Introduction to Scala
  • Spark Usage
  • Mllib

Course 7: Big Data Analytics & Visualization

  • Introduction to Statistics
  • Simple Linear Regression
  • Data Science Overview
  • Data Engineering Overview
  • Machine Learning: Introduction
  • Recommendation Engine
  • Clustering
  • Classification
  • Data Visualization

Appendix: Hadoop Administration

  • Hardware Configuration
  • Planning a Hadoop Cluster
  • Installation
  • Network Port Bonding
  • Configuration and Settings
  • Rack Topology