This project aims for students to aid in the development of an ML-driven web application and also to engage students in the critical business aspects of technology development such as contract negotiations and client-facing support. The objective is to simulate a real-world environment where students must understand the development of a functional web application that utilizes ML technologies to address specific user needs and industry problems but also navigate the business challenges associated with bringing a tech product to market. By the end of the project, students will have a comprehensive understanding of the intersection between technology innovation and business strategy, showcasing their understanding how a viable product will be ready for potential investment or market launch.

Technical Design & Development:

• Task: Work on the web application's architecture and integrate Machine Learning (ML) models to enhance its functionality.
• Deliverable: Upload a document summarizing outline of the technical architecture
• Filename for Deliverable: StudentName_TechDesignDevelopment.pdf

Client Support Strategy:

• Task: Create a comprehensive client support plan that includes customer service policies, and support infrastructure.
• Deliverable: Upload a PDF of the client support strategy, ensuring it addresses user satisfaction and engagement.
• Filename for Deliverable: StudentName_ClientSupportStrategy.pdf

1. Each student will be paired with an experienced staff member who will serve as a mentor throughout the project.
2. Mentors will schedule weekly check-ins to discuss progress, challenges, and provide guidance.
3. Training sessions will be hands-on to enhance practical understanding.
4. Students will have access to necessary software tools like web development IDEs, design tools, and ML platforms.
5. Subscriptions to online resources and tools will be provided as required.
6. Students will be given access to datasets necessary for ML model training and testing, ensuring compliance with data privacy regulations.
7. If proprietary or sensitive data is involved, data handling training will be provided.
8. Understanding that students may be balancing studies, flexible hours will be offered to accommodate their schedules.