Data Science Practicum Pathway: DSBA 6390

The Data Science Practicum pathway is a hands-on, project-based capstone course designed for students who wish to apply their technical and analytical skills to real-world challenges without completing a formal internship. Working in small teams, students select an industry or organization of interest and, with instructor approval, define a data-driven business problem and design an end-to-end analytics solution.
Projects will emphasize core data science competencies, including data wrangling, predictive modeling, machine learning, natural language processing (NLP), and data visualization – while addressing practical organizational needs. Participation in these projects will require an application and a company selection process.

This practicum provides a rigorous applied experience designed to strengthen professional readiness, teamwork, communication, and problem-solving abilities in a data-centric business environment.

Practicum Requirements Summary

Students must meet all prerequisite coursework and secure instructor approval before enrollment. 

  • Complete a minimum of 18 credit hours before registration.
  • Demonstrate proficiency in Python, Predictive Modeling, Machine Learning, Cloud Computing, and Data Visualization.
  • Have completed the following courses (or equivalents): DSBA 6160, DSBA 6156, and DSBA 6211.
  • Participate in team-based project selection, scoping, and implementation.
  • Deliver a comprehensive final presentation and written project report demonstrating actionable insights and technical rigor.

The Data Science Practicum Pathway: Three Phases

Phase 1: Pre-Practicum Preparation 

During this phase, students prepare for successful practicum placement and project scoping:

  • Confirm Eligibility: Ensure all prerequisites and credit-hour requirements are met.
  • Project Proposal Submission: Identify an area of interest, a potential company partner, or an industry domain. Prepare and submit a project proposal for instructor review and approval.
  • Application Process: If pursuing a project with an external organization, complete the required practicum application and company selection process.
  • Instructor Review: The instructor will assess project feasibility, alignment with course learning outcomes, and data availability.
  • Project Team Formation: Students will be grouped based on interests, technical skills, and project complexity.
  • Project Authorization: Receive final approval to proceed with the selected or assigned project before registration in DSBA 6390.

Phase 2: Practicum Implementation Phase 

Once enrolled, students will begin structured project execution with ongoing guidance from the instructor:

  • Finalize project scope, deliverables, and success criteria with instructor feedback.
  • Data Acquisition and Preparation: Collect, clean, and preprocess datasets for analysis, ensuring data integrity and ethical handling.
  • Exploratory Data Analysis (EDA): Identify key trends, correlations, and insights to inform model design.
  • Model Development: Apply appropriate analytical and machine learning techniques to address the project’s central business or operational problem.
  • Progress Reports: Submit periodic project updates and reflect on milestones achieved, challenges faced, and next steps.
  • Instructor Mentorship: Receive technical and strategic guidance during regular check-ins to ensure steady progress and professional-quality outcomes.

Phase 3: Final Deliverables & Presentation Phase

In the concluding phase, students synthesize their project results and present outcomes to academic and professional audiences:

  • Finalize Analysis: Validate models, interpret findings, and quantify business or technical impact.
  • Develop Insights & Recommendations: Translate analytical results into actionable business insights and recommendations.
  • Peer and Instructor Evaluation: Projects will be assessed based on technical quality, communication clarity, teamwork, and overall impact.
  • Reflection Summary: Students will complete a brief reflection discussing lessons learned, skill development, and career relevance.

Practicum Presentation Process

The practicum culminates in a professional presentation and evaluation session:

  • Presentation Format (20–30 minutes): Each team presents its business problem, methodology, key findings, and recommendations to faculty and invited guests.
  • Q&A Session (15–20 minutes): Faculty and industry reviewers may ask questions regarding data sources, technical methods, and conclusions.
  • Evaluation Criteria: Presentations are evaluated on analytical depth, technical execution, clarity, and professional quality of recommendations.
  • Feedback & Revision: Teams receive feedback and may be asked to refine reports or visualizations before final grading.

Semester Availability & Important Notes

  • DSBA 6390 is offered only in the Fall and Spring semesters.
  • Projects involving external partners require early coordination; students should begin outreach one semester in advance.
  • Enrollment is by instructor permission only after project approval.
  • Students may not receive practicum credit for work conducted in a paid internship; instead, they should pursue the DSBA 6400 Internship course if applicable.