In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning.
AI Capstone Project with Deep Learning
AI Capstone Project with Deep Learning
This course is part of multiple programs.
Instructors: Alex Aklson
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Gain insight into a topic and learn the fundamentals.
4.5
(634 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.
Skills you'll gain
Details to know
Shareable certificate
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Assessments
7 assignments
Taught in English
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This course is available as part of
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- Learn new concepts from industry experts
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- 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
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4.5
634 reviews
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JK
5
Reviewed on Jul 18, 2023
Thank you, good course working with large dataset is use a lot of time but that is good to practice.
SM
5
Reviewed on Jul 23, 2020
Very Good course. Learnt a lot from this course. Also got good hands-on experience.
RB
5
Reviewed on May 22, 2020
A very nice project based course to get hands on experience with deep learning and transfer learning.
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