Predictive Analytics Certificate Program

Description:

Predictive Analytics is among the fastest growing fields in business today. Experts like Nate Silver, of the New York Times blog FiveThirtyEight, are showing the world that predictive analytics pays big dividends in politics, sports and business. Companies such as Google, Twitter, Netflix and CPG are recruiting predictive analytics professionals to mine the ever-growing mass of consumer behavior data to gain a competitive edge in the marketplace. Statisticians no longer need to be the back room number cruncher.
The six-week Predictive Analytics Certificate Program will introduce you to many of the popular advanced statistical techniques used in the field of marketing science and predictive analytics. The course will teach multivariate techniques used to transform information from large data sets data into actionable insights. You will gain hands-on experience using SPSS and prepare to be a part of this growing field.
As you carefully sift through the data, you will discover how to turn data into insights and insights into knowledge. You will experience how the art of “story telling” helps to communicate your findings better, captures your audience’s attention and leads to actionable management decisions.
The Predictive Analytics Certificate Program also counts as an elective towards completing the Integrated Marketing Communications Certificate Program.
NOTE: This is not a statistics course. Even though all the techniques are based on the theory of statistics, the approach taken here is logic-based, rather than formula-based. Hence, you will not be a statistics expert at the end of this program; however, you will know and apply all the techniques in a practical manner. Requirement: Basic Business Statistics. No prior experience in SPSS is required.

For More Information, Contact:

Jurate Murray
  • Email: jmurray9@depaul.edu
  • Phone: (312) 362-5913
  • FAX: (312) 362-6540

Student Testimonials

"The course strengthened my knowledge of advanced data analysis and statistical modeling techniques and gave me practical experience at applying [these techniques] to a complex real-world business problem. The course was well laid out and delivered with a highly efficient style. I was able to recognize my passion for the subject and will pursue further education in this field of study."
-Bryan Rulli

Who Should Attend

  • Professionals in fields such as analytics, marketing, management, business intelligence, data and marketing science, and operations research
  • Professionals wanting to improve their analytical skills
  • Individuals with a technical background interested in marketing or data analysis
  • Individuals with no technical background interested in exploring careers in data analysis
  • College graduates in the social sciences interested in furthering their data analysis skills

Benefits

  • Gain knowledge of SPSS
  • Discover how to use data to create a coherent “story” to communicate an effective marketing strategy and make presentations supported by data analyses
  • Become proficient in advanced multivariate statistical techniques using a practicing manager’s point of view
  • Learn to match the right technique with the right opportunity
  • Update and enhance your current skills

Topics

  • Factor analysis for data reduction
  • Multiple regression for prediction purposes
  • Cluster analysis for better segmentation
  • Multiple discriminant analysis for classification
  • Correspondence analysis with perceptual mapping

Syllabus

Week 1
Predictive Analytics & Data Modeling
  • Overview of multivariate statistical techniques
  • Introduction to measurement scales
  • Introduction to data analysis using SPSS
Week 2
Factor Analysis
  • Overview of data analysis using SPSS
  • Using SPSS factor analysis for data reduction
Week 3
Multiple Regression Analysis
  • Understanding multiple regression analysis
  • Using SPSS multiple regression analysis to explain and predict causal relationships
Week 4
Cluster Analysis
  • Understanding cluster analysis
  • Using SPSS cluster analysis to create consumer segments
Week 5
Multiple Discriminant Analysis
  • Understanding discriminant analysis
  • Using SPSS multiple discriminant analysis to predict consumer choice
Week 6
Correspondence Analysis
  • Understanding correspondence analysis
  • Using SPSS correspondence analysis to visualize relationships between variables

Frequently Asked Questions

Click here for DePaul University Continuing and Professional Education departmental student policies.
Will we be using data?
Yes, this program teaches you how to use SPSS.
Do I need to have experience with SPSS?
No prior experience in SPSS is required.
Do I need to access my own company's data?
No. A real-world consumer dataset will be provided for in-class data analysis.
Do I get DePaul credit for this class?
No, but some DePaul CPE courses have been approved for CEU credits. This is a professional education program with different requirements than courses taken for academic credit.
How big is the class?
Class size is limited to allow for a more interactive environment in the classroom. Most classes have fewer than 20 students.
Will I have to write papers and take exams?
There are no assignments, papers or exams for the program. Each week, in-class time will be provided for you to work with SPSS leaning how to analyze and interpret a different multivariate statistical technique using a real-world dataset.

Registration

Online registration is available 24 hours a day, 7 days a week. Add the course you are interested in to your shopping cart and proceed to checkout. Registration is also available via phone, fax or mail. An Adobe Acrobat PDF of the registration form is provided for your convenience.

Course Availability

Course Section Add to Shopping Cart
KMC 325-00
20142
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Loop6348
Jan Gollins
Loop Campus, TBA
Mondays, June 9 - July 14, 2014, 6:00 - 9:00 PM
1.8 CEUs
18 Contact Hours
Required Fees: Price
Registration - Late fee of $75 applied to all registrations received after 6/2/2014$1,095.00
Course Section Add to Shopping Cart
KMC 325-00
20144
1
Loop6506
Jan Gollins
Loop Campus, TBA
Tuesdays, October 21 - November 25, 2014, 6:00 - 9:00 PM
1.8 CEUs
18 Contact Hours
Required Fees: Price
Registration - Late fee of $75 applied to all registrations received after 10/14/2014$1,095.00