Capstone Projects in AI, ML & Data Science
Build industry-grade capstone projects across Machine Learning, Deep Learning, NLP, and Data Analytics to strengthen your portfolio and job readiness.
Modules
- Loan Default Prediction (ML Pipeline)
- Face Recognition Attendance System
- Time Series Forecasting for Energy Demand
- Real-Time Emotion Detection
- Chest X-ray Image Classification
- Sign Language Translator (CNN + LSTM)
- Customer Segmentation Using Clustering
- EDA on COVID-19 & Visualization Dashboard
- Recommendation Engine (Collaborative Filtering)
- Streamlit / Flask App Deployment
- Heroku & AWS Deployment
- GitHub Repository Setup
- Pitching Your Project (Resume + LinkedIn)
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Your Learning Roadmap
Follow this path to mastery. Our AI guide leads the way.
Week 1-2: AI/ML Project Design
10 hrsSelect ML datasets, set up pipelines, and build baseline models.
Week 3: Deep Learning Projects
10 hrsCNN, RNN-based DL models with image or NLP datasets.
Week 4: Data Science Analytics
10 hrsEDA, visualization dashboards, and business insights.
Week 5: Deployment
8 hrsContainerize apps, deploy on cloud platforms (AWS/Heroku).
Week 6: Portfolio & Resume Boost
6 hrsPrepare GitHub repos, project reports, and LinkedIn highlights.
Why Capstone Projects?
- Bridge the gap between theory and real-world applications.
- Strengthen your portfolio for job interviews and hiring assessments.
- Work on real datasets and build end-to-end pipelines.
- Capstones include deployment & documentation for GitHub.
- Projects mimic real client problems from the tech industry.