Engineering | Entrepreneurship + Innovation

Fulton Analytics Program

Program Description

In this program, students will be introduced to descriptive and predictive data analytics methodologies. Data preprocessing and visualization will be introduced alongside descriptive analytical techniques that are concerned with identifying proper summary statistics to aid in the understanding of data sets. Predictive analytics will also be introduced, with focuses on the processing of data to assist in how future data can be categorized or classified.

Program Topics

The Fulton Graduate Analytics Program is an action-oriented experience that will cover the following topics:

  • Data Preprocessing
  • Descriptive Analytics
  • Data Exploration
  • Forecasting Methods
  • Regression Techniques
  • k-Means Clustering
  • Decision Trees and Random Forests
  • Neural Networks
  • Support Vector Machines

Program Project

Towards the end of the program you will be completing a three phased project based on a data set provided.  This data set will be partitioned into three categories: Training Data (60%), Testing Data (30%), and Evaluation Data (10%).  In the first phase, you will preprocess the training data to help you determine which predictive model you think would work best.  Summary statistics, the removal of outliers, and the handling of missing or bad data, will help you clean up the data set for better analysis. In the second phase, you will take the training data and train your selected model based on Phase 1.  Once the training has been complete, you can make inferences about the data, and determine whether the selected model is best suited to classify or categorize the data set. In the final phase, you will test your final model on the testing data, and make any last minute changes to update your model for final evaluation.  After all three phases have been complete, your model will be evaluated for quality based on the unseen evaluation data.

Learning Outcomes

Those who complete the Fulton Graduate Analytics Program will:

  • Gain an understanding of and appreciation for the complexities of data management, including data preprocessing and visualization.
  • Be able to identify and implement summary statistics for a variety of data types and data sets.
  • Explore different predictive analytics techniques, including support vector machines, neural networks, and decision trees.
  • Be able to identify when and how predictive analytics techniques are applied to varying datasets.
  • Demonstrate the ability to preprocess a dataset, and select an appropriate predictive technique to categorize a related, unknown, dataset. 

Earning a Certificate of Completion

To earn a Fulton Graduate Analytics Program certificate of completion, participants must be available to attend weekly workshop meetings (approximately 2 hours each week) over the course of the program session.

 

The next Fulton Graduate Analytics Program will be:

When: Fall 2017 – Spring 2018; Fridays; 12 noon – 2 pm

Workshop Dates and Topics:

  • 9/29/2017 – Program Welcome and Data Essentials
  • 10/6/2017 – Preprocessing and Similarity Measurements
  • 10/20/2017 – Descriptive Analytics
  • 10/27/2017 – Data Exploration and Visualization
  • 11/3/2017 – Forecasting Methods
  • 11/17/2017 – Linear Regression Techniques
  • 2/2/2018 – Logistic Regression Techniques
  • 2/9/2018 – k-means Clustering
  • 2/16/2018 – Decision Trees and Random Forests
  • 2/23/2018 – Neural Networks
  • 3/16/2018 – Support Vector Machines
  • 3/23/2018 – Final Project Review and Program Closing

Where: ASU Tempe campus: BYENG M1-35

 

Who Should Enroll

The Fulton Graduate Analytics Program is available to all current Fulton graduate students who are currently enrolled in a degree-seeking program of study.

 

Pre-Requisites

In order to be eligible for the Fulton Graduate Analytics Program, applicants must be post-baccalaureate degree-seeking graduate students in good academic standing. A strong work ethic and the ability to leave your comfort zone are also required for successful completion

  • Are you a current ASU graduate student enrolled in a degree-seeking program of study? Y/N
  • If yes, please provide your 10-digit ASU Affiliate ID #:
  • If yes, please provide a statement justifying your interest and commitment to the program:
  • If yes, of the following software tools, please select which one(s) you are familiar with: (MATLAB, Microsoft Excel, RStudio, Minitab, Weka, SPSS)
  • If no, unfortunately, you are not eligible for this program. Please contact us for alternate opportunities.

Application Deadline: Sunday, September 10, 2017 at 11:59 pm MST.

After your application is submitted, a Fulton Graduate Analytics Program representative will contact you to discuss registration finalization and details.

 

 

Contact Information

Email: mclough@asu.edu

Phone: (480)965-2804