Highly successful businesses know that they can no longer rely solely on their product or service to grow; they must leverage their data to better understand their customers and learn from the collective experiences of their organizations to remain competitive.
UC Irvine’s 3-month post-graduate level Accelerated Certificate Program (ACP) in Data Science & Predictive Analytics for Business Professionals provides individuals the skills needed to effectively collect and manage Big Data and perform data-driven discovery and prediction, extracting value and competitive intelligence for their organizations.
- Learn from industry experts to utilize a combination of science, art, and business techniques to deliver new insights and competitive intelligence
- Develop strategies and skills to effectively collect and manage Big Data and perform data-driven discovery and prediction
- Optimize marketing campaigns and website behavior to increase customer responses and conversions
- Integrate powerful and traditionally untapped sources of information including social data, unstructured text, and big data sets
- Define business goals, prepare data, develop and verify predictive models, and deploy and refine predictive models
- Develop actionable plans to increase sales, reduce marketing costs, and improve customer retention
- Gain a competitive edge in the global job market through an internship in a U.S. company
Who Should Attend
This program is designed for students and professionals with a wide range of professional or educational backgrounds including business, science, engineering, information technology and marketing to develop the skills they need to succeed in this exciting, high growth field.
To earn a certificate at UCI Division of Continuing Education, students must complete all required courses with a grade of “C” or better.
This intensive hands-on course gives you the skills necessary to extract stored data elements, understand what they mean in the company, transform their formats, and derive new relationships among them to produce a dataset suitable for analytical modeling. Use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability in your company.
This hands-on course teaches the skills necessary to extract stored data elements, understand what they mean, transform their formats, and derive new relationships among them in order to produce a dataset suitable for analytical modeling. Data preparation for data mining consists of three elements: (1) Data Mining Process delineation (you have to understand the overall process), (2) Data Understanding (you can’t properly prepare data until you understand it), (3) Data Pre-processing (transforming data into a form compatible with data mining.) By the end of the course, you will be able to use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability for your company.
Learn how to use the basics of predictive analytics and modeling data to determine which algorithms to employ. Learn “best practices” and the influence various options have on predictive models to gain a deeper understanding of how the algorithms work qualitatively. Understand common approaches to deployment of predictive models and be able to integrate models into decision-making processes. Learn how to monitor models, when to update them, how to deploy and refine them, and to develop applicable performance metrics.
Highly successful businesses know that the rules have changed. No longer can they rely solely on their product or service to grow; they must leverage their data (financial, customer support, web interactions, etc.) to better understand their customers and learn from the collective experiences of their organizations to remain competitive. This course provides individuals the skills needed to effectively collect and manage Big Data and perform data-driven discovery and prediction, extracting value and competitive intelligence for their organizations.
The world produces more than 2.5 exabytes of data every day. Visualization is one key approach to gaining insight from this mountain of data, enabling you to see trends and patterns (along with gaps and outliers) in the data that are not easily identified in rows and columns of numbers. Visualization can also provide access to huge data sets, such as weather, web traffic, sales and voting records. Data sets of this size have the potential to be overwhelming and inaccessible; a good visualization provides a way to explore, understand, and communicate the data, along with actions the data indicate should be taken. You will use Tableau in conjunction with Alpine to explore and analyze data and learn how it can be used to visualize Big Data.
This course will begin with a review of some case histories of Big Data use. Basic elements of successful Big Data implementation will be covered as well as a review of commercially available tools and technology. A focus will be placed on value opportunities in online marketing, search optimization and site performance modeling.
As an optional last course and for an additional fee of $2,900, you have the opportunity to apply academic theory and gain practical experience in a variety of businesses and industries for 10 weeks. A research project provides additional training. Also included in the internship are the Resume Development and Interviewing Skills workshops.
Students will be placed into a morning (9:00-12:00) or afternoon (13:00-16:00) schedule. Courses in the program are taken consecutively, completing one before proceeding to the next. Schedules are not guaranteed and are subject to change. A final schedule will be provided on the first day of the program.
Certificate tuition: $7,900**We are pleased to offer a 25% discount on fall 2020 and winter 2021 ACP tuition and 33% discount for spring if you choose the remote option.
(Approximate total cost: $14,100 USD, excludes airfare)
Internship tuition: $2,900
UPCOMING PROGRAM DATES
|Fall 2020||Sep 21 - Dec 4|
|Spring 2021||Mar 29 - Jun 11|
|Fall 2021||Sep 27 - Dec 10|