Microsoft Digital Skills - Azure Data Scientist - (2023)
Timeline
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July 1, 2023Experience start
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July 5, 2023Project Scope Meeting
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December 16, 2023Experience end
Timeline
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July 1, 2023Experience start
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July 5, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
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December 16, 2023Experience end
Categories
Machine learning Artificial intelligence Data visualization Data analysis Data modellingSkills
microsoft azure machine learning model training data science data ingestion digital literacy machine learning microsoft certified professional forecastingSaskatchewan Polytechnic is the first post-secondary institution in Canada to become a Microsoft in Education Global Training Partner.
As a Microsoft in Education Global Training Partner, Saskatchewan Polytechnic offers a range of services provided by fully qualified Microsoft Certified trainers and Microsoft Certified Educators, delivering official Microsoft Learn Curriculum in Microsoft Technical Certifications, Microsoft Fundamentals as well as Microsoft Certified Educator content.
This posting is for a course to prepare students for the following Microsoft Role: Azure Data Scientist.
These courses run on a rolling basis throughout the year - please submit to this posting if your project is to be completed in 2023. For projects running future other timeframes, please refer to our subportal on Riipen.
Students in this course are all enrolled in the School of Continuing Education and therefore are more experienced in the workforce.
This will be dependent on the scope of the given project. This could include:
A report and/or presentation showing the student's findings and projections on how their changes will affect your business.
Some potential project examples:
- Create and train machine learning models from data to make predictions. Can include deploying a trained model to the cloud.
- Tune hyperparameters of existing machine learning models for optimization. Includes tracking model versions and efficiently searching the hyperparameter space.
- Create a machine learning pipeline consisting of multiple steps in the machine learning process. Can include data ingestion and model deployment steps.
Project timeline
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July 1, 2023Experience start
-
July 5, 2023Project Scope Meeting
-
December 16, 2023Experience end
Timeline
-
July 1, 2023Experience start
-
July 5, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
December 16, 2023Experience end
Project Examples
In this course, students will learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches how to leverage existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.
This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
Students in this course will be developing the skillset required to successfully write the DP-100: Design and Implementing a Data Science Solution on Azure
Companies must answer the following questions to submit a match request to this experience:
A representative of the company will be available for a pre-selection discussion with the administrator of the course to review the project scope.
A representative of the company will be available to answer questions from students in a timely manner for the duration of the project.
Timeline
-
July 1, 2023Experience start
-
July 5, 2023Project Scope Meeting
-
December 16, 2023Experience end
Timeline
-
July 1, 2023Experience start
-
July 5, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
December 16, 2023Experience end