Practicum Pathway – HCIP 6250 Problem-Solving in Healthcare Analytics

Program Overview

The Practicum pathway is a hands-on, project-based capstone experience designed for students who wish to apply their technical and analytical skills to real-world problems without completing a formal internship. Working in small teams, students select an industry or organization of interest and, with instructor approval, identify a data-driven health or healthcare challenge and design an end-to-end analytics solution. Projects 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 requires a competitive application and company selection process.

Throughout the practicum, students conduct meaningful data analysis and visualization using open-source tools (e.g., Python, R) and commonly used proprietary visualization platforms (e.g., Tableau, Power BI). Students also develop foundational project management skills, collaborate effectively in teams, and enhance their professional profiles by building a polished CV and LinkedIn presence. This practicum provides a rigorous applied learning experience that strengthens professional readiness, teamwork, communication, and problem-solving skills within a data-centric healthcare environment.

Practicum Requirements Summary

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

  • Completion of all prerequisite coursework and instructor approval prior to enrollment
  • Participation in team-based project selection, scoping, and implementation
  • Delivery of a comprehensive final presentation and a written project report demonstrating technical rigor and actionable insights

The 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 Authorization: Receive final approval to proceed with registration in HCIP 6250.

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 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 healthcare or technical impact.
  • Develop Insights & Recommendations: Translate analytical results into actionable 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 health analytical 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 analysis, reports or visualizations before final grading.

Semester Availability & Important Notes

  • HCIP 6250 is offered only in the Fall and Spring semesters.
  • The course must be taken in the last semester, and with the instructor’s permission only.
  • Students may not receive practicum credit for work conducted in a paid internship; instead, they should pursue the HCIP 6400 Internship course if applicable.