Master of Computer Science in Applied Artificial Intelligence

About

Artificial intelligence is transforming the world. With a Master of Computer Science in Applied Artificial Intelligence (MCS AAI), you’ll be ready to innovate, solve complex problems, and lead the way forward. This course covers key machine learning methodologies, including supervised (decision trees, neural networks, SVM), unsupervised, and reinforcement learning. It explores challenges, computational learning theory, and algorithm evaluation. Prerequisites include linear algebra, calculus, probability/statistics, and ideally, basic AI concepts. A focus on algorithms and data structures crucial for modern database systems. It covers key aspects like buffer management, indexing, concurrency control, query optimization, and transaction management. The curriculum also explores database architectures, data models, and distributed database concepts, emphasizing security, integrity, and efficient data management techniques. A look at fundamental and advanced neural network concepts, including deep learning principles, various network architectures (e.g., convolutional, recurrent), and optimization techniques (e.g., gradient descent). It explores applications in computer vision and natural language processing, focusing on statistical learning, loss functions, and practical implementations. Canada has been experiencing significant growth in the demand for AI professionals, reflecting the country’s commitment to technological advancement and innovation. From 2018 to 2023, there was a 37% increase in need for core AI skills, particularly in areas such as machine learning, deep learning, and AI ethics and governance. Designed for students with a background in mathematics and computer science, this program offers advanced training in machine learning, neural networks, large language models, data analytics, and AI ethics. 

Career Path 

Graduate career path includes AI Engineer (Designing & Deploying Machine Learning Models in Industry), Machine Learning Scientist (Research & Development in Algorithms, Deep Learning, NLP, Computer Vision), Data Scientist (Predictive Analytics, Big Data, AI-Driven Insights), Natural Language Processing (NLP) Specialist (Chatbots, Speech Recognition, Language Models), Cybersecurity AI Specialist (Threat Detection, AI-Driven Security Systems), AI Product Manager (Strategy, Development, Deployment of AI Solutions), Computer Vision Engineer (Image Recognition, Video Analytics, Medical Imaging), Healthcare AI Specialist (Diagnostics, Personalized Medicine, Drug Discovery), Financial AI Analyst (Algorithmic Trading, Fraud Detection, Risk Modeling), Robotics Engineer (Autonomous Systems, Industrial & Service Robots), AI Ethics & Policy Specialist (Responsible AI, Governance, Compliance).