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Math Foundations for AI

Vector Institute

Tuesday, 18 February 2020 at 10:00 AM - Monday, 13 April 2020 at 3:00 PM (EST)

Math Foundations for AI

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Ticket Type Sales End Price Fee GST/HST Quantity
Non-refundable Registration Fee (Total course fee: $3,000) Ended $250.00 $0.00 $32.50

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Event Details

VECTOR INSTITUTE AI CERTIFICATE COURSES FOR INDUSTRY

 

Math Foundations for AI

 

Available to  Vector Institute Sponsors only.

 

For registration inquiries, email: natalie.klym@vectorinstitute.ai

 

Date: Feb 18 - Apr 13, 2020 

 

Location: This course will be delivered online via D2L Brightspace with in-person tutorials at Vector Institute, 661 University Ave, Suite 710, Toronto, ON M5G 1M1

 

Instructor:  Graham Taylor

 

Registration Deadline: Feb 14, 2020 

 

Fees$3,000 

(A deposit of $250 will be collected upon registration. $2,750 will be invoiced upon course commencement.)

 

Please read: Terms and Conditions


Other Courses Offered: 

  • Math Foundations for AI 
    February 18-April 13, 2020 
    Register Here

  • Machine Learning
    Coming soon

  • Deep Learning I
    March 17- May 5, 2020
    Register Here

  • Deep Learning II 
    Coming soon

  • Reinforcement Learning
    Coming soon


Course Description

 

The Math Foundations for AI course provides an overview of the mathematical and computational foundations that are required to build machine learning and AI systems. Participants will gain an understanding of the historical context, breadth, and current state of the field.

 

The course covers fundamental tools and techniques used in machine learning and AI, including scientific computing and data analysis in Python; mathematical foundations; and fundamentals of modeling. The course will talk about some basic machine learning algorithms, but will not cover any advanced machine learning models or concepts. The course will be split into a series of intensive modules that start with the basic background and principles of core technical machine learning and AI, and end with how to apply this foundational knowledge to concrete problems on real datasets.

 

This course is designed to give participants the background required to pursue more advanced certificate courses offered by the Vector Institute.

 

 Who Should Attend 

  • Employees interested in taking courses in Vector's AI Certificate Program for Industry who wish to refresh their knowledge of mathematics and computing.

  • Participants are expected to have already taken undergraduate courses in probability and statistics, calculus, linear algebra, and data structures and algorithms.

 

 Available to  Vector Institute Sponsors only.

 

Learning Outcomes  

 

By the end of this course, participants should be able to:

 

  • Articulate the most pertinent issues concerning artificial intelligence and society;
  • Apply the scientific Python stack to manipulate vectors and matrices; employ an automatic differentiation framework; use data visualization techniques to perform exploratory data analysis and communicate findings; and access a compute cluster to scale up experiments;
  • Express the mathematical foundations of artificial intelligence and machine learning, including relevant topics in calculus and linear algebra (e.g., differentiation, matrix-vector operations), and probability theory;
  • Employ general-purpose optimizers to fit the parameters and hyper-parameters of machine learning models; and contrast the similarity and difference between machine learning and optimization;
  • Master the algorithmic foundations of artificial intelligence and machine learning; identify canonical algorithmic problems; and propose existing algorithmic paradigms to solve them.

 

Course Load

 

Participants can expect to spend approximately 8 hours per week reading and engaging with the material, attending Tutorials, and completing assignments.

 

Instructor 

 

Graham Taylor is a Canada Research Chair and Associate Professor of Engineering at the University of Guelph. He directs the University of Guelph Centre for Advancing Responsible and Ethical AI and is a Faculty Member and Canada CIFAR AI Chair at the Vector Institute. He has co-organized the annual CIFAR Deep Learning Summer School and has trained more than 60 students and research staff on AI-related projects. In 2016 he was named as one of 18 inaugural CIFAR Azrieli Global Scholars. In 2018 he was honoured as one of Canada's Top 40 under 40. In 2019 he was named a Canada CIFAR AI Chair. He spent 2018-2019 as a Visiting Faculty member at Google Brain, Montreal.

 

Graham co-founded Kindred, which was featured at number 29 on MIT Technology Review's 2017 list of smartest companies in the world and CB Insights AI 100 list, highlighting the most innovative AI companies for 2018. He is the Academic Director of NextAI, a non-profit accelerator and founder development program for AI-focused entrepreneurs.

 

Course Outline & Schedule

 

All course Units will be released online according to the schedule below and supplemented by mandatory in-person Tutorials


Week 1: Tues, Feb 18--Mon, Feb 24

  • Unit 1: Introduction to AI, Machine Learning, and Scientific Python

  • Tutorial: Friday Feb 21, 3-5pm at Vector

 

Week 2: Tues, Feb 25--Mon, Mar 2

  • Unit 2: Mathematical Foundations: Linear Algebra 

  • Tutorial: Friday Feb 28, 3-5pm at Vector

 

Week 3: Tues, Mar 3--Mon, Mar 9

  • Unit 3: Mathematical Foundations: Analytical Geometry

  • Tutorial: Friday Mar 6, 3-5pm at Vector

 

Week 4: Tues, Mar 10--Mon, Mar 16

  • Unit 4: Mathematical Foundations: Matrix Decompositions

  • Tutorial: Friday Mar 13, 3-5pm at Vector

 

Week 5: Tues, Mar 17--Mon Mar, 23

  • Unit 5: Mathematical Foundations: Vector Calculus

  • Tutorial: Friday Mar 20, 3-5pm at Vector

 

Week 6: Tues, Mar 24--Mon, Mar 30

  • Unit 6: Mathematical Foundations: Probability and Distributions

  • Tutorial: Friday Mar 27, 3-5pm at Vector

 

Week 7: Tues, Mar 31--Mon, Apr 6

  • Unit 7: Continuous Optimization

  • Tutorial: Friday Apr 3, 3-5pm at Vector

 

Week 8: Tues, Apr 7--Mon, Apr 13

  • Unit 8: When Models Meet data

  • Tutorial: Friday Apr 10, 3-5pm at Vector


*******************************************

Webinar/ Information Session:

 

Vector Institute will be hosting a Zoom call to share more information about this course and answer any questions you may have.  

When: Feb 5, 2020 04:00 PM Eastern Time (US and Canada)

Register in advance for this meeting:
https://vectorinstitute.zoom.us/meeting/register/uZ0vdOGvpjsp-7poQjBiksoCU_M1q36fqA


 

Have questions about Math Foundations for AI? Contact Vector Institute

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When & Where


Vector Institute, 7th Floor
661 University Ave Suite 710, Toronto, ON M5G 1M1
MaRS Discovery District
Toronto, ON M5V 3K2
Canada

Tuesday, 18 February 2020 at 10:00 AM - Monday, 13 April 2020 at 3:00 PM (EST)


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