Duration
5 days
Overview
In a 5 day course students will setup entire environment from ground 0 by deploying hortonworks on Google cloud and later use same environment for development purposes.
Intended Audience
The intended audience of the course is:
- Hadoop Developers
- Data Engineers
- Integration Engineers
- Hadoop Administrators
- Data Steward
Pre-requisite and Lab Details
The intended audience should have a background on:
- Software Development
- Unix and Hadoop
The lab setup for this course would be:
- Windows 7 or Higher
- 4 GB RAM
- Google Cloud Free Account
Course Outline
Big Data
- What is Big Data
- Dimensions of Big Data
- Big Data in Advertising
- Big Data in Banking
- Big Data in Telecom
- Big Data in eCommerce
- Big Data in Healthcare
- Big Data in Defense
- Processing options of Big Data
- Hadoop as an option
Hadoop
- What is Hadoop
- How Hadoop Works
- HDFS
- Mapreduce Deep Dive
- How Hadoop has an edge
Hadoop Ecosystem
- Sqoop
- Oozie
- Pig
- Hive
- Flume
Hadoop Hands On
- Running HDFS commands
- Running your Mapreduce program
- Running Sqoop Import and Sqoop Export
- Creating Hive tables directly from Sqoop
- Creating Hive tables
- Querying Hive tables
- Running an Oozie workflow
Hive
Introduction
- Basic Data Analysis with Hive
- Hive Data Management
- Text Processing with Hive
- Transformations in Hive
- Optimizing Hive
- Hive Hands On
- Extending Hive
Impala
Introduction
- Basic Data Analysis with Impala
- Text Processing with Impala
- Optimizing Impala
- Impala Hands On
Pig
Introduction
- How Pig works
- Pig Hands On
HBase
Introduction
- HBase installation
- HBase Shell commands
- HBase Hands On
Flume
Introduction
- Flume installation
- Flume implementation
Python
Python Setup
- Command Line Basics
- Installing Python
- Running Python Code
Python Object and Data Structure Basics
- Introduction to Python Data Types
- Numbers
- Variable Assignments
- Introduction to Strings
- Indexing and Slicing with Strings
- Lists in Python
- Dictionaries in Python
- Tuples with Python
- Sets In Python
- Boolean in Python
- I/O with Basic Files in Python
- Lab: Python Basics Hands-On
Python Comparison Operator
- Python Statements
- If Elif and Else Statements
- For Loops
- While Loops
- Lab: Python Statements Hands-On
Methods and Functions
- Functions in Python
- Lambda Expression, Map and Filter Functions
- Lab: Python Functions Hands-On
Python for Data Analysis – NumPy
- Introduction to NumPy
- NumPy Arrays
- NumPy Array Indexing
- NumPy Operations
- Lab: NumPy Hands-On
Python for Data Analysis – Pandas
- Introduction to Pandas
- Series
- DataFrames
- Missing Data
- Groupby
- Merging Joining and Concatenating
- Lab: Pandas Hands-On
Linear Regression
- Linear Regression Theory
- Lab: Linear Regression with Python
Logistic Regression
- Logistic Regression Theory
- Lab: Logistic Regression with Python
K Nearest Neighbors
- K Nearest Neighbors Theory
- Lab: K Nearest Neighbors with Python
Decision Trees and Random Forests
- Introduction to Tree Methods
- Lab: Decision Trees and Random Forests with Python
Support Vector Machines
- SVM theory
- Lab: SVM with Python
K Means Clustering
- K Means Algorithm Theory
- Lab: K Means with Python
Principal Component Analysis
- Lab: PCA with Python
Hierarchical clustering
- Lab: Hierarchical clustering with Python
Time Series Analysis
- ARIMA
- SARIMA
- Holt-Winters
- Lab: Time Series Analysis with Python
Apriori Algorithm
- Association Rule
Lab: Use case of Apriori
Programme scope, delivery arrangements and suitability are confirmed during enquiry.