SAIT

Calgary, Alberta, Canada

Participating as an Industry Partner will bring new perspectives to your current product development process. If you are new to the world of UX design, you will have the opportunity to collaborate and experience what it’s like to have a designer on the team. The discovery artifacts and the MVP prototype you end up with will be a great resource for you and your team to build upon or iterate from as your product evolves over time. If you already have a design team, this is a great chance to bring in a fresh set of eyes, who is bias free towards your product and eager to make a positive impact. This collaboration may also highlight opportunities to improve your current workflows.

SAIT

Calgary, Alberta, Canada

Participating as an Industry Partner will bring new perspectives to your current product development process. If you are new to the world of UX design, you will have the opportunity to collaborate and experience what it’s like to have a designer on the team. The discovery artifacts and the MVP prototype you end up with will be a great resource for you and your team to build upon or iterate from as your product evolves over time. If you already have a design team, this is a great chance to bring in a fresh set of eyes, who is bias free towards your product and eager to make a positive impact. This collaboration may also highlight opportunities to improve your current workflows.

SAIT

Calgary, Alberta, Canada

Students from the SAIT's Applied Machine Learning Bootcamp and our Applied Product Management Bootcamp participate in a 78 hour interdisciplinary machine learning capstone project. This project culminates in the development of a machine learning model that predicts, detects, or forecasts an entity. The data for the use case could be images (computer vision), text (natural language processing), time series (multi-variate or univariate), or tablular data. The data format would be a folder of images or comma-separated values (CSVs) for text, time series, or tablular data. The client will need to: 1) Provide a clearly defined machine learning problem. 2) Explain how the client intends to use the solution. 3) Explain why this problem needs to be solved. 4) Provide a subject matter expert that can be a touch point for the student and answer questions related to the data and use case.

SAIT

Calgary, Alberta, Canada

Students from the SAIT's Applied Machine Learning Bootcamp and our Applied Product Management Bootcamp participate in a 78 hour interdisciplinary machine learning capstone project. This project culminates in the development of a machine learning model that predicts, detects, or forecasts an entity. The data for the use case could be images (computer vision), text (natural language processing), time series (multi-variate or univariate), or tablular data. The data format would be a folder of images or comma-separated values (CSVs) for text, time series, or tablular data. The client will need to: 1) Provide a clearly defined machine learning problem. 2) Explain how the client intends to use the solution. 3) Explain why this problem needs to be solved. 4) Provide a subject matter expert that can be a touch point for the student and answer questions related to the data and use case.