Education

Are you currently in school for AI or looking to change your career path? Consider applying to one of our scholarships! New AI courses and workshops are available!

We are working with BCIT, Northeastern University, SFU and UBC to create great learning opportunities with new courses and workshops in AI. With different options for whether you're in school or looking for a professional workshop, we are sure to have the right fit for you. Check out the list below of courses and workshops. You may be eligible for a $500 scholarship!

Athena Pathways has partnered with Microsoft

Microsoft is providing funding for BC women to take Global Knowledge courses for FREE! Check out the current course offering below in the Professional Workshops Category.

Microsoft logo
Microsoft Funded Global Knowledge Course Options

Through Microsoft funding, you may apply to take up to a MAXIMUM OF TWO COURSES out of the three available:

  • Microsoft Azure Fundamentals (AZ-900T01) – 1 Day
  • Microsoft Azure AI Fundamentals (AI-900T00) – 1 Day
  • Designing and Implementing an Azure AI Solution (AI-100T01) – 3 Days

For those who have had no exposure to Azure, Global Knowledge recommends you take the following two courses:

  • Microsoft Azure Fundamentals (AZ-900T01) – 1 Day
  • Designing and Implementing an Azure AI Solution (AI-100T01) – 3 Days

For those who have had some exposure to Azure, Global Knowledge recommends you take the following two courses:

  • Microsoft Azure AI Fundamentals (AI-900T00) – 1 Day
  • Designing and Implementing an Azure AI Solution (AI-100T01) – 3 Days

If you have questions regarding which of the two courses you should take based on your current knowledge level, please contact Global Knowledge directly.

Global Knowledge contact: Philip Murch |  Email: Philip.Murch@globalknowledge.com

If you are applying to take two courses, you may send a $100 e-transfer for both instead of two individual transfers at $50 each.

Undergraduate Studies

APRE 5101 - Fundamentals of the Internet of Things (IoT)- CRN 88971

  • Institution: BCIT
  • Date: Feb 01 - Fri Apr 30 , 2021
  • Course Page
Course Description

This on-line course is designed to introduce you to the use, benefits and impact of IoT not only in industry and business but in our day-to-day lives. You will learn how data is communicated, collected, analyzed and abstracted, and delivered to the end user to make life safer, more efficient and to assist in achieving better data to make better decisions.
The IoT Application Framework will be introduced as a practical application development and deployment roadmap to assist the end user in successfully implementing IoT solutions. You will also learn some of the challenges inherent in setting up and using IoT effectively including cybersecurity concerns and privacy issues.

Apply for a Scholarship

CMPT 419/ 726 Special Topics in Artificial Intelligence

Course Description

Special Topics in Artificial Intelligence: Machine Learning. Machine Learning is the study of computer algorithms that improve automatically through experience. It is one of the most exciting aspects of artificial intelligence, and is the basis for many of its industrial applications. It is the preferred framework for many applications, such as face detection, hand-written digit recognition, speech recognition, and credit card fraud detection. This course provides students with a grounding in both the theoretical justification for, and practical application of, machine learning algorithms. Covers techniques in supervised and unsupervised learning, the graphical model formalism, and algorithms for combining models. 

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Special Topics Database Systems

  • Institution: SFU
  • Date: January 5 to April 12, 2021
  • Course Page
Course Description

This course introduces Data Mining, an area that plays a key role in Big Data analytics. The goal of data mining is the efficient discovery of useful patterns in large datasets. This course focuses on fundamental data mining tasks and algorithms as well as key applications. It will prepare you both for developing your own data mining application and for starting your data mining research. Students taking this course are expected to have taken an algorithms course and to have an understanding of basic statistics equivalent to an entry-level course. The course project requires programming in Python or R, and students are expected to be proficient with one of these programming languages.

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Special Topics in Artificial Intelligence

  • Institution: SFU
  • Date: Jan 5 to April 12, 2021
  • Course Page
Course Description

This course introduces fundamental concepts in robotics and related fields, including analytical methods for decision making, and machine learning in the context of robotics. Topics include modelling and simulation of robotic systems, optimization, optimal control, robotic safety, reinforcement learning, and robotic perception. Applications of the material include unmanned aerial vehicles and self-driving cars.

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CPSC 340 Machine Learning and Data Mining

  • Institution: UBC
  • Date: Jan 04, 2021 to Apr 08, 2021
  • Course Page
Course Description

Models of algorithms for dimensionality reduction, nonlinear regression, classification, clustering and unsupervised learning; applications to computer graphics, computer games, bio-informatics, information retrieval, e-commerce, databases, computer vision and artificial intelligence.

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COMP 1021 - Applied AI for Non-Programmers

  • Institution: BCIT
  • Date: January 09, 2021-April 10, 2021
  • Course Page
Course Description

This hands-on entry level course provides an overview of Artificial Intelligence (AI) and is offered by BCIT Computing Part-time Studies. Aimed at business or IT professionals and other who are curious about learning AI fundamentals, students begin by discussing AI concepts, and making comparisons to Machine Learning (ML) and Data Science.
There are no specific prerequisites other than being proficient in using a personal computer, and being able to interact and communicate with others on a group project.
Topics include supervised learning, neural networks, unsupervised learning, and reinforcement learning.
Commonly used AI tools and platforms allow participants to prepare data, train and evaluate their models.
Online discussions include: natural language processing and decision making, as well as social issues and implications due to the limitations of AI.
COMP 1021 is an elective in the Applied Information Systems (ACIS) Associate Certificate, which is a sub-set of the Computer Systems Technology (CST) Diploma.
Evaluation includes significant participation, labs, activities, online quizzes, group work and a project presentation. Upon successful completion students will be able to develop and deploy a no-code AI solution using Microsoft Azure.

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COMP 4254 - Advanced Topics in Data Analytics

Course Description

This is the final course for the Applied Data Analytics Certificate (ADAC) from BCIT Computing and assumes students have completed both MATH 3060 and COMP 2854 prior to this course. Building on statistics, data mining, Python for Data Analysis and visualization techniques, students who have completed the core requirements of ADAC will be able to integrate these advanced topics into a data analytics project. Participants are introduced to emerging sources of digital mapping data, data standards, mapping compilation procedures, mapping systems, plus an introduction to cartography tools and techniques in data analytics and Big Data. Labs and exercises use Excel, Python and Apache Spark for data mining with a focus on Business Intelligence and Big Data. Discussions also include NoSQL databases, and Hadoop. Students learn to work with a variety of structured and unstructured data sources to model, analyze and visualize data. Upon successful completion, participants will be able to present an advanced data analytics project start-to-finish. Prerequisite(s)
COMP 2256 and COMP 2454 and COMP 2854 and COMP 3840 and MATH 3060

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COMP 8085 - Artificial Intelligence

  • Institution: BCIT
  • Date: January 4, 2021 - March 29, 2021
  • Course Page
Course Description

Artificial Intelligence (AI) is the intelligence expected to be demonstrated by machines and computer programs. This course is designed to provide students with expertise in creating and modifying required AI algorithms and techniques. The first part of the course will focus on classic AI solutions (especially decision making) while the second part will cover some of machine learning (ML) related applications of AI (with an emphasis on learning from examples). The course will consider real world problems that need to be solved with applications of AI and the techniques used to build such applications (e.g. using the techniques to create challenging non player characters (NPC) in games development or password strength classification and intrusion detection in network security). More specifically, students will learn about the searching paradigm in designing intelligent agents and will practice implementing search algorithms. Logical knowledge representation and reasoning (another essential tool for AI experts) will be another topic in this course. Probabilistic reasoning will also be explored to help students learn how to deal with incomplete information and uncertainty. The course will also examine different learning techniques to guide students in creating self-learning models that can improve performance in decision-making over time through practical examples.
Prerequisite(s) COMP 8042

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COMP 3981 - Introduction to Artificial Intelligence

  • Institution: BCIT
  • Date: January 6-April 17 2021
  • Course Page
Course Description

This course provides an introduction to the various topics in artificial intelligence. Topics to be covered include search, games, constraint satisfaction problems, knowledge and reasoning, and learning. Students will develop an understanding of the basic concepts and algorithms used in artificial intelligence. Application of artificial intelligence to problems in different domains will also be discussed.Prerequisite: Completion of first year CST and Admission into the Artificial Intelligence and Machine Learning Option

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Graduate Studies and Professional Development

Machine Learning: Strategic Applications

Course Description

Machine Learning—it’s not just a buzzword any more.
A subset of artificial intelligence, Machine Learning (ML) is the science of getting computers to uncover key connections and make decisions without being explicitly programmed. It has given us many striking new applications, like self-driving cars and speech recognition.
This program introduces the tools, techniques, opportunities and applications of ML from a strategic perspective. Unlock the opportunities of this powerful technology to create greater value and competitive edge in your business.

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Advanced Machine Learning

  • Institution: UBC
  • Date: March 29 - April 22, 2021
  • Course Page
Course Description

Advanced machine learning methods in the context of natural language processing (NLP) applications. Bag of words, recommender systems, topic models, natural language as sequence data, Markov chains, and recurrent neural networks.

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Data Visualization and Storytelling

Course Description

Today’s organizations have the ability to collect data across a wide variety of channels and activities. However, communicating critical take-aways to stakeholders and creating actionable insights and decisions is becoming increasingly difficult in this sea of data. In this course, participants will learn how to communicate and sell marketing strategies, activities and results using a combination of visual thinking, storytelling, dashboards, and data visualizations. Using industry-standard tools, participants will identify the appropriate charts, graphs, and visual elements required for effective data visualization and communication across a diverse range of audiences.
This course is recommended as the final required course in the Associate Certificate in Data and Marketing Analytics program. Following this course, participants can choose between Marketing Intelligence & Performance Optimization, Mobile and Social Media Analytics, or Agile Marketing for their final course.

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Customer Analytics

  • Institution: UBC
  • Date: February 17 - March 13, 2021
  • Course Page
Course Description

This course examines the tools, techniques, and strategies required to collect, manage, and analyze customer data. Specifically, participants will look at the role of data in understanding, driving, and improving customer acquisition, customer support, and customer retention. Leveraging a variety of customer touch-points, the course will look at customer segmentation based on customer needs, customer life cycle, and customer experience. Once completed, participants will be able to use customer analytics to better understand their customers’ behaviors and to make effective and profitable customer decisions.
This course is recommended as a precursor to the Data Visualization and Storytelling course in the Associate Certificate in Data and Marketing Analytics program.

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Microsoft Sponsored Global Knowledge Courses

Microsoft Azure AI Fundamentals (AI-900T00)

Course Description

New – This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Apply for the Course and Microsoft Sponsorship

Microsoft Azure AI Fundamentals (AI-900T00)

Course Description

New – This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Apply for the Course and Microsoft Sponsorship

Microsoft Azure Fundamentals (AZ-900T01) - sponsored by Microsoft and provided by Global Knowledge

Course Description

This one-day course will provide foundational level knowledge on cloud concepts; core Azure services; security, privacy, compliance, and trust; and Azure pricing and support.
This course is a high-level overview of Azure. It will provide foundational level knowledge of cloud services and how those services are provided with Microsoft Azure.

For further details about this course, please visit:

Apply for the Course and Microsoft Sponsorship

Microsoft Azure Fundamentals (AZ-900T01) - sponsored by Microsoft and provided by Global Knowledge

Course Description

This one-day course will provide foundational level knowledge on cloud concepts; core Azure services; security, privacy, compliance, and trust; and Azure pricing and support.
This course is a high-level overview of Azure. It will provide foundational level knowledge of cloud services and how those services are provided with Microsoft Azure.

For further details about this course, please visit:

Apply for the Course and Microsoft Sponsorship

Eligible courses will be displayed on the Athena Pathways website and updated regularly.

There are a limited number of scholarships available, and as such, are not guaranteed to all applicants. Completion of an application form along with proof of successful completion of your
course/workshop will be required as part of the application process.