Objective: To successfully transition Buyer Folio's key AI models to a more robust and scalable cloud environment provided by GCP Vertex AI.

Problem Learners Will Be Solving: Learners will be addressing the challenge of transferring AI models from a development and testing environment (Google Colab) to a production-ready cloud infrastructure (GCP Vertex AI). This includes ensuring data integrity, model performance, system integration, and compliance with security and regulatory standards.

Outcome Learners Are Expected to Achieve: By the end of the project, learners are expected to have:

1. Configured the GCP Vertex AI Environment: Set up the necessary infrastructure on GCP, including virtual machines, storage, and related services.
2. Migrated AI Models: Successfully exported and deployed the Folio Score, Co-Buyer Matching, and Property Recommendation models to Vertex AI.
3. Integrated Systems: Ensured seamless integration of the migrated models with existing Buyer Folio systems and workflows.
4. Conducted Testing: Completed comprehensive testing to validate the models' functionality, performance, and accuracy in the new environment.
5. Ensured Security and Compliance: Implemented security best practices and ensured compliance with relevant regulations.
6. Provided Documentation and Training: Created detailed documentation of the migration process and conducted training sessions for the Buyer Folio team.
7. Established Support and Maintenance: Developed a plan for post-migration support and ongoing maintenance of the models.

Project Activities

Discovery and Planning

Discovery Session:

Conduct a session to clarify project goals, requirements, and stakeholders.

Deliverable: Documented project goals, requirements, and stakeholder roles.

Environment Setup:

Configure the GCP account and necessary permissions.

Set up the Vertex AI environment.

Deliverable: Fully configured GCP Vertex AI environment.

Model Migration and Integration

Model Export and Preparation:

Export Folio Score, Co-Buyer Matching, and Property Recommendation models from Google Colab.

Deliverable: Exported model files and associated datasets.

Data Migration to GCP:

Prepare and migrate datasets to GCP storage solutions (e.g., Cloud Storage, BigQuery).

Deliverable: Successfully migrated datasets in GCP.

Model Deployment on Vertex AI:

Deploy models on GCP Vertex AI, ensuring configuration and optimization.

Deliverable: Models deployed and operational on Vertex AI.

Integration with Buyer Folio Systems:

Integrate migrated models with existing Buyer Folio systems and workflows.

Deliverable: Integrated systems with verified functionality.

Testing and Finalization

Testing and Validation:

Conduct unit tests, integration tests, and performance tests on deployed models.

Deliverable: Testing reports with results and performance metrics.

User Acceptance Testing (UAT):

Facilitate UAT with Buyer Folio team to validate model functionality.

Deliverable: UAT feedback and approval from Buyer Folio.

Documentation and Training:

Prepare comprehensive documentation covering migration steps, configuration details, and usage instructions.

Conduct training sessions for Buyer Folio team on managing models in Vertex AI.

Deliverable: Documentation and training materials.

Support and Maintenance Plan:

Establish a plan for post-migration support and ongoing maintenance of models.

Deliverable: Support plan and maintenance guidelines.

Project Deliverables

Documented project goals, requirements, and stakeholder roles.

Fully configured GCP Vertex AI environment.

Exported model files and datasets migrated to GCP.

Deployed and operational Folio Score, Co-Buyer Matching, and Property Recommendation models on Vertex AI.

Integrated systems with verified functionality.

Testing reports with results and performance metrics.

UAT feedback and approval from Buyer Folio.

Comprehensive documentation and training materials.

Support and maintenance plan.

1. Technical Guidance: Assign experienced cloud architects and engineers as mentors to guide students in understanding the application's architecture, cloud technologies, and migration best practices.
2. Infrastructure Analysis: Provide access to the existing infrastructure and relevant documentation to help students analyze the application's current state and identify potential challenges and opportunities for optimization.
3. Migration Strategy Support: Offer insights into selecting the most suitable cloud provider, choosing appropriate services, estimating resource requirements, and designing a scalable and cost-effective migration strategy.
4. Hands-On Assistance: Collaborate with students during the migration process, offering technical support, troubleshooting assistance, and real-time feedback to overcome obstacles and ensure successful execution.
5. Performance Evaluation: Review the migrated application's performance metrics, analyze optimization opportunities, and provide recommendations for further enhancements to maximize efficiency and cost savings.