Applied AI & Data Science Program
MIT Professional Education · AAIDSP Jan 2026 · Cohort D
Elective: Deep Learning Project ·
Capstone: Deep Learning — Facial Emotion Detection
Projects Completed
FoodHub Data Analysis
Score: 60 / 60
Foundations for Data Science
EDA, data cleaning, outlier detection (IQR method), and statistical analysis on a food delivery platform dataset. Uncovered ordering patterns, top-performing cuisines, and key drivers of delivery time.
SVHN Digit Recognition
In Progress
Deep Learning Project
Built and benchmarked four models (2 ANN + 2 CNN) to classify Street View house numbers. Applied data-driven spatial masking, full EDA, multi-model comparison, and detailed error analysis on misclassified images.
Facial Emotion Detection
Capstone
Capstone Project · Upcoming
Deep learning model for real-time facial emotion classification using CNN-based architectures. Goal: accurate multi-class emotion recognition from facial image data.