Philadelphia Finance

Sep 18 2018

Data Science and Big Data Analytics Training and Certification – EMC Education

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This ‘Open’ curriculum-based training and certification provides a hands-on practitioner’s approach to the techniques and tools required for Big Data Analytics. ‘Open’ courses focus on technology concepts and principles, ideal for multi-vendor, multi-technology environments. Supported by real-world use cases, the curriculum leverages industry best practices and industry-standard terminology and definitions.

Earn certifications for each of the two courses below to become a certified Data Scientist.

Course 1
Data Science and Big Data Analytics

Course 2
Advanced Methods in Data Science and Big Data Analytics

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Data Science and Big Data Analytics

Gain the skills needed to immediately and effectively participate in big data and other analytics projects.

Data Science and big data analytics is an ‘open’ course that provides an introduction to big data and the Data Analytics Lifecycle to address business challenges that leverage big data. The course provides grounding in basic and advanced analytic methods and an introduction to big data analytics technology and tools, including MapReduce and Hadoop.

GET CERTIFIED: This course aligns to EMC Proven Professional Data Scientist Associate (EMCDSA) certification.

Big Data Overview

State of the practice in analytics

The role of the Data Scientist

Big Data Analytics in
Industry Verticals

Introduction to Big Data Analytics

Key roles for a successful analytic project

Main phases of the lifecycle

Developing core deliverables for stakeholders

End-to-end data analytics lifecycle

Introduction to R

Analyzing and exploring data with R

Statistics for model building and evaluation

Using R to execute basic analytic methods

Naive Bayesian Classifier

Linear and Logistic Regression

Time Series Analysis

Advanced analytics and statistical modeling for Big Data – Theory and Methods

Using MapReduce/Hadoop for analyzing unstructured data

Hadoop ecosystem of tools

MADlib and Advanced SQL Techniques

Advanced analytics and statistical modeling for Big Data – Technology and Tools

How to operationalize an analytics project

Creating the Final Deliverables

Data Visualization Techniques

Hands-on Application of Analytics
Lifecycle to a Big Data Analytics Problem

Communication of Results and Big Data Analytics Life Cycle Lab

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