AI Capstone Project with Deep Learning

AI Capstone Project with Deep Learning

This course is part of multiple programs.

Instructors: Alex Aklson

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

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 4 modules in this course

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.

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

4 videosTotal 7 minutes

Introduction2 minutesPreview module
Choose One Library Only (PyTorch or Keras)0 minutes
1.0 Loading data.1 minute
Keras Stream3 minutes

3 assignmentsTotal 40 minutes

Download Data10 minutes
Loading Data with Keras30 minutes
Opt-in to receive your badge!0 minutes

2 app itemsTotal 120 minutes

Lab: Loading Data60 minutes
Loading Data with Keras60 minutes

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.