Artificial Intelligence & Data Science
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Big Data Specialization by Coursera

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Course Features

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Duration

8 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Effort

3 hours per week

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Teaching Type

Self Paced

Course Description

A comprehensive overview of big data organization, analysis, and interpretation will help you make better business decisions. Your insights can be applied to real-world problems. ********* Are you looking to learn more about big data and how it can impact your business? This specialization is for you. Through hands-on experience using the systems and tools used by big data engineers and scientists, you will be able to understand what big data can offer. No programming knowledge is required. This tutorial will show you how to use Hadoop with Spark, Pig, Hive, MapReduce and Spark. You will learn how to use graph analytics to model problems and perform predictive modeling by following the code. This specialization will allow you to ask the right data questions, communicate with data scientists effectively, and explore large, complex data sets. The final Capstone Project was developed in partnership by Splunk data software company. It will allow you to apply the skills that you have learned to basic analysis of big data.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors

Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting

Recognize different data elements in your own work and in everyday life problems

Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design

Retrieve data from example database and big data management systems

Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications

Design an approach to leverage data using the steps in the machine learning process

Apply machine learning techniques to explore and prepare data for modeling

Course Instructors

Ilkay Altintas

Chief Data Science Officer

Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Ex...

Amarnath Gupta

Director, Advanced Query Processing Lab

Amarnath Gupta received his Ph.D. in Computer Science from Jadavpur University in India. He is currently a full Research Scientist at the San Diego Supercomputer Center of UC San Diego, and directs t...

Mai Nguyen

Lead for Data Analytics

Mai H. Nguyen is the Lead for Data Analytics at the San Diego Supercomputer Center (SDSC) of the University of California, San Diego (UCSD). Her research centers on applying machine learning techniqu...
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