Data 424: Data Analytics Capstone

Course Description

The Capstone course aims at providing students with an opportunity to integrate and apply the
algorithms, methods and tools they have learned throughout the program to solve real-world data
analysis problems that have an interdisciplinary nature. Students will conduct a team-based project
that involves the main aspects of the data analytics process, and will submit a consolidated report
and give a presentation at the conclusion of the project. The course serves as a final preparation for
students entering into the profession. Students get experience in working as teams, participating in
project planning and scheduling, writing reports, giving presentations, and interpreting results in a
professional manner.

This course (formerly known as CPTS/STAT 424) was taught by Dr. Assefaw Gebremedhin in Spring 2019.

Project

A capstone project is sponsored by a company or by an academic research group. A typical
project is expected to map to the following overall flow (the exact nature of data analysis and output
will depend on the questions and objectives, as well as the application domain):
1) Engage client to establish questions and objectives;
2) Critically review technical literature relevant for the project;
3) Organize, clean and pre-process data;
4) Exploratory Data Analysis;
5) Data Analysis-based Inference/Prediction/Explanation of the studied phenomenon and/or
Recommendation of decision/action based on analyzed data;
6) Data summarization and visualization; data product preparation;
7) Communicate key insights to a non-technical audience with the final data product, including the
written report and oral-digital presentation.

Prerequisites

A capstone project is sponsored by a company or by an academic research group. A typical
project is expected to map to the following overall flow (the exact nature of data analysis and output
will depend on the questions and objectives, as well as the application domain):

  • Engage client to establish questions and objectives;
  • Critically review technical literature relevant for the project;
  • Organize, clean and pre-process data;
  • Exploratory Data Analysis;
  • Data Analysis-based Inference/Prediction/Explanation of the studied phenomenon and/or
    Recommendation of decision/action based on analyzed data;
  • Data summarization and visualization; data product preparation;Communicate key insights to a non-technical audience with the final data product, including the
    written report and oral-digital presentation.

Student Learning Outcomes

Through successful completion of their capstone project, students will be able to:

  • Identify relevant questions and objectives through client engagement;
  • Demonstrate information literacy through a critical review of technical literature relevant for the
    management and analysis of data for their group project
  • Develop a project-appropriate plan and structure for data management;
  • Resolve group work allocation, leadership and cooperation issues;
  • Structure, manage and access one or more large, complex datasets;
  • Complete the analysis and interpretation of a complex, real-world data project; and
  • Present the analysis and interpretation of a complex, real-world data project in both written
    reports and digital+oral presentations