Advanced Diploma in Software Engineering Technology - Artificial Intelligence (Optional Co-op)
DURATION
3 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
CAD 3,114 / per year *
STUDY FORMAT
On-Campus
* tuition 2 semesters Canadian students; CAD 16,704 - tuition 2 semesters International students
Key Summary
Introduction
Program Details
- Program Code: 3402
- School: School of Engineering Technology and Applied Science
- Credential: Ontario College Advanced Diploma
- Program Type: Post-secondary program
- Program Length: 3 years/ 6 semesters
- Location: Progress Campus
Through collaboration with industry, the Software Engineering Technology – Artificial Intelligence (AI) program will provide our students with skills in state of art design and AI application development technologies. Software is taking the planet by storm and AI-driven technologies are at the center of it. AI’s global economic impact is expected to reach trillions by 2025. AI is set to become the new database for next-generation applications.
Our Software Engineering Technology – Artificial Intelligence program aligns well with the newest technology trends in the software industry, namely “Augmented Analytics,” “AI-Driven Development,” and “Autonomous Things.” The coursework emphasizes modern software design and AI frameworks, machine learning, data visualization, big data fundamentals, natural language processing, image recognition, recommender systems, software bots, digital ethics, and privacy guidelines within AI solutions.
To round out the technical focus of the curriculum, the Software Engineering Technology – Artificial Intelligence program includes two software development projects. For these real-world business applications, you put into action all the technical, systems, and business skills acquired during your courses to build AI-enhanced software solutions for automating, classifying, predicting, recommending, and understanding processes and data.
Please note: This program is available with a co-op option (program #3412). Qualified students transfer to the co-op option in Semester 3. A fast-track version of this program is available to qualified college or university graduates with a background in software. Fast-track applicants gain direct admission into Semester 3 of this three-year program and receive their advanced diploma in four semesters (program #3422). The co-op option is available for fast-track students with four semesters plus two work terms (program #3432). This program is available in a fully online version (program #3462) with a co-op option (program #3442). The fast-track programs are also available in a fully online version (program #3472), and, online co-op (Program #3452).
The co-op option in this program will provide you with the opportunity to gain hands-on experience while you complete two work terms as an employee in the field. This experience not only allows you to put classroom learning into practice, but will also provide valuable contacts for your future career.
To participate in programs with optional co-op, students will typically complete an application process in the first semester of their studies, and if academically qualified, may be admitted to the co-op program. Academically qualified students who are accepted into the program will register for the co-op preparation course as scheduled.
When you graduate, your diploma will highlight the co-op credential.
Co-op Requirements
- Minimum of 80% of courses completed from year one
- A minimum C (60%) grade in COMM-170/171
- A cumulative GPA of 2.5 or higher (this must be maintained for the duration of the program)
- Students must be legally eligible to work in Canada
- Students who meet the above prerequisites will apply to transfer to the co-op program as scheduled
Note: Meeting the minimum co-op program requirements does not guarantee admission into the co-op program.
Admissions
Curriculum
Semester 1
- COMM-160/161 College Communication 1
- COMP-100 Programming I
- COMP-120 Software Engineering Fundamentals
- COMP-213 Web Interface Design
- GNED General Education Elective
- MATH-175 Functions and Number Systems
Semester 2
- COMM-170/171 College Communication 2
- COMP-122 Introduction to Database Concepts
- COMP-123 Programming 2
- COMP-125 Client-Side Web Development
- COMP-225 Software Requirements Engineering
- COMP-301 Unix/Linux Operating Systems
- MATH-185 Discrete Mathematics
Semester 3
- COMP-228 Java Programming
- COMP-229 Web Application Development
- COMP-237 Introduction to Artificial Intelligence
- COMP-246 Software Systems Design
- GNED-500 Global Citizenship: From Social Analysis to Social Action
- MATH-210 Linear Algebra and Statistics
Semester 4
- COMP-214 Advanced Database Concepts
- COMP-216 Networking for Software Developers
- COMP-247 Supervised Learning
- COMP-254 Data Structures and Algorithms
- COMP-311 Software Testing and Quality Assurance
- ENGL-253 Advanced Business Communications
Semester 5
- CNET-307 IT Project Management
- COMP-251 Big Data Tools for Machine Learning
- COMP-255 Business and Entrepreneurship for Software Engineering Technology
- COMP-257 Unsupervised and Reinforcement Learning
- COMP-258 Neural Networks
- COMP-304 Mobile Apps Development
Semester 6
- COMP-261 AI Ethics and Data Governance
- COMP-262 Natural Language Processing and Recommender Systems
- COMP-263 Deep Learning
- COMP-264 Cloud Machine Learning
- COMP-313 Software Development Project 2
- EMPS-102 Employment Skills 2
- GNED General Education Elective
Program Outcome
Program Highlights
- Software Engineering Technology – Artificial Intelligence courses incorporate the use of leading technology geared to industry standards.
- Project-based learning is a key component of the offering.
- Knowledgeable and approachable faculty members have diverse industry experience and academic credentials.
- This program is also delivered in a version that includes a co-op option. Students who choose this version (program #3412) are introduced to some of the biggest names in the industry with whom they are able to network in addition to gaining experience that puts them ahead of the competition — before they even graduate.
- Graduates from the program may apply for certified membership to their provincial engineering technology association.
Program Vocational Learning Outcomes
Program Vocational Learning Outcomes describe what graduates of the program have demonstrated they can do with the knowledge and skills they have achieved during their studies. The outcomes are closely tied to the needs of the workplace. Through assessment (e.g., assignments and tests), students verify their ability to reliably perform these outcomes before graduating.
- identify, analyze, design, develop, implement, verify and document the requirements for a computing environment.
- diagnose, troubleshoot, document and monitor technical problems using appropriate methodologies and tools.
- analyze, design, implement and maintain secure computing environments.
- analyze, develop and maintain robust computing system solutions through validation testing and industry best practices.
- communicate and collaborate with team members and stakeholders to ensure effective working relationships.
- select and apply strategies for personal and professional development to enhance work performance.
- apply project management principles and tools when responding to requirements and monitoring projects within a computing environment.
- adhere to ethical, social media, legal, regulatory and economic requirements and/or principles in the development and management of computing solutions and systems.
- investigate emerging trends to respond to technical challenges.
- analyze and define the specifications of a software system based on requirements engineering processes and techniques.
- design, develop, integrate, document, implement, maintain and test software systems based on software engineering methodologies, modern programming paradigms and frameworks.
- analyze, evaluate and apply software engineering design techniques, data structures, algorithms, and patterns to the implementation of a software system.
- design, model, implement, optimize and maintain a database and apply data mining concepts and tools for decision making.
- develop, maintain and deploy software systems to resolve networking issues.
- build automated software solutions through the analysis, evaluation, and integration of intelligent systems into various applications.
- design and implement appropriate testing, verification and evaluation procedures to assess software quality and improve software performance.
- create innovative and entrepreneurial concepts that lead to the development of new software products and/or the enhancement of existing ones.
Career Opportunities
Future Alumni
The graduates of the Software Engineering Technology – Artificial Intelligence program can work on all software projects that involve intelligent use of data, such as machine learning, natural language processing, recommendation systems, image recognition, data analytics, big data, and more. The graduates can find employment in various financial, health, social and multimedia, insurance, telecommunications, large retail, tech start-up, transportation, and government companies and institutions.
Companies Offering Jobs
IBM Canada, Manulife, CIBC, RBC, BMO, Bell Canada, Scotiabank, TD, Toronto Transit Commission (TTC), American Express, Toronto Stock Exchange, Canadian Tire, Top Hat, SOTI, and more.
Career Outlook
- AI Developer
- Software Engineer
- Machine Learning Engineer
- Data Analytics Developer
- Software tester
- Mobile application developer
- Computer programmer
- Systems analyst
- Data analyst
- Data Science Developer
- Database Developer
- Web application developer
- Applications or software support