Efficient project management relies on effective governance and the smooth creation of project documents. Many organizations face challenges due to manual and inefficient processes, causing delays, errors, and non-compliance with industry standards. The current lack of AI-driven project management software exacerbates these issues, leading to significant time investments by project managers and teams in document creation, impacting project goals and decision-making timelines.

The objective of this project is to create a minimum viable product (MVP) of a project management software solution that leverages generative AI to intelligently create project management artifacts based on the nature of the project, its appropriate project lifecycle, user inputs, information, and documents.

Depending on their skills and experience students can work on:

Application Development

1. Integration to 3rd Party API (ChatGPT SDK)
2. User Management (ACL, Crud)
3. Frontend UI Development
4. Project Lifecycle Module( dashboard, artifacts, search, reports)
5. Software Testing
6. Software Documentations

Infrastructure and Network

1. Setting up cloud computing environments, virtual machines and cloud services
2. Setting up of containers and clusters
3. Setting up of CI-CD pipeline and tools
4. Network and network security
5. Network infrastructure and monitoring

Upon completion of the project, students are expected to deliver technical documentation on the area that they have worked in. These deliverables could be one of the following:

1. Technical Report: A technical report that summarizes the student's project work, including an overview of the project, methodology used, results achieved, and recommendations for future work.
2. Code Documentation: Documentation of the code written by the student, including comments within the code itself as well as a separate document that provides an overview of the code structure, key functions, and how to contribute to or modify the code.
3. Database Documentation: Documentation of the database schema, including tables, relationships, and data dictionary. This document should also include instructions on how to set up and manage the database.
4. API Documentation: Documentation of any APIs developed by the student, including endpoints, request/response formats, authentication methods, and usage examples.
5. Testing Documentation: Documentation of the testing process, including test plans, test cases, and test results. This document should also include any bugs or issues identified during testing and how they were resolved.
6. Deployment Documentation: Documentation of the deployment process, including instructions on how to deploy the application or system to a production environment. This document should also include information on how to configure and manage the deployed system.

• We will provide mentorship to students so they will have the opportunity to learn new technologies in cloud-native application development and machine learning; along with the gold standard of project management.
• Individual mentorship will be provided for a minimum of 5 hours, per student during the entire project; in addition to the feedback to be received from daily standup meetings and other scrum events.
• Students will also have access to tools and technologies that they will use to have hands-on experience in development.