This is the second of two courses in the UBC Micro-certificate in Artificial Intelligence Cloud Solutions Strategy.
Artificial Intelligence (AI) is a vast field of technologies that, when combined with cloud services, can help your organization create a robust decision-making framework to improve customer service, efficiency and performance with little-to-no human involvement.
The number of AI-based and Machine Learning (ML) services commercially available in the market is ever-expanding. To be a smart consumer, you need to be able to identify the relevant technology, theory and data underlying contemporary data services, so that you can formulate meaningful questions and make informed choices.
In this course, you take a deep dive into the technical implementation of AI applications and services within a cloud computing framework and learn how to design solutions with AI to improve customer experiences, business processes and decision-making.
Come away with a strategy to add AI to your own real-world project and learn how to assess and select the right infrastructure for high-performance and low-cost instances optimized for Machine Learning.
You’ll also be encouraged to upskill with additional online training and hands-on tutorials through freely available resources.
Technical and coding skills are not required to take this course. It is designed to accommodate professionals in non-technical or tech-adjacent roles.
Course Outline
Week 1: Explore a range of contemporary AI and ML services commercially available in the market today and get to know the key players.
Week 2: Learn the difference between structured and unstructured data algorithms and how they are used to achieve desired outcomes.
Week 3: Gain an understanding of advanced ML algorithms and how they can provide insights to benefit your organization.
Week 4: Take a closer look at AI and the neural network category of AI cloud services.
By the end of this course, you’ll be able to:
- Analyze the state of the ML and AI commercial services market and recognize the main players within it
- Identify the four basic categories of AI services: prediction, structured data, unstructured data and neural networks
- Assess and choose the right infrastructure for high-performance and low-cost instances optimized for Machine Learning
- Apply your knowledge with hands-on tutorials through freely available resources
How am I Assessed?
You’re assessed on successfully completing weekly activities, including your contributions to discussion posts and applied case study projects (based on real-life scenarios). These activities are marked using a proficiency scale, and your instructor provides you informal feedback in the live sessions.
While you’re not assessed on your attendance of the live sessions, we encourage you to attend these classes, so you don’t miss the opportunity to learn and interact with your instructor and other participants. All sessions are recorded in case you miss one.
Expected Effort
Expect to spend approximately 5–7 hours a week completing all learning activities, including attending the live online sessions.
Technology Requirements
To take this course, you’ll need access to:
- an email account
- a computer, laptop or tablet, using Windows or macOS
- the latest version of a web browser (or previous major version release)
- a reliable internet connection
- a video camera and microphone
Textbooks
There are no textbooks for this course.
Course Format
This 100% online program is instructor-supported with real-time classes and combines self-paced independent study and weekly 1.5-hour live online sessions. These live, virtual classes are also recorded.
Outside of class time, you can access online materials at your own pace. Each week, you’ll have an opportunity to review readings and videos, apply your knowledge in exercises and case studies, contribute to a discussion board and connect with other students.
One business day before the course start date, we’ll email you step-by-step instructions for accessing your course.