Artificial Intelligence and Machine Learning-2025/2026
| Level 1 | ||||
| Take all of the following Mandatory Courses: | ||||
| ACAD-6002 | Graduate Success Strategies | 1 | ||
| This course presents and helps to develop some of the skills required to achieve academic and career success for graduate students. Areas of focus include college resources, study skills, and time management among other skills. The importance of Academic Integrity will be a main focus. | ||||
| MGMT-6135 | Essential Skills for Mgmt Professionals | 4 | ||
| This course applies the principles of professional communication in the Canadian industry. It explores intercultural communication and the characteristics of diverse worldviews. Students will identify issues involved in communications and global diversity, and develop necessary skills to create professional documents that adhere to Canadian standards. Through presentations, case studies and thematic readings, students will learn written, verbal and nonverbal skills that are essential to business management, while maintaining sensitivity to issues involving geographic, cultural, gender and ability diversity. Throughout the course, students will work both individually and in groups to build their knowledge and skills needed to demonstrate professional communication within Canadian businesses. | ||||
| DEVL-6024 | Career Planning | 1 | ||
| This course introduces students to the importance of personal career management. Students will learn about, practice and use career (job) search, resume writing and interview skills. Students will also complete an individual career management project. | ||||
| INFO-6120 | Databases-Intro | 4 | ||
| An introduction to relational database system design and development, by creating a variety of simple databases, based upon typical business requirements. Students build complete database solutions incorporating multi-table relational databases, forms, reports, queries, and test data. Students will also be introduced to the Structured Query Language. | ||||
| INFO-6143 | Python Programming | 4 | ||
| This course is an introduction to the fundamentals of procedural / object-oriented programming using the Python language. Problem analysis and algorithmic thinking skills will be emphasized. Content will include data types, variables, sequence, selection, repetition, arrays, methods, and the use of an integrated development environment (IDE) tool for writing, testing and debugging code. | ||||
| INFO-6144 | JavaScript Programming | 4 | ||
| This course will introduce students to both client-side and server-side JavaScript. Students will be introduced to object-oriented programming concepts using the Document Object Model (DOM) and various HTML controls, including accompanying CSS style principles. Object creation and customization, exception-handling, event handling, and testing and debugging techniques will be covered. | ||||
| INFO-6145 | Data Science & Machine Learning | 3 | ||
| This course covers the fundamental principles and history of data science and machine learning. In addition, students will explore how to use modern tools to reorganize and restructure large amounts of unstructured textual data. | ||||
| Level 2 | ||||
| Take all of the following Mandatory Courses: | ||||
| INFO-6146 | Tensorflow & Keras With Python | 4 | ||
| This course provides students with an introduction to the Google TensorFlow platform through the Python Keras framework, including a review of Python and related development tools. Coursework includes deep learning models utilizing classification and regression, unsupervised clustering, and HMMs (Hidden Markov Models). | ||||
| INFO-6147 | Deep Learning With Pytorch | 3 | ||
| This course covers the theoretical and practical applications of state-of-the art deep learning for various datasets (e.g., tabular, image, text, time series). An open-source software stack (i.e., Python, PyTorch, PyTorch Lightning) will be utilized for this course. | ||||
| INFO-6148 | Natural Language Processing 1 | 4 | ||
| This course introduces Natural Language Processing (NLP) and its key concepts. Students will utilize the spaCy Python library to solve real world text processing problems. This will include the application of text-processing pipelines, the extraction of linguistic features, word vectors, intent recognition and other language processing strategies. | ||||
| INFO-6149 | Machine Learning Security | 3 | ||
| In this course, students will discover how to mitigate the major kinds of machine learning security risks, including compromises of unsupervised learning systems utilizing strategies such as evasion attacks, data poisoning and model stealing. | ||||
| INFO-6150 | Data Mining & Analysis | 3 | ||
| Data mining is a powerful tool used to discover patterns and relationships in data. Students learn how to apply data mining principles to the dissection of large complex data sets, including those in very large databases or through web mining. Students also explore, analyze and leverage data and turn it into valuable, actionable information for an organization. | ||||
| INFO-6151 | Data Visualization for Machine Learning | 3 | ||
| This course delves into the principles and methodologies of data visualization driven by machine learning using Python. Participants will grasp the art of crafting informative and compelling visualizations throughout the entire machine learning journey, spanning from data exploration and preparation to the interpretation of model evaluations. | ||||
| COOP-1020 | Co-operative Education Employment Prep | 1 | ||
| This workshop will provide an overview of the Co-operative Education consultants and students' roles and responsibilities as well as the Co-operative Education Policy. It will provide students with employment preparatory skills specifically related to co-operative education work assignments and will prepare students for their work term. | ||||
| Level 3 | ||||
| Take all of the following Mandatory Courses: | ||||
| INFO-6152 | Deep Learning With Tensorflow & Keras 2 | 4 | ||
| In this course, students learn advanced techniques for designing and deploying cutting edge technologies such as Convolutional Neural Networks, Recurrent Neural Networks and Generative Adversarial Networks using TensorFlow and Keras. | ||||
| INFO-6153 | Natural Language Processing 2 | 4 | ||
| Building on the work done in the previous NLP course, students will focus on variations of the Transformer architecture, utilizing frameworks such as BERT (Bidirectional Encoder Representations from Transformers) and GPT-3 (Generative Pre-trained Transformer 3) to create more sophisticated NLP solutions. | ||||
| INFO-6154 | Machine Learning Optimization Strategies | 3 | ||
| In this course, students will be able to experiment with various process optimization practices with a goal to improve the performance of different learning models. From a practical perspective, students will have the opportunity to work with state-of-the-art NVIDIA GPU hardware systems to accelerate model learning execution. | ||||
| INFO-6155 | Social Media Analytics | 3 | ||
| This course introduces the core concepts of social media marketing, content production, and analytics. Beginning with an introduction to social media in business, students will move on to utilizing various AI/ML tools to build, train and apply models that will produce content and analyze marketing campaigns to generate useful social, marketing, and business insights. | ||||
| INFO-6156 | Capstone Project | 6 | ||
| This project-based course is designed to allow students to demonstrate the various software development skills they have been exposed to in previous course offerings. Students are responsible for the entire project development lifecycle and will work in project teams using various tools to develop a single comprehensive solution. | ||||
| Program Residency | ||||
| Students must Complete a Minimum of 16 credits in this program at Fanshawe College to meet the Program Residency requirement and graduate from this program | ||||