Preferred Career Domain Predictor

A machine learning-based tool to help students discover suitable career domains based on their academic background, interests, and skillsets.

Team

• Aashutosh Mishra
• Gaurav Upadhyay

Problem Statement

can we predict a student's preferred career domain using personal and academic attributes?
the goal is to recognize patterns and recommend likely-fit career domains—not to prescribe exact outcomes.

Dataset

• collected via google form (277 valid responses)
• features: cgpa, department, skill ratings, career preferences, influences, higher studies, etc.
• cleaned and transformed into 16 relevant features

Models and Accuracy

model	accuracy	precision	recall	f1-score
random forest	0.73	0.77	0.73	0.74
mlp (neural net)	0.71	0.74	0.71	0.72
knn classifier	0.70	0.80	0.70	0.72
catboost	0.70	0.75	0.70	0.69
xgboost	0.62	0.64	0.62	0.62

Random forest performed best in terms of accuracy and interoperability.

Try it out

• Deployed app: demo

Key Learnings

• complete ml pipeline implementation
• real-world data handling and transformation
• model selection and evaluation
• web app deployment using streamlit

Limitations

• small sample size
• subjective survey responses
• no actual career outcome data
• limited diversity in dataset