AI Capstone Project with Deep Learning (Coursera)

Learning Outcomes:

• determine what kind of deep learning method to use in which situation

• know how to build a deep learning model to solve a real problem

• master 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

Course 6 of 6 in the IBM AI Engineering Professional Certificate

Syllabus

WEEK 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.

WEEK 2

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

WEEK 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.

WEEK 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.