Within our MS Analytics curriculum, students gain practical experience towards the end of their studies by collaborating with an organization on a real-world analytics or data science project. To enroll, students must have completed a minimum of 7 courses (for full-time students) to 8 courses (for part-time students) including CSE 6242 Data & Visual Analytics and MGT 6203 Data Analytics in Business. Alternatively, permission from both the instructor and the MS Analytics program is required for enrollment.

Overview

The Applied Analytics Practicum is a semester-long 6-credit course designed to offer students in the MS Analytics program hands-on professional practice experience.  Practicum projects serve as a platform to apply theoretical concepts learned in the classroom to real-world data science challenges pertinent to businesses, government agencies, or other organizations. This course aims to equip students with the following skills:

• Defining and scoping analytics projects to align with organizational needs
• Handling, structuring, and analyzing authentic datasets
• Employing relevant data science methodologies, tools, and techniques
• Generating value, insights, and knowledge through analytics and data science principles
• Project management
• Delivering professional written and oral presentations of findings

The Practicum extends over a full semester (10 weeks for summer or 15 weeks for fall or spring), culminating in a comprehensive written report and presentation to the project sponsor. Student earn 6 academic credits for their involvement and are thus expected to dedicate approximately 20 hours per week to project work over the course of the semester. There are no associated costs for organizations to sponsor an Applied Analytics Practicum project.

Practicum Sponsors are asked to indicate their preference for working with either the on-campus cohort or the online cohort, or they can express openness to either. While there are some distinctions between the two programs concerning project dynamics, both offer robust opportunities for collaboration.

One significant difference is that sponsors working with the on-campus students work with a single team of 3-4 students whereas sponsors working with the online students must be open to working with a minimum of 20 students. Sponsors of projects for the online cohort have the option to ask students to work individually or in teams comprised of 2 or 3 students per team.  Another difference is that the on-campus cohort consists of students based in Atlanta, Georgia, whereas the online cohort represents diverse geographical locations worldwide. Despite these differences, both cohorts follow the same curriculum and are equally prepared to undertake the practicum with proficiency.

Learn more about the on-campus MS Analytics program

Learn more about the online MS Analytics program

Requirements

To fulfill Georgia Tech's MS Analytics practicum requirements, opportunities should enable students to:

• Apply classroom concepts to address significant analytics or data science challenges within your organization
• Utilize advanced data science skills at the graduate level
• Engage in various aspects of the data science project life cycle, including data mining, machine learning, predictive modeling, statistical correlations, and visualizations
• Dedicate 20 hours per week throughout an entire semester

Sponsor Commitments include:

• Impact: Sponsors commit to providing a data science project of substantial interest and value to their organization.
• Data Transfer: Data should be ready for secure transfer to students approximately one to two weeks before the start of the semester, typically through the sponsor's preferred internal method. Any cost associated with student access to software/platforms is assumed by the sponsoring organization.
• NDA: We encourage organizations to structure the NDA such that it's solely between the sponsoring company and the students.  The NDA should allow students to list the sponsoring company's name and provide a high-level project description to support students in marketing themselves for future positions without revealing protected information. Please note that Georgia Tech staff and faculty (including TAs) typically do not sign NDAs as they do not access the project data.
• Liaison & Student Communication: Sponsors are asked to assign a liaison as the primary point of contact for student communication. This liaison does not need to have data science knowledge but does need to have domain knowledge along with a solid understanding of the project statement and expectations. This liaison should be available to host weekly meetings with the students and to answer students' questions via an e-communication channel in between meetings. 
  • For on-campus practicums, weekly virtual meetings and a dynamic communications channel (Slack or Teams) are required.
  • For online practicums, virtual office hours and a dynamic communication channel (like Slack or Teams) are required. TAs are assigned to online practicum projects to assist sponsors with student communication, including setting up virtual meetings for office hours and establishing a communication channel with all relevant parties invited.
• Meetings:
  • Sponsors are responsible for hosting a Project Pitch Meeting to pitch their project to students. For on-campus students, these meetings occur the week before classes and each sponsor is given a 10-minute timeslot to highlight their project. The internal Georgia Tech practicum team is responsible for scheduling these timeslots. For the online cohort, the Project Pitch Meeting occurs 6-8 weeks in advance of the semester starting. Each sponsor schedules their own individual 1-hour virtual session to pitch their project and answer student questions. These virtual sessions are recorded and shared with students who are unable to attend the live sessions.
  • We ask all sponsors to host a Project Launch Meeting with the students assigned to their project during the first week of the semester.
• Deliverables:
  • Students are required to submit a mid-semester progress report in the form of a PPT presentation to both the sponsor and the MS Analytics Program. On-campus students are required to present their mid-semester progress report to the sponsor.
  • Students are required to submit a final project report to both the sponsoring organization and the MS Analytics program. On-campus students are also required to present their project results to the sponsor.

For an in-depth overview of project sponsorship, please review our sponsorship Info Session video

Project Proposal Examples & Template

We have partnered with sponsoring organizations on a broad array of projects including predictive modeling, dashboarding, optimization, valuation, and other data science & analytics problems.  The examples provided below reflect projects that have been submitted and approved in previous semesters:

• Analyze and predict timeline risk associated with clinical studies for a pharmaceutical company
• Perform social media sentiment analysis for a telecommunication company
• Analyze and predict likelihood of injury for players based on their training schedule, for a college sports team
• Predict paper breaks in paper manufacturing process in advance and identify potential causes
• Develop a predictive model and risk calculator to identify patients as high risk for being readmitted to the hospital
• Apply neural network to time-series data from consumer payment history to predict future payment delinquency
• Performing optimal rent assessment for a non-profit agency that supports low-income families with finding affordable housing, to determine how much they should be charging for rent within the confines of limited capital reserves
• Classify instances of bullying in kids' text message conversations using NLP for a start-up, with eventual goal of building an app that can alert parents to instance of bully in real-time
• Build a model to rank the riskiest delivery routes for a Fortune 500 company's connected fleet services, with the goal of increased driver safety and improved efficiency
• Classify breast tissue ultrasound images by benign and malignant tumors for a healthcare start-up to provide "baseline" accuracy and guide future steps for classification improvement

Call For Proposals

We are actively seeking organizations interested in sponsoring a MS Analytics practicum project for the upcoming semester(s). 

If your organization is interested in learning more about sponsoring a practicum project, please join us for an upcoming Practicum Sponsorship Info Session. Upcoming session information can be found in the right column of this page. Previous practicum sponsors can bypass the Info Session and complete the form below to have your project proposal added to our MS Analytics practicum opportunities database for review. We will carefully review your proposal and follow up regarding the next steps.

Project Proposal Deadlines:

• Spring 2025 Proposal: September 20, 2024
• Summer 2025 Proposal: February 20, 2025

• Fall 2025 Proposal: May 20, 2025