All prices are in Canadian dollars.

Applied Machine Learning Professional Certificate in Supply Chain

Date:   Feb 20, 2021 - May 07, 2021
Location:   Online Western Canada

2021 DATES

Feb 17

Feb. 20 - Mar 5

Mar 6 - 19

Mar 20- Apr 9

Apr 10 - May 7

May 16, 2021


Course Orientation

1:   Introduction to Machine Learning

2:   Supervised, Unsupervised and Reinforcement Learning 

3:   Deep Learning, Natural Language Processing, Computer Vision

4:   Business Project

Certificate Awards Ceremony

Learning Outcome(s):

Participants who complete this course will be able to:

  • Use machine learning to inform supply chain decision making
  • Work with the concept of a data model, to evaluate it, and explain why models fail.
  • Apply algorithm model building knowledge to build forecasting and prediction models.
  • Classify models - as supervised, unsupervised, or reinforced.
  • Apply data wrangling and pre-processing techniques
  • Classify performance models as regression or classification.
  • Publish and deploy models onto a commercial Machine Learning platform
  • Configure, implement and report on a real use case for your organization.


None. No coding expertise or experience is required


The course is carefully scheduled in modules over a 3-month period,
in which participants will grow from ML novice to a confident ML practitioner. 

The purpose overall is to deliver value to your work and your organization. 

Module 1:  Introduction to Machine Learning 

This module cuts through the jargon such that key foundational machine learning concepts are understood and form the basis for going deeper in the theory and more importantly practice. Participants start learning by using simple data.  

Module 2:  Supervised, Unsupervised and Reinforcement Learning  

Real-life is not as simple. This module takes the participants deeper into machine learning so that they become comfortable in using unclean data and various types of machine learning algorithms 

Module 3:  Deep Learning, Natural Language Processing, Computer Vision  

This module explores neural networks which make up the backbone of deep learning algorithms. Participants also learn to use text data from documents and emails to model 

Module 4:  Business Project  

Supported by an expert instructor, the participant now applies the learnings on a real business project in their own job. This ensures that the skills effectively result in on-the-job performance. The participant and their workplace see results!


We have gathered a roster of outstanding experts to instruct and coach participants
through this applied machine learning course. They are:

Dr. Rajbir Bhatti

Associate Professor, Bissett School of Business, MRU. Ph.D. (SCM), B.Tech, M.Tech
with 20+ years of research experience in supply chain optimization. Expertise in the application of fuzzy logic techniques to real-world industry problems.

Amit Varma

Technology entrepreneur with 20+ years experience in applying technology to construction, energy, banking, and financial services. Masters in Management Science, BSc Management Science.

Kwame Asiedu

Data science expert with 15+ years experience in big data mining and analytics, machine learning, pattern recognition, digital signal processing, system design and analysis, biometrics, and IoT. MSc Geomatics Engineering, BSc Computer Science and Psychology

Dr. Padma Paul

20+ years in AI, ML, research, and software development. B.Sc., M.Phil., and Ph.D. in Computer Science. Ranked 7th in all Computer Science PhD Students for research in Computer Science. Ranked 1st in AI and Applied Machine Learning among all universities/labs in Canada.

Jaspreet Gill

Data Scientist and Software Engineer with a Master’s in System Software and Post Graduate Diploma in Machine Learning and Artificial Intelligence. Expertise in the application of ML/AI in transportation, oil and gas, and manufacturing industries.

Dr. Diego Raffa

Data Scientist with a background in energy, academics, and research. Trained as a chemist, he researched after his Ph.D. in the fields of chemistry and physics. Expertise in the energy industry and the applications of machine learning in supply chain management.

Ian Gonzalez

16 years in senior positions in Procurement, Engineering and Maintenance, and Corporate Planning departments within oil and gas, and aviation MRO. industries. He has a passion for SCM teaching and does so from the perspective of an experienced SCM professional, engineer, and computer programmer. MBA and BSc Mechanical Engineering.


15 Credits | 21 hours of instruction | 50 hours of self directed learning

Course Fees:

Member        :    $1,800 + GST

Non-Member:     $2,100 + GST

Membership will be activated after this course has started.
Corporate rates $1,800 per person for 3 or more participants.
Contact John Burke at

For Alberta residents, this course is eligible for application for funding
under the Canada Alberta Job Grant scheme. 

On approval, the net cost of the program will be:

Member        :     $600.00 + GST

Non-Member :     $700.00 + GST

Apply here for funding support.

N.B. Applicants need to be employed to qualify for this funding.

Course Overview:

Artificial Intelligence (AI) can be used today to make faster, more accurate and risk-managed supply chain decisions.

"We estimate that firms will derive between $1.3trn and $2trn a year”
in economic value from using AI in supply chains and manufacturing" 
– McKinsey Global

This Applied Machine Learning Professional Certificate
for Supply Chain
is the first of its kind in Canada. 

It will give supply chain professionals a clear edge in harnessing the power of AI in everyday SCM practices and decisions.

This course will enable you to be competent and confident in using Machine Learning ML in your analysis, planning and decision making. At the end of this course, you will be able to build and deploy predictive models for supply chain planning and decisions, for example to rank goods and services, model smart purchasing programs, generate proposal tenders, predict shipments, and prepare budgets that react to market changes.


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