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URL: https://www.coursera.org/learn/computer-vision-and-sequence-analysis-in-machine-learning

⇱ Computer Vision and Sequence Analysis in Machine Learning | Coursera


Computer Vision and Sequence Analysis in Machine Learning

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Computer Vision and Sequence Analysis in Machine Learning

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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.

Details to know

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Recently updated!

January 2026

Assessments

4 assignments

Taught in English

There are 4 modules in this course

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.

You’ll also gain exclusive insights from a now-retired, globally recognized pioneer in medical technologyβ€”whose decades-long career shaped the field and who now shares hard-earned wisdom to inspire and guide the next generation of innovators. This course is ideal for: β€’ Healthcare professionals (e.g., clinicians, nurses, administrators) looking to understand how AI and machine learning can enhance patient care and operational efficiency. β€’ Data scientists and analysts working in or transitioning to the healthcare industry. β€’ Students and researchers in fields like biomedical engineering, public health, or health informatics who want a practical introduction to ML in clinical contexts. β€’ Healthcare innovators and tech entrepreneurs aiming to build or evaluate AI-driven healthcare solutions.

The first module explores images and the vital role their data structure plays in computer vision.

What's included

3 videos1 reading1 assignment

3 videosβ€’Total 17 minutes
  • What Sets Images Apartβ€’6 minutes
  • Shape of Dataβ€’4 minutes
  • Journey Through 50 Years of Changing Technologyβ€’7 minutes
1 readingβ€’Total 10 minutes
  • Course Syllabusβ€’10 minutes
1 assignmentβ€’Total 30 minutes
  • Module 1 Assessmentβ€’30 minutes

In the second module, we explore more building blocks of computer vision and begin working with real-life datasets.

What's included

6 videos1 assignment2 programming assignments

6 videosβ€’Total 29 minutes
  • Convolutional Neural Networkβ€’5 minutes
  • Computer Vision Refresher and a Working CNN Exampleβ€’7 minutes
  • CNN Working Example, Part 2β€’6 minutes
  • Defining Transfer Learningβ€’2 minutes
  • A Transfer Learning Exampleβ€’4 minutes
  • Segmentation and Interpretabilityβ€’5 minutes
1 assignmentβ€’Total 45 minutes
  • Module 2 Assessmentβ€’45 minutes
2 programming assignmentsβ€’Total 360 minutes
  • Computer Vision CNNβ€’180 minutes
  • Computer Vision Transfer Learningβ€’180 minutes

This module introduces learners to time series analysis using real-world datasets focused on human activity.

What's included

4 videos1 assignment1 programming assignment

4 videosβ€’Total 21 minutes
  • Time Series Analysisβ€’6 minutes
  • 1D Convolutional and Recurrent Neural Networksβ€’3 minutes
  • Time Series Example Part 1: Human Activity Datasetβ€’6 minutes
  • Time Series Example Part 2: Human Activity Datasetβ€’5 minutes
1 assignmentβ€’Total 30 minutes
  • Module 3 Assessmentβ€’30 minutes
1 programming assignmentβ€’Total 180 minutes
  • Time Series Human Activityβ€’180 minutes

This module introduces advanced techniques for identifying state transitions in time series data.

What's included

5 videos1 assignment1 programming assignment

5 videosβ€’Total 20 minutes
  • State Transition in Time Seriesβ€’3 minutes
  • Robust Principal Component Analysisβ€’2 minutes
  • Enduring Power of Certain Technologiesβ€’5 minutes
  • Preparing for the Upcoming Applied Sequence Analysisβ€’2 minutes
  • Sequence Analysis Datasetβ€’7 minutes
1 assignmentβ€’Total 30 minutes
  • Module 4 Assessmentβ€’30 minutes
1 programming assignmentβ€’Total 180 minutes
  • RPCA and Hidden Markovβ€’180 minutes

Instructor

Cleveland Clinic
2 Coursesβ€’947 learners

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