Capstone: AI Innovation Project
artificial-intelligence-ai.
Course Modules:
Module 1: Project Planning and Problem Selection
Identifying a real-world challenge or business need
Aligning your project with your AI specialization
Defining scope, objectives, and success metrics
Module 2: Proposal Development and Approval
Writing a project proposal and problem statement
Building a feasibility analysis and stakeholder map
Getting instructor feedback and proposal sign-off
Module 3: Data Collection and Preprocessing
Sourcing datasets or generating synthetic data
Cleaning, labeling, and feature engineering
Exploratory data analysis and validation
Module 4: Model Design and Selection
Choosing appropriate ML/DL models for your use case
Building custom architectures or using pretrained models
Justifying algorithm choice with design reasoning
Module 5: Model Training and Evaluation
Training your model using best practices
Evaluating with cross-validation and appropriate metrics
Fine-tuning and hyperparameter optimization
Module 6: System Integration and Deployment
Packaging your solution as an app, API, or dashboard
Integrating with databases or front-end interfaces
Optional: Deploying on cloud or mobile platforms
Module 7: Usability, Ethics, and Bias Review
Ensuring accessibility and fairness in your solution
Testing against ethical frameworks and social impact
User testing, feedback, and refinement
Module 8: Business Case and Value Proposition
Market need or organizational benefit
ROI and impact forecasting
Optional: Startup pitch deck preparation
Module 9: Presentation and Demo Day
Preparing final documentation and demo
Delivering a compelling video or live pitch
Peer review and Q&A from instructors/mentors
Module 10: Final Submission and Certification
Submit final project files, codebase, and documentation
Receive personalized feedback and evaluation
Earn your Master Study AI Certification with Capstone distinction
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