Skip to main content

Program Components

Engineering AI-based Software Systems#

The main focus of the course is on the interconnection of SE+AI and how these topics apply for AI-based systems. For example, issues related to CI/CD during development while handling large training data and managing model evolution and tracking accuracy as the AI-based software systems evolve are unique aspects that will be covered in this course. As part of the course, trainees will conduct a hands-on project with our industrial partners where they will exercise the theory learned in the course. Trainees will have the option to either study an existing AI-based system or develop a new system as part of the project. Trainees will prepare case reports about their projects. The prepared cases will be used in following years to enrich our training and will be disseminated to the international community.

Although the course will mainly focus on the engineering of AI-based systems, trainees will be asked to reflect on the social aspects and how they influenced the engineering aspects of the system.

Social Aspects for AI-based Software System#

A newly developed course that focuses on various social criteria that AI-based systems need to consider, e.g., privacy, ethics, equity, diversity, inclusion (EDI), human rights and sustainable development goals (SDG). Trainees will be introduced to the fundamental theories, normative frameworks and ethical concepts and will learn to apply them on AI-based systems. To gain applied knowledge on the concepts they are taught, trainees will be provided with existing AI-based systems, or can use their projects from the Engineering AI-based Software Systems course, and will be asked to write a report on these systems. The reports will examine the various social aspects of the system being studied and report on how these aspects have been considered (or not) in the studied systems. Trainees will be asked to come up with an ethical assessment and concrete recommendations for such systems, while considering the engineering implications of their recommendations.

Professional Development Modules#

Specialized modules that focus on professional skills in the context of AI-Software Systems will be provided to trainees. This includes specialized modules on professional skills (e.g., dissemination and presentation skills, commercialization and entrepreneurship, communication and explainability) and aspects of engagement and relation-building with communities and diverse stakeholders. In addition to newly developed modules, trainees will have access to a curated list of relevant professional development modules that fit the SE4AI CREATE program offered through the host universities (e.g. Concordia’s GradProSkills, Queen’s Smith School of Business, Centre for Teaching and Learning, University Research Services, and School of Graduate Studies). Trainees are given full flexibility to choose the modules that better fit their expected future career aspirations (e.g., academic researcher versus entrepreneur).

Industrial Embedding#

SE4AI CREATE trainees will be offered the opportunity to go on one or more internships with our industrial partners. Master’s trainees will typically serve a single four-month internship, typically after their second term in the program. PhD trainees will typically serve two four-month internships. Trainees will be supported by their academic supervisors and the relevant contact at the host partner.

Industry Webinars or Seminars#

All trainees will have the opportunity to present at least one online webinar and/or an on-site seminar to one or more industrial partners.

The seminars will:

  • Provide trainees with hands-on real-life presentation experience to an academic and non-academic audience.
  • Provide trainees with an opportunity to expand their professional network for post-graduation hiring opportunities.
  • Communicate some of the academic innovations to practitioners and academics,

Specialization Courses#

Trainees of the SE4AI CREATE program will take one or more specialization course from a curated list of courses on SE, AI, and Social concepts. The exact number of specialization courses depends on the trainee’s home institution and program.

Specialization courses include courses in (not a complete list): Software Analytics, Software Quality, Software Testing, Product Lines, Software Re-engineering, Software Architecture, Advanced Concepts in Cloud Computing, Neural Network, Reinforcement Learning, Deep Learning, Advanced AI, Ethics, Development and Global Engineering, and EDI in STEM. The aforementioned list is a preliminary list that will change and evolve. Protocols are already in place to allow trainees to obtain credit for courses taken at non-home institutions to maximize the number of specialization courses available to our trainees. The exact specialization course(s) a trainee will take will be determined in consultation with their supervisor.

Hands-on Leadership and Mentorship Training#

To position trainees to be successful and socially responsible leaders in their field the SE4AI CREATE incorporates hands-on leadership and mentorship training. This training is achieved through a multitude of mechanisms. Trainees will serve as mentors-in-training (MIT) along supervisors to more junior trainees. For example, PhD students and postdocs can serve as MITs to undergrad and MSc, and PhD trainees, respectively. MITs will be trained to incorporate EDI principles in leadership, including equity aspects in collaboration, evaluation and assessment (e.g. counteracting gender, racial, cultural and language bias), as well as equitable modes of collaboration (e.g. monitoring speaking time in group meeting to give everybody the opportunity to participate and contribute). To ensure a comprehensive training of the MITs, they will be given the option to mentor trainees in all aspects, i.e., proposing research projects, supporting progress, as well as advising them on technical writing, presentation, and research methodology issues.