AI Capstone Project with Deep Learning

IBM via Coursera

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Overview

“AI Capstone Project with Deep Learning” is an advanced, hands-on course designed for learners ready to apply their AI and deep learning knowledge in a comprehensive, real-world project. This capstone experience integrates key concepts, techniques, and tools from deep learning to solve complex problems, enabling participants to showcase their skills through a practical, end-to-end AI solution. The course guides students through project planning, data collection, model design, training, evaluation, and deployment phases. Emphasis is placed on selecting appropriate neural network architectures—such...

Syllabus

Module 1 - Loading Data

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.

Module 2

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

Module 3

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.

Module 4

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.