Introduces students to the life cycle of information systems. Covers techniques and tools used in systems analysis and project management. Emphasizes communication skills, both written and oral, as well as team skills.

A software design and implementation experience involving a medium to large group. Students prepare requirements, specification, analysis and design documents as a team toward development of a useful software product and use the documentation to implement and test the product. The development process should consider a broad range of constraints including non-functional requirements to the software product, health and safety, sustainable development and environmental stewardship. Students manage their projects professionally, present their design work orally, and demonstrate formally that the product meets its requirements.

Review software development processes, quality models, and quality standards.  Learn about software process and product metrics and monitoring.  Explore factors influencing team productivity and product quality.  Survey ways that AI is influencing software quality practices.  Use automated testing and continuous integration in a software project environment and include exploratory and acceptance tests as part of your manual test suite. Practice software project tracking, planning, and scheduling, along with organizing and managing software development teams, performing risk analyses, and planning for change.

Maintainability and reusability analysis. Approaches to maintenance and long-term software development. Change management and impact analysis. Release and configuration management. Reengineering and reverse engineering. Regression testing.

Explore behind the scenes configuration required for web applications to achieve scalability as well as robust and maintainable performance in production environments. Design and deploy local and hybrid development environments to bridge the gap between traditional development and operations management. 

This course introduces concepts of software design patterns and architecture. The course covers principles of reuseable object-oriented programming, as well as creational, structural, and behavioural patterns. The course also covers software quality attributes, architectural tactics and patterns, designing and documenting software architecture, architecture reconstruction, architecture evaluation, and software product lines. Students will practice applying and implementing design patterns and software architecture design and evaluation in course work by developing various software systems.

Learn what it takes to develop and maintain production ready machine learning (ML) systems.  Explore the phases of the ML Operations cycle, ML Continuous Integration/Continuous Development & Deployment/Continuous Testing pipelines, testing strategies, ML training and service architectures, and hardware considerations for deep learning systems. 

Explores how full-stack software development improves the efficiency and awareness of energy systems. Introduction to software-driven paradigms in the energy sector, including transactive energy, peer to peer energy trading, and the internet of energy. Leverages distributed software technologies to implement a group research project addressing energy sustainability. Strengthens skills in sustainable and ethical software development, problem-solving, and teamwork. Learning outcomes include designing software architecture for complex energy requirements and prototyping novel solutions in energy systems. 

An independent project or literature survey. Students work under the supervision of a chosen faculty member. Students are responsible for finding a supervisor and initiating the project or literature survey. Deliverables include a comprehensive report detailing the work.