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Data Science

Overview

Corporations have dramatically increased investments in their "digital enterprise" in the past few years. It has been estimated that by 2020, IT departments will be monitoring 50 times more data than they are today. This tidal wave of data is driving unprecedented demand for those with the skills required to manage and leverage these very large data sets into a competitive advantage.

Curriculum is designed to help meet the expanding needs for data scientists who are skilled in the utilization of a unique blend of science, art and business. These professionals understand how to automate methods of collecting and analyzing data and utilize techniques to discover previously hidden insights that can profoundly impact the success of any business.

Understand the skills needed to effectively collect and manage big data, perform data-driven discovery and prediction, and extract value and competitive intelligence for your organization. This program provides the skills required to become a data scientist and provides existing data analysts with opportunities to broaden skills.

Learn topics such as: utilizing concepts in on- and off-cloud; scalable data engineering (inspecting, cleaning, transforming, and modeling data), unstructured data and NoSQL; computational statistics; pattern recognition; data mining /predictive analytics; machine learning; data visualization; and high performance software and hardware.

Who Should Enroll

This program is intended for professionals in a variety of industries and job functions who are looking to help their organization understand and leverage the massive amounts of diverse data they collect. Others who would benefit from this program include: data engineers, data analysts, computer scientists, business analysts, database administrators, researchers, and statisticians.

Career Insight

Occupational summary for software developers, applications in the United States.

801,667
Jobs
(2016)
18.40%
Projected Growth
(2017-2027)
$88k-$141k
Annual Salary
(25th-75th Percentile)

Program Benefits

  • Learn from industry experts how to utilize a combination of science, art & business techniques to deliver new insights and competitive intelligence
  • Describe the phases of the analytics lifecycle
  • Utilize a variety of statistical and computer science tools and techniques to analyze data
  • Describe and use the typical tools and technologies required to model and analyze large (big) datasets
  • Explain the use of typical tools to explore data (R, STATISTICA, Hadoop, etc.)
  • Utilize an inquisitive "hacker" mentality to uncover new meaning from existing data
  • Effectively design, model and manage databases
  • Describe and utilize unstructured and structured data sets leveraging text analytics tools.
  • Define requirements, develop an architecture, and implement a data warehouse plan

Course Schedule

Required Courses

TitleWinterSpringSummerFall
I&C SCI X426.60
Introduction to Data Science (3 units)
I&C SCI X426.60
to be scheduled Online Online Online Online to be scheduled
I&C SCI X426.61
Data Exploration, Analytics and Visualization (3 units)
I&C SCI X426.61
to be scheduled Online Online Online Online to be scheduled

Elective Courses

TitleWinterSpringSummerFall
Data Science
I&C SCI X414.33
Math Review for Data Science and Analytics (2.5 units)
I&C SCI X414.33
to be scheduled Online Online to be scheduled
I&C SCI X425.22
Business Intelligence/Data Warehouse (3 units)
I&C SCI X425.22
to be scheduled Online Online to be scheduled
I&C SCI X425.18
Hadoop: In Theory and Practice (3 units)
I&C SCI X425.18
to be scheduled Online Online  
I&C SCI X425.80
Introduction to Big Data (2 units)
I&C SCI X425.80
  Online   to be scheduled
I&C SCI X425.70
Big Data Analytics (2 units)
I&C SCI X425.70
to be scheduled Online    
I&C SCI X425.63
Effective Data Preparation (2 units)
I&C SCI X425.63
to be scheduled Online Online to be scheduled
I&C SCI X426.64
Introduction to Programming with Python (2 units)
I&C SCI X426.64
to be scheduled Online Online Online to be scheduled
I&C SCI X426.62
Introduction to Python for Data Analysis (1.5 units)
I&C SCI X426.62
  Online   to be scheduled
I&C SCI X425.32
Data Modeling (2.5 units)
I&C SCI X425.32
to be scheduled   Online  
I&C SCI X425.35
Data Management (2.5 units)
I&C SCI X425.35
  Online   to be scheduled
I&C SCI X426.75
Tools and Techniques for Machine Learning (2 units)
I&C SCI X426.75
  Online   to be scheduled
I&C SCI X425.20
R Programming (2 units)
I&C SCI X425.20
to be scheduled Online Online to be scheduled

Course schedules are subject to change. Individual courses may be taken without enrolling in the full certificate.

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Certificate Eligibility and Requirements

A certificate is awarded upon completion of 15 credit units (6 required and 9 elective credit units) with a grade of “C” or higher in each course.

Some courses may be listed as electives in multiple certificates, students may use a maximum of two courses to fulfill a certificate requirement between two programs.

To become an official candidate in the program, students pursuing the certificate must submit a Declaration of Candidacy. Students are encouraged to declare candidacy as soon as possible, but no later than after the third course in the program. To receive the certificate after completing all program requirements, students must submit a Request for Certificate. All requirements must be completed within five (5) years after the student enrolls in his/her first course. Students not pursuing a certificate are welcome to take as many individual courses as they wish.

Presented in partnership with:
Predictive Analytics World
Predictive Analytics World is the business-focused event for predictive analytics professionals, managers and commercial practitioners.
Learn More

Advisory Committee

  • Dean Abbott, President, Abbott Analytics
  • John Elder, Ph.D., Chief Scientist, Elder Research
  • Bernie Jeltema, Principal Consultant, Strategic Frameworks, Inc.
  • Derrick Lam, MBA, Database Administrator, UCI Division of Continuing Education Instructor
  • Amit Manghani, Senior Director of Product Management, Oracle
  • Gary Miner, Ph.D., Senior Consultant/Statistician, Statsoft
  • Bob Nisbet, Ph.D., Consulting Data Scientist
  • Eric Siegel, Ph.D., Chair, Predictive Analytics World
  • Jim Sterne, President, Target Marketing, Chairman, Digital Analytics Association, Founder, eMetrics Marketing Optimization Summit
  • James Taylor, CEO, Decision Management Solutions

On-site Training Available

Our Corporate Training specialists can deliver this program or customize one that fits your organization’s specific needs. Visit Corporate Training or call (949) 824-1847 for information.

English Proficiency Requirement
All certificate programs at UCI Division of Continuing Education (classroom and online formats) require professional-level English language proficiency in listening and note-taking, reading comprehension and vocabulary, written expression, and oral presentation.