IBM
AI Capstone Project with Deep Learning
IBM

AI Capstone Project with Deep Learning

This course is part of multiple programs.

Alex Aklson
Joseph Santarcangelo

Instructors: Alex Aklson

Sponsored by Southeastern University

27,267 already enrolled

Gain insight into a topic and learn the fundamentals.
4.5

(586 reviews)

Advanced level
Designed for those already in the industry
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(586 reviews)

Advanced level
Designed for those already in the industry
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build a deep learning model to solve a real problem.

  • Execute the process of creating a deep learning pipeline.

  • Apply knowledge of deep learning to improve models using real data.

  • Demonstrate ability to present and communicate outcomes of deep learning projects.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate from IBM
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There are 4 modules in this course

In this module, you will get introduced to the problem that we will try to solve throughout the course. You will also learn how to load the image dataset, manipulate images, and visualize them.

What's included

4 videos3 assignments2 app items

In this Module, you will mainly learn how to process image data and prepare it to build a classifier using pre-trained models.

What's included

1 video2 assignments2 app items

In this Module, in the PyTorch part, you will learn how to build a linear classifier. In the Keras part, you will learn how to build an image classifier using the ResNet50 pre-trained model.

What's included

1 video2 assignments2 app items

In this Module, in the PyTorch part, you will complete a peer review assessment where you will be asked to build an image classifier using the ResNet18 pre-trained model. In the Keras part, for the peer review assessment, you will be asked to build an image classifier using the VGG16 pre-trained model and compare its performance with the model that we built in the previous Module using the ResNet50 pre-trained model.

What's included

1 video2 peer reviews1 app item

Instructors

Instructor ratings
4.5 (95 ratings)
Alex Aklson
IBM
22 Courses1,155,374 learners

Offered by

IBM

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4.5

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Reviewed on May 22, 2020

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