Excelerate × Rochester Institute of Technology
AI-Powered Data Analysis Star Performer
Verified recognition for turning a large student engagement dataset into a clear machine-learning-backed decision story.
8,558
Records analyzed
95%
Overall score
100%
Peer evaluation
1
Predictive model built
360° Evaluation
Three perspectives · averaged- 84%
- Self
- 100%
- Peer
- 100%
- Managerial
- 95%
- Overall average
What the credential represents
The work covered data cleaning, exploratory analysis, cohort comparison, and Random Forest modeling to identify the strongest drivers of student participation.
- Star Performer recognition from the program
- Overall score recorded at 95%
- Random Forest feature importance used to prioritize findings
Evidence of analytical practice
The portfolio includes a data-quality review, a detailed cleaning and visual-insights report, a model-evaluation report with charts, and a final presentation. The recorded dashboard recommendation is presented as a proposed next step, not a deployed product.
- Week 1: data understanding and data-quality review
- Week 2: cleaning, feature engineering, and visual insights
- Week 3: Random Forest evaluation, feature importance, and participation heatmap
- Week 4: final program-insights presentation
Why it matters for executive support
This proof demonstrates disciplined research, structured reporting, pattern recognition, and the ability to translate complex information into a decision-ready summary.
Verified proof
Open the evidence
Use the links below to verify the credential or review the supporting work directly.