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About W Booth School

The W Booth School of Engineering Practice and Technology within McMaster University’s Faculty of Engineering is dedicated to student-centred experiential learning through flexible, adaptable and innovative programs and teaching using state of the art resources and facilities. Our learning environment emphasizes hands-on education and transferable skills to produce engaged graduates ready to serve a diverse community and societal needs. 

Undergraduate Programs

Seven undergraduate programs, including the McMaster-Mohawk Bachelor of Technology Partnership.

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Combined Degree/Diploma
Automotive & Vehicle Engineering Technology
Automation Engineering Technology

Degree Completion Program
Civil Engineering Infrastructure Technology
Power and Energy Engineering Technology
Manufacturing Engineering Technology
Software Engineering Technology

Certificate Programs
Certificate in Technology

Graduate Programs

Five graduate programs focused on tackling complex global challenges through problem-based learning.

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Engineering Design
Engineering and Public Policy
Engineering Entrepreneurship and Innovation
Technology Entrepreneurship and Innovation
Manufacturing Engineering

Our Vision: To be internationally recognized for excellence in practice-based education that produces holistic change leaders and innovators who create sustainable prosperity and positively impact the environment, society and the economy.

We are home to seven undergraduate and five graduate programs. Our unique specializations focus on the cross-section of technology and society. In small classes, students work closely as groups to find creative solutions for a changing world. Our partnership with Mohawk College - a hallmark of the W Booth School since its inception - enables us to provide specialized offerings, including a Bachelor of Technology degree tailored to the needs of industry.

At both the undergraduate and graduate levels, students are immersed in education that is practice-based and innovative.  Students connect with the community, spend time in labs, and work collaboratively with industry as part of their education.

Key Facts

Founded in 2005

Current Enrollment:1,500+ students (undergrad and grad)

Alumni: 2,500 and counting

92% of our alumni are employed in their field of study within six months of graduating

The late Walter G. Booth, a philanthropist, entrepreneur, and 1962 Faculty of Engineering graduate, gave generously to McMaster, the only university willing to take a chance on his non-conventional route through the post-secondary education system.

Student Spotlights

Master's program the 'most significant year' of successful policy researcher's academic journey

June 5, 2019 /  Department News

Master's program the 'most significant year' of successful policy researcher's academic journey

Gussai Sheikheldin, MEPP alumni, met with Dr. Gail Krantzberg, and shared his story.

Quality Assurance Top Priority for Graduate of W Booth School

November 15, 2018 /  Department News

Quality Assurance Top Priority for Graduate of W Booth School

Quality assurance is all about maintaining standards. It’s a comprehensive process that’s driving increased efficiencies in sectors ranging from healthcare and education to energy and manufacturing.

Pursuit of Authenticity Drives McMaster Engineering Graduate

October 30, 2018 /  Department News

Pursuit of Authenticity Drives McMaster Engineering Graduate

Live and work with passion and purpose. That’s the advice of McMaster alumnus Pouyan Safapour, Bachelor of Engineering (2009) and Master of Engineering (2011).

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Undergraduate Studies

Combined Degree/Diploma

High school or post-secondary transfer students earn a degree, diploma, and 12 months of work experience in 4.5 years of study.

Program Streams:

Degree Completion Program

College and University graduates advance directly to level 3 of a degree.  Flexible evening and weekend courses make it possible for technologists and internationally educated professionals to gain Canadian credentials while working.

Program Streams:

Certificate Programs

Certificate in Technology: Canadian and internationally educated professionals advance their career with evening and weekend courses in technology and leadership.

Graduate Studies

Our customized graduate studies learning methodology reflects core subject matter viewed through a market-driven, experiential learning lens. Curriculum is structured so that academics converge with learning by practice in real time. Creativity and innovation are nurtured throughout this educational experience. Program graduates will have a set of technical and professional skills that enable an enhanced range of career choices in tomorrow’s world.

We offer Master of Engineering Programs specializing in:

Featured Initiatives:

  • Practitioner's Forum
  • Innovation Studio
    • An Initiative of the W Booth School of Engineering Practice and Technology where students learn how to pursue value creation through the practice of thought leadership, interdisciplinary initiatives and community building.

2017-18 Timetable of Graduate Courses


Why Enrol?

Benefits from Attending the W Booth School:

  • Gain marketable technical, leadership and entrepreneurial skills
  • Access state of the art facilities and labs – including the new "Learning Factory" at W Booth
  • Connect with technical and business mentors
  • Build professional networks
  • Apply for generous bursaries and scholarships
W Booth School


Project Profiles

Students in M.Eng. Design program apply machine learning and data analytics to aquaponics farming

August 15, 2019 /  Department News

Students in M.Eng. Design program apply machine learning and data analytics to aquaponics farming

Jingpeng Zhai, a student in the Master of Engineering Design program with the W Booth School of Engineering Practice and Technology has been working in a team of three with their client to design a process to help demonstrate the viability of a indoor aquaponics farming in Canada.

Eco-Pen Startup Begins to Blossom at W Booth School

November 26, 2018 /  Department News

Eco-Pen Startup Begins to Blossom at W Booth School

These two W Booth School graduate students are writing a new chapter in the story of eco-entrepreneurship in Canada.

Friendship at W Booth School Sparks High Tech Start Up

June 5, 2018 /  Department News

Friendship at W Booth School Sparks High Tech Start Up

Fourth year students Cole Kirschner and Nathan Cawte are bullish on the future of predictive technology applied to human health.

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Artificial Intelligence Courses

W Booth School offers a series of courses in artificial intelligence.

They range from the 4th year undergraduate courses (designated as course code 4' hundreds and 6' hundreds) to graduate level courses.

Currently offered courses are:


SEP 786 Artificial Intelligence and Machine Learning Fundamentals

  • Solving Problems using AI: Searching, optimization, online search agents. Constraint satisfaction.
  • Knowledge, Reasoning and Planning: Logic and Inference, Planning and Acting, Knowledge Representation. Knowledge and Reasoning with Uncertainty. Machine learning problems, training and testing, overfitting.
  • Modelling strategies: data preprocessing, overfitting and model tuning. Measuring predictor importance. Factors that Can Affect Model Performance. Feature selection. Measuring performance of classification models.


SEP 787  Machine Learning : Classification Models

  • Discriminant analysis and other linear classification: Logistic regression, Linear discriminant analysis, Partial least squares discriminant analysis, Penalized models, Nearest shrunken centroids
  • Linear Support Vector Machine: Empirical vs structural risk minimization, Soft margin classifier
  • Nonlinear classification models: Nonlinear discriminant analysis, Flexible discriminant analysis, Support vector machines, K-nearest neighbors, Naïve Bayes
  • Classification Trees and Rule based modes: Basic classification trees, Rule-based models, Bagged trees, Random forests, Boosting
  • Remedies for severe class imbalance: The effect of class imbalance, Model tuning, Alternate cutoffs, Adjusting prior probabilities, Unequal case weights.


SEP 788 Neural Networks and Development Tools

  • Introduction to AI landscape.
  • Tools for building a machine learning project (Python crash course).
  • Neural Networks Mathematical background.
  • Hyperparameters, Generalization, Training process.
  • Using Python scikit-learn.
  • Project 1 – build and train a neural network using python scikit-learn
  • Neural networks vs deep learning.
  • TensorFlow
  • Applying TensorFlow for Machine learning,
  • Project 2- use TensorFlow/Keras for defining and training a deep learning network (use case).
  • Other DNN frameworks and hardware.
  • Project 3- More complex deep learning challenge (using Google cloud or Azure) .


SEP 789 Deep Learning and Its Applications

  • Image processing using machine learning.
  • Convolutional Neural Network (CNN) Architecture and training.
  • Image recognition application.
  • Transfer learning, Image classification, Image segmentation, Image labeling, Clinical imaging.
  • Project 1 – build and train a CNN network (image processing).
  • Recurrent Neural Network (RNN) Architecture; RNN Applications (Time series, Stock market).
  • Deep learning application in Natural language processing.
  • Smart manufacturing: Comparison between deep learning and traditional machine learning, Product quality inspection, Fault assessment, Defect prognosis.
  • Project 2 – build and train a RNN network.
  • Reinforcement learning: Architecture; Application in Robotics, Application in display advertising.
  • Advanced topics: Autoencoders, Deep Residual Networks, Generative Models (GANs).
  • More Applications: Digital & Smart Systems, Energy, Transportation, Micro-Nano Systems, Advanced Manufacturing
  • Project 3 – select one project out of 3-4 themes with data sets to apply deep learning with minimal guidance.


SEP 767 Multivariate statistical methods for Big Data analysis and process improvement

  • Course overview and introduction
  • Principal Component Analysis (PCA)
  • Applications of PCA
    • Monitoring processes
    • Data visualization
  • Projection to Latent Structures (PLS)
  • Applications of Latent Variable Methods
    • Soft Sensors
    • Advanced pre-processing
  • Working with images
  • Classification
  • Dealing with batch data
  • Multiblock data analysis

Be a part of the explosive growth in digital reality (AR/VR) applications

Starting in September 2019, The School will be offering an opportunity to specialize in augmented reality / virtual reality (ART/VR) within our Master of Engineering Design program.  Augmented reality and virtual reality are projected to be $200+ Billion industry by 2022, with applications ranging from architecture, medicine, engineering design, manufacturing systems operations to animated 3D immersive entertainment.  Huge advances in these technologies have been developed by the entertainment industry; these advances and further enhancements are rapidly finding their applications in all walks of life (e.g. self-driving vehicles).


Why would you enroll?

AR/VR are essential technologies used to develop self-driving cars (Google autonomous car has travelled 20 Million miles in the VR space as a part of its training), architecture, anatomy and surgery, training in operation of complex machinery (e.g. aircraft, industrial plants), games, movies, and many other fields.

For instance, “Ready Player One” movie directed by Steven Spielberg (2018) was shot in virtual reality instead of being shot on a movie set (see clip about the production process).

If you would like to work in the above fields, developing AR/VR tools and applications, apply! 


Who should apply?

Applicants with a solid background in software code development (C++ or C# or Java or Python) are encouraged to apply.


What and how will you learn?

You will learn how to use the industry leading software for creation of AR/VR, how to create special effects through customization of the software code, and how to integrate various digital assets into an AR/VR produced entity.

WBooth School offers its students the opportunity to develop advanced knowledge of these technologies by learning under the guidance of the leading industry experts.  In particular, our collaboration with Pipeline Studios (winner of two Emmy awards for its animated movies) provides an opportunity for hands-on learning and co-op placements with the industry leading company.  The program is supported by a new AR/VR laboratory equipped with specialized workstations and other virtual reality equipment.


The following six courses constitute the specialization in AR/VR:

SEP 6CG3: Fundamentals of computer graphics and animation development

Review platforms and languages for development: C++, C#, Unity, Maya API, Python, CUDA/Open CL along with  open sourse software in the Visual effects field: Open Image IO, Open shading language, Mitsuba.  Key mathematical and algorithmic foundations of animation and applications in the field of visual effects applications: geometry, algebra, calculus, vector fields.  Areas of research: rendering, character animation, simulation, computer vision.

Principles and mathematics foundation of computer graphics. Creation of 2D and 3D pictures. Application of the given principles in common situations, such as how to approximate an ideal solution on available hardware, or how to represent a data structure more efficiently. Rendering equation, GPU architecture considerations, and importance- sampling in physically based rendering.

  • Modern approaches to shading and rendering, e..g. probability theory for use in Monte-Carlo rendering
  • Implementations of GPU shaders, software rendering, and graphics-intensive 3D interfaces
  • 3D real-time graphics platforms–their design goals and trade-offs–including new mobile and browser platforms
  • Programming and debugging approaches unique to graphics development
  • Algorithms used for path following, hierarchical kinematic modelling, rigid body dynamics, flocking behaviour, particle systems, collision detection.

SEP 6VE3: Visual effects and animation production technology

Domain knowledge of visual effects pipelines. Overview of how productions are executed:  Film, TV, Games, Mixed reality.   Introduction to major 3rd party applications software: Autodesk Maya, Pixar’s Renderman, Mitsuba, Foundry Nuke, Unity Game Engine.  Brief summary of research and development areas: rendering, digital creature/human, simulation, image processing, computer vision.

Basics of visual effects and compositing, the fundamentals of bluescreen  and greenscreen keying, 3D texturing, cloning, wire & rig removal, rotoscoping, 2D and 3D motion tracking, and matchmoving. Various forms of 2D, 2.5D & 3D visual effects, including 3D CGI, crowd replication, face replacements, faking shadows, reflections and Z depth, atmospheric, smoke, cloud & heat FX, sky replacements, day-for-night and digital 3D HUD FX. Selected topics in 2D, 2.5D & 3D digital matte painting and projections, film colorization, particle systems, fluid and rigid body dynamics, full digital environments, digital destruction, advanced lighting and rendering techniques, stereoscopic 3D, 2D to 3D conversions, and expert 3D and Photoshop extraction and modeling techniques.

SEP 714: Workflow management for animated prototypes

The course deals with the workflow employed in production of animated visual content.  Management of large scale dataset for creative technology application, asset management and development of building blocks which are required to develop the pipeline and use of Python as the basis for integration within the workflow.

  • Development with Python
  • Asset creation, Asset bundles & version management
  • Dependency graph evaluation
  • Database infrastructure for published assets
  • Department and production workflows
  • Render farm utilization
  • Distributed render management

SEP 715: Rendering techniques

Mathematical theory behind a modern photorealistic rendering system and its practical implementation.   Monte Carlo integration, Shading and lighting algorithms, Acceleration structures, Ray tracing optimization.  Volume rendering techniques used for feature animation and visual effects production.

The course presents both the mathematical theory behind a modern photorealistic rendering system and its practical implementation. Through a method known as 'literate programming', the material combines a human-readable documentation and source code into a single framework that is specifically designed to aid comprehension. Ray-tracing hair and curves primitives, numerical precision issues with ray tracing, LBVHs, realistic camera models, the measurement equation, and Discussion of bidirectional path tracing, numerical robustness issues in ray tracing, realistic camera models, and subsurface scattering.

Modern production volume rendering techniques in a generic context, explaining how the techniques fit together and how the modules are used to achieve real-world goals.  Implementation of the techniques, showing how to translate abstract concepts into concrete, working code and how the ideas work together to create a complete system.

SEP 791: Augmented Reality, Virtual Reality and Mixed Reality

In-depth exploration of the rapidly developing new interdisciplinary topic employing techniques from computer graphics, computer vision, and virtual immersion techniques with applications in varying fields including entertainment, manufacturing and sciences.

  • Stereoscopy fundamentals
  • Psychology of vision and immersion
  • Current hardware (Magic Leap AR, Oculus, Vive, PS4 VR, Hololens)
  • Virtual reality vs. Augmented reality vs. mixed reality
  • Holographic techniques of challenges
  • 360 degrees video processing for VR
  • Development platforms

SEP 792: Interactive applications utilizing GPU's for real-time projects

Modern techniques used to generate rapidly synthetic three-dimensional images. With the advent of programmable shaders, a wide variety of new algorithms have arisen and evolved over the past few years and are presented in this course.

  • Open GL/ Vulkan, Unity/ Unreal game engines
  • Game engine architecture
  • Real time rendering techniques
  • CPU compute via CUDA/ Open CL/ Direct compute
  • GPU architecture
  • Computer vision