This course explores the foundational and applied aspects of machine learning techniques used to analyze image and time-series data, with a focus on healthcare applications. Learners will gain hands-on experience in designing models that detect brain tumors from MRI scans and predict clinical events such as sepsis onset using patient vital signs.

Computer Vision and Sequence Analysis in Machine Learning
访问权限由 Coursera Learning Team 提供
您将学到什么
Analyze the unique structure and dimensionality of image data compared to tabular data.
Build and optimize convolutional neural networks (CNNs) for medical image classification and segmentation.
Apply transfer learning to improve model performance on limited datasets.
您将获得的技能
要了解的详细信息

添加到您的领英档案
4 项作业
January 2026
了解顶级公司的员工如何掌握热门技能

该课程共有4个模块
The first module explores images and the vital role their data structure plays in computer vision.
涵盖的内容
3个视频1篇阅读材料1个作业
In the second module, we explore more building blocks of computer vision and begin working with real-life datasets.
涵盖的内容
6个视频1个作业2个编程作业
This module introduces learners to time series analysis using real-world datasets focused on human activity.
涵盖的内容
4个视频1个作业1个编程作业
This module introduces advanced techniques for identifying state transitions in time series data.
涵盖的内容
5个视频1个作业1个编程作业
位教师

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.







