Program Overview

The one-year Artificial Intelligence (AI) and Machine Learning post graduate co-op education program will focus on teaching students how to build, manage and administer systems that analyze big data and convert it into an autonomous task. If you're ready to build a highly in-demand skillset in artificial intelligence and machine learning, then this certificate will provide you with everything you need to hit the ground running in this fast-growing field of information technology.

Program Details

Program Code
Ontario College Graduate Certificate
30 Weeks
Start Dates

Full Time Offerings

2024 January
2024 May
2024 September
2025 January
2025 May

Your Learning Experience

AIM2 is only available to domestic students. A version for international students can be found at AIM1


The AI and Machine Learning one-year graduate certificate program is designed for students with software development backgrounds who want to specialize in this highly demanded field of information technology.


With a focus on deep learning neural networks, students will discover how to design and deploy cutting-edge technologies such as convolutional neural networks, recurrent neural networks and generative adversarial networks in areas such as healthcare, bioscience, manufacturing, financial services and supply chain sectors. Students will also work with mainstream technologies such as Google's TensorFlow to train various machine learning models using big data and state-of-the-art hardware.


Not only will students gain extensive technical knowledge of AI and Machine Learning, but they will also learn and apply skills in project management, communication and teamwork through hands-on, industry-based research projects and a comprehensive in-class capstone project. 


In their final semester, students will complete a paid, co-operative work term with an industry partner.

Laptop and technical requirements


Please note, this program requires a laptop. It is recommended that students use a PC laptop vs. a Mac laptop, as Windows is required to be able to load program-specific software. For more information on specific requirements, visit the Laptop Requirements page on the Fanshawe CONNECTED website.


Career Information

Fanshawe’s AI and Machine Learning program will prepare graduates to take advantage of the growing opportunities in the AI and Machine Learning field of information technology. Graduates can expect to be hired as the following:

  • AI Developer/Programmer - developing artificial intelligence software and applications, and programming systems based on the data collected and analyzed
  • Machine Learning Developer - developing artificial intelligence systems that use big data to research, develop, and generate algorithms to learn and make predictions
  • Data Analyst - collecting, processing and tracking down statistical information from datasets
  • Computer Systems Analyst - maintaining and upgrading existing systems and designing new computer systems and frameworks

Program Coordinator:

Jim Cooper

Admission Requirements

An Ontario College Diploma, an Ontario College Advanced Diploma, a Degree, or equivalent in Computer Science or a related field with software development education.

English Language Requirements

English Language Requirements

Test Score
IELTS Academic Overall score of 6.5 with no score less than 6.0 in any of the four bands
CAEL Overall score of 70 with no score less than 60 in any of the four bands
PTE Academic 59
Cambridge English Overall score of 176 with no language skill less than 169
ESL4/GAP5 Minimum grade of 80% in Level 9, 75% in Level 10
Duolingo Overall score of 120, with no score lower than 105


Learn More about English Language Requirements

Applicant Selection Criteria

Applicant Selection Criteria

Where the number of program eligible applicants exceeds available spaces, the Applicant Selection Criteria for this program will be:
1. Preference for Permanent Residents of Ontario
2. Receipt of Application by February 1st (After this date, Fanshawe College will consider applicants on a first-come, first-served basis until the program is full)
3. Achievement in the Admission Requirements


Level 1
Take all of the following Mandatory Courses:
INFO-6146Tensorflow & Keras With Python4
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-6147Deep Learning With Pytorch3
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-6148Natural Language Processing 14
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-6149Machine Learning Security3
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-6150Data Mining & Analysis3
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-6151Data Visualization for Machine Learning3
This course is an introduction to the consumption and rendering of business data as dashboard information. Students will have an opportunity to create meaningful dashboards consisting of pie charts, stacked charts, area graphs etc. working with both Python and JavaScript tools.
COOP-1020Co-operative Education Employment Prep1
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.
View all courses

Tuition Summary


Canadian Costs
Total Cost of Program

*Total program costs are approximate, subject to change and do not include the health and dental plan fee, bus pass fee or program general expenses.