unleash the power of big data analytics - data science and big data analytics
DESCRIPTION
Data Science and Big Data Analytics course provides hands-on practitioner's approach to the techniques and tools required for Big Data Analytics. The course is designed to enable students to: Become an immediate contributor on a data science team Assist reframing a business challenge as an analytics challenge Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyze big data Tell a compelling story with the data to drive business action Use open source tools such as "R", Hadoop, and Postgres Prepare for EMC Proven Professional Data Scientist certificationTRANSCRIPT
DATA SCIENCE AND BIG DATA ANALYTICSAn ‘open’ course to unleash the power of Big Data
DATA SCIENCE AND BIG DATA ANALYTICS COURSEAn ‘open’ course and certification focused on concepts and principles applicable to any technology environment and industry.
This course is intended for: • Business and data analysts looking to add big data analytics skills
• Managers of business intelligence, analytics, or big data groups
• Database professionals looking to enrich their analytic skills
• College graduates looking into data science as a career field
The course provides a hands-on practitioner’s approach to the techniques and tools required for analyzing Big Data.
The course is designed to enable students to: • Become an immediate contributor on a data science team
• Assist reframing a business challenge as an analytics challenge
• Deploy a structured lifecycle approach to data analytics problems
• Apply appropriate analytic techniques and tools to analyze big data
• Tell a compelling story with the data to drive business action
• Use open source tools such as “R”, Hadoop, and Postgres
• Prepare for EMC ProvenTM Professional Data Scientist certification
Visit EMC Education Services Website http://education.EMC.com to • Access additional information on the course and the certification
• Sign up to receive an automatic notification on course availability
Source: McKinsey Quarterly Article - “Hal Varian on how the Web challenges managers”.
EDUCATION SERVICES
This course prepares you to become a certified EMC Proven Professional Data Science Associate (EMCDSA).
The ability to take data – to be able to understand it, process it, to extract value from it, to visualize it, to communicate it – that’s going to be a hugely important skill in the next decades.”- Hal Varian, Chief Economist, Google
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herein are the property of their respective owners. © Copyright 2011 EMC Corporation. All rights reserved. Published in the USA. 12/11
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DATA SCIENCE AND BIG DATA ANALYTICS COURSE OUTLINEApplying a hands-on practitioner’s approach to the techniques and tools required for Big Data Analytics.
Big Data Overview
Introduction to “R”
Key roles for a successful analytic project
State of the practice in analytics
Analyzing and exploring data with “R”
Main phases of the lifecycle
End-to-end data analytics lifecycle
Using “R” to execute basic analytic methods
Advanced analytics and statistical modeling for Big Data – Theory and Methods
Advanced analytics and statistical modeling for Big Data – Technology and Tools
Communication of Results and Big Data Analytics Life Cycle Lab
Introduction to Big Data Analytics
The role of the Data Scientist
Developing core deliverables for stakeholders
Big Data Analytics in industry verticals
Statistics for model building and evaluation
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Analytics Lifecycle LabToolsIntroduction
Module-1 Module-2 Module-3 Module-4 Module-5 Module-6
Adv. MethodsBasic Methods
Naïve Bayesian Classifier
K-Means Clustering
In-database Analytics
Data Visualization Techniques
MADlib and Advanced SQL Techniques
Association Rules
Decision Trees
How to operationalize an analytics project
Hadoop ecosystem of tools
Creating the Final Deliverables
Using MapReduce/Hadoop for analyzing unstructured data
Hands-on Application of Analytics Lifecycle to a Big Data Analytics Problem
Linear and Logistic Regression
Time Series Analysis
Text Analytics