Graduate capstone · MS Data Analytics
DA 790: Data Analytics Capstone
Build the project you'll be hired for. One semester, one real problem, worked end to end with advanced analytics methods under my direction — and a finished piece of work you can defend line by line in an interview.
Why this capstone
Not one regression on a clean dataset.
DA 790 is the culminating experience of the DA program. If you do your capstone with me, you will take a business problem you actually care about — in hospitality, healthcare, education, or a field of your choosing — and work it through the full CRISP-DM cycle: business understanding, data preparation, and the application and interpretation of advanced techniques. The strongest projects combine methods: statistical modeling, machine learning, and emergent AI approaches such as large language models and computer vision, chosen to fit the problem rather than the other way around.
A reproducible analysis: a repository or notebook that regenerates your results from raw data — your portfolio piece
A short paper documenting the work from problem framing to interpretation
A formal Zoom presentation to me and invited DA students
The kind of projects I advise
Your topic is yours. This is the ambition I look for.
Predicting hotel booking cancellations with gradient boosting plus an LLM classifier over guest reviews. Forecasting emergency department demand with time-series models. Segmenting school districts with clustering plus an LLM pipeline that summarizes public board minutes. I treat the capstone like an independent study: you define the topic, choose the methods, and drive the process. I provide direction, feedback, and a structured semester schedule with clear checkpoints, so you always know whether you are on track.
Learning outcomes
What you will be able to do
Who it is for. MS Data Analytics students in their final semester who want a portfolio project they can defend line by line in an interview.
Prerequisites. Students in the UNLV MS Data Analytics program who have agreed a topic with me and registered for DA 790 with Dr. Taghva, naming me as project advisor.
Tools. Student's choice, matched to the problem. Format. By arrangement with the advisor, Fall 2026 (August 24 to December 12).
Frame a real business problem and work it through the full CRISP-DM cycle
Choose and apply advanced methods that fit the problem: statistical modeling, machine learning, language models, or computer vision
Produce a reproducible analysis that regenerates results from raw data
Write a short paper from problem framing to interpretation
Defend the work in a formal presentation
Interested?
Start here
- 01Email me
Write to ryoung@unlv.edu with DA 790 in the subject line and a sentence or two about what you might want to work on. No polished proposal needed for a first conversation.
- 02We talk it through
We will discuss your idea, the data it needs, and whether the scope is right for one semester.
- 03Register with Dr. Taghva
When we agree to work together, register for DA 790 with Dr. Taghva and indicate that I will be acting as your project advisor.
- 04Get the student page
I will give you access to the student page with the full semester schedule, deliverable requirements, and our working agreement.
Watch
Lectures and walkthroughs
Selected recordings from this course and related work are on my YouTube channel. WebCampus remains the official home for required course videos.
Current DA 790 students
Already working with me?
If I am advising your capstone, everything that governs the semester — the week-by-week schedule, deliverable requirements, evaluation criteria, and our working agreement — lives on the student page. You received the password when we agreed to work together. Capstone projects that need GPU time can request it through student resources.
Fall 2026 office hours are Mondays and Wednesdays from 3:00 to 4:00 p.m. in BEH 328. Friday meetings are available by appointment on Zoom.