Solving Problems with Algorithms and AI
Main contact
Timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
-
October 18, 2025Data Understanding & Requirements Analysis
-
October 25, 2025Data Preparation & Preprocessing
-
November 1, 2025Initial Algorithm Design & Implementation
-
November 8, 2025Model Refinement & Iteration
-
December 4, 2025Program end
Timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
Deliverable: A formal document submitted to the instruction team and the company. This should include a summary of the project's goals, a clear list of functional and non-functional requirements gathered from the company, and a proposed team plan for the remaining milestones.
Purpose: This milestone ensures that students have a solid understanding of the company's needs from the very beginning.
-
October 18, 2025Data Understanding & Requirements Analysis
Explore datasets and project problem space.
Identify challenges related to the 4Vs (Volume, Variety, Velocity, Veracity).
Define initial approach and success criteria.
-
October 25, 2025Data Preparation & Preprocessing
Perform data cleaning, transformation, and integration.
Document assumptions, challenges, and early insights.
-
November 1, 2025Initial Algorithm Design & Implementation
Evaluate models or analyses for accuracy and relevance.
Refine approaches based on findings and company feedback.
Write necessary code to automate data analysis and visualization.
Write document to reflect on initial analysis & modeling.
-
November 8, 2025Model Refinement & Iteration
Optimize algorithm performance and scalability.
Compare alternative approaches, gather partner feedback.
-
November 15, 2025Validation & Evaluation
Present results to company and/or class.
Submit final deliverables and reflect on lessons learned.
-
November 22, 2025Deliverable Development
Finalize documentation, reports, visualizations, and code.
Prepare presentation/demo for company partner.
-
December 3, 2025Presentation & Submission
Deliver final report, code, and presentation to company.
Reflect on outcomes, lessons learned, and possible extensions.
-
December 4, 2025Program end
Program scope
Categories
Software development Machine learning Artificial intelligenceSkills
computational thinking algorithms algorithm design problem solving artificial intelligence big data large language modeling machine learning methods computer systems artificial intelligence systemsOur graduate learners bring strong skills in algorithm design, data structures, and computational problem-solving. They are capable of analyzing complex challenges, developing efficient solutions, and applying modern approaches—including AI and big data techniques—to real-world problems. Companies can expect motivated learners who can deliver computational thinking-oriented insights, prototypes, and optimized solutions to support decision-making and innovation.
Learners
Expected Outcomes for Learners:
Learners will strengthen their ability to analyze complex problems, design and implement efficient algorithms, and apply modern data structures, databases, and AI techniques. They will gain hands-on experience working with real-world data and industry challenges, improving both technical and professional skills.
Deliverables for the Employer:
Employers can expect clear documentation of problem analysis, algorithm design, and solution implementation, along with data-driven insights, computational thinking, prototypes, or visualizations tailored to the project. Final deliverables may include a written report, an application form, code, and a presentation summarizing findings and recommendations.
Project timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
-
October 18, 2025Data Understanding & Requirements Analysis
-
October 25, 2025Data Preparation & Preprocessing
-
November 1, 2025Initial Algorithm Design & Implementation
-
November 8, 2025Model Refinement & Iteration
-
December 4, 2025Program end
Timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
Deliverable: A formal document submitted to the instruction team and the company. This should include a summary of the project's goals, a clear list of functional and non-functional requirements gathered from the company, and a proposed team plan for the remaining milestones.
Purpose: This milestone ensures that students have a solid understanding of the company's needs from the very beginning.
-
October 18, 2025Data Understanding & Requirements Analysis
Explore datasets and project problem space.
Identify challenges related to the 4Vs (Volume, Variety, Velocity, Veracity).
Define initial approach and success criteria.
-
October 25, 2025Data Preparation & Preprocessing
Perform data cleaning, transformation, and integration.
Document assumptions, challenges, and early insights.
-
November 1, 2025Initial Algorithm Design & Implementation
Evaluate models or analyses for accuracy and relevance.
Refine approaches based on findings and company feedback.
Write necessary code to automate data analysis and visualization.
Write document to reflect on initial analysis & modeling.
-
November 8, 2025Model Refinement & Iteration
Optimize algorithm performance and scalability.
Compare alternative approaches, gather partner feedback.
-
November 15, 2025Validation & Evaluation
Present results to company and/or class.
Submit final deliverables and reflect on lessons learned.
-
November 22, 2025Deliverable Development
Finalize documentation, reports, visualizations, and code.
Prepare presentation/demo for company partner.
-
December 3, 2025Presentation & Submission
Deliver final report, code, and presentation to company.
Reflect on outcomes, lessons learned, and possible extensions.
-
December 4, 2025Program end
Project examples
Data Optimization: Designing algorithms to optimize logistics, scheduling, or resource allocation.
Big Data Analysis: Applying algorithms to extract insights from large or complex datasets.
AI-Enhanced Solutions: Implementing machine learning or AI techniques for prediction, classification, or recommendation.
Search & Matching Systems: Building efficient search, ranking, or recommendation algorithms for real-world applications.
Network & Graph Analysis: Applying graph algorithms to social networks, transportation systems, or supply chains.
Data Structure Design: Developing customized data structures for performance-critical applications.
Process Automation: Creating algorithmic workflows that improve efficiency or reduce manual effort.
Visualization & Reporting Tools: Turning raw data into meaningful dashboards and visual insights.
Additional company criteria
Companies must answer the following questions to submit a match request to this program:
Main contact
Timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
-
October 18, 2025Data Understanding & Requirements Analysis
-
October 25, 2025Data Preparation & Preprocessing
-
November 1, 2025Initial Algorithm Design & Implementation
-
November 8, 2025Model Refinement & Iteration
-
December 4, 2025Program end
Timeline
-
September 23, 2025Program start
-
October 2, 2025Project Brief & Requirements Report
Deliverable: A formal document submitted to the instruction team and the company. This should include a summary of the project's goals, a clear list of functional and non-functional requirements gathered from the company, and a proposed team plan for the remaining milestones.
Purpose: This milestone ensures that students have a solid understanding of the company's needs from the very beginning.
-
October 18, 2025Data Understanding & Requirements Analysis
Explore datasets and project problem space.
Identify challenges related to the 4Vs (Volume, Variety, Velocity, Veracity).
Define initial approach and success criteria.
-
October 25, 2025Data Preparation & Preprocessing
Perform data cleaning, transformation, and integration.
Document assumptions, challenges, and early insights.
-
November 1, 2025Initial Algorithm Design & Implementation
Evaluate models or analyses for accuracy and relevance.
Refine approaches based on findings and company feedback.
Write necessary code to automate data analysis and visualization.
Write document to reflect on initial analysis & modeling.
-
November 8, 2025Model Refinement & Iteration
Optimize algorithm performance and scalability.
Compare alternative approaches, gather partner feedback.
-
November 15, 2025Validation & Evaluation
Present results to company and/or class.
Submit final deliverables and reflect on lessons learned.
-
November 22, 2025Deliverable Development
Finalize documentation, reports, visualizations, and code.
Prepare presentation/demo for company partner.
-
December 3, 2025Presentation & Submission
Deliver final report, code, and presentation to company.
Reflect on outcomes, lessons learned, and possible extensions.
-
December 4, 2025Program end