Online Training - Data Science and Big Data Analytics

Dilihat 2000

DESCRIPTION Data Science is a "concept to unify statistics, data analysis and their related methods" to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization. This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible - increasing the potential for data to transform our world. COURSE OUTLINE 1. Introduction to Big Data Analytics

Big Data Overview
State of the Practice in Analytics
The Data Scientist
Big Data Analytics in Industry Verticals

2. Data Analytics Lifecycle

Discovery
Data Preparation
Model Planning
Model Building
Communicating Results
Operationalizing

3. Review of Basic Data Analytic Methods Using R

Using R to Look at Data – Introduction to R
Analyzing and Exploring the Data
Statistics for Model Building and Evaluation

4. Advanced Analytics – Theory And Methods

K Means Clustering
Association Rules
Linear Regression
Logistic Regression
Naïve Bayesian Classifier
Decision Trees
Time Series Analysis
Text Analysis

5. Advanced Analytics - Technologies and Tools

Analytics for Unstructured Data - Map Reduce and Hadoop
The Hadoop Ecosystem
- In-Database Analytics – SQL Essentials
- Advanced SQL and MADlib for In-Database Analytics

6. The Endgame or Putting it All Together