Capstone: AI Innovation Project

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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

?Master Study NLP Fundamentals: The Foundation of Language Understanding in AI

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