Overview:
In this comprehensive foundations course, students will learn the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML). From the basics to more advanced techniques students will learn to identify opportunities for AI. They will learn to clearly define ML/AI problems and use data science techniques to analyze and solve business problems. They will build supervised and unsupervised learning solutions and explore the modelling process which includes: How to build classification, regression, deep learning, and clustering models; data wrangling and preprocessing; how to create an AI governance framework, and how to build a model development pipeline for ML solutions. Students will also learn to integrate deployed microservices/API models into end-user applications, and how to deploy a variety of models using both low code, no code platforms and Python.
Delivery Format:
This course is designed to be delivered online in a hybrid format that combines synchronous and asnchronous delivery.
Full details and licensing options available upon request.