DATA 027 - Foundations in Applied Machine Learning - Citizen Development
Course Description
Embark on a transformative learning journey where you'll explore the core principles of Artificial Intelligence (AI) / Machine Learning (ML). Machine learning is a branch of artificial intelligence that enables computers to learn and make decisions without explicit programming. It involves the development of algorithms that enable systems to analyze data, recognize patterns and improve performance over time.
From the basics to more advanced techniques, you'll learn to identify opportunities for machine learning. You'll explore how to clearly define machine learning problems and use data science techniques to analyze and solve business problems. Our hands-on approach in this course focuses on tabular data, guiding you through the creation of supervised learning solutions. Gain expertise in the entire modeling process, from constructing classifications to evaluating models that solve business problems and elevate business strategies.
The course experience is designed and delivered in partnership with Braintoy, the creator of Canada's first low-code / no-code applied machine learning platform. It is well suited to individuals who are technically curious but not necessarily technically experienced. If you have an interest and aptitude for learning new technologies this course has been designed with you in mind. The course offers an applied experience using a low-code / no-code environment to build and evaluate supervised learning models. No prior programming experience is required. The course will provide you with a citizen developer skillset in supervised learning. A citizen developer skillset empowers individuals, typically with non-technical backgrounds, to create and customize solutions without extensive coding. It promotes agility, innovation and self-sufficiency within the workplace, allowing you to contribute actively to the development and improvement of solutions that support business functions within your current and future roles.
Note: Registration for this course closes two days before the course start date.
Learner Outcomes
Upon successful completion of this course, you will be able to:- evaluate data for a use case through data science techniques
- outline the steps of the modelling process and aspects of data science that can be used to solve a problem and create value for an organization
- analyze and prepare data for modelling through data wrangling and preprocessing
- build classification models used to solve problems for an organization.
Earn a Micro-Credential
This course qualifies for the SAITMicro badge. Students who successfully complete this course with a final grade of A- (80%) or higher will earn a micro-credential and receive a shareable digital badge. Learn more.
Prerequisites
There are no prerequisites for this course.Applies Towards the Following Certificates
- Applied Machine Learning Certificate of Completion : Applied Machine Learning Certificate of Completion