4.5
stars
441 ratings

Alex Aklson +1 more instructor

14,614 already enrolled

Offered By

IBM Skills Network

About this Course

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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.
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

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Advanced Level

Approx. 15 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Advanced Level

Approx. 15 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.51/5 (66 Ratings)

Alex Aklson

Ph.D., Data Scientist

807,926 Learners

22 Courses

Joseph Santarcangelo

Ph.D., Data Scientist at IBM

IBM Developer Skills Network

925,904 Learners

26 Courses

Offered by

IBM Skills Network

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Module 1 - Loading Data

3 hours to complete

4 videos (Total 8 min)

Week2

Week 2

3 hours to complete

Module 2

3 hours to complete

1 video (Total 2 min)

Week3

Week 3

3 hours to complete

Module 3

3 hours to complete

1 video (Total 2 min)

Week4

Week 4

7 hours to complete

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.

7 hours to complete

1 video (Total 3 min), 2 readings, 2 quizzes

Reviews

4.5

82 reviews

5 stars
69.75%
4 stars
18.96%
3 stars
7.67%
2 stars
1.80%
1 star
1.80%

TOP REVIEWS FROM AI CAPSTONE PROJECT WITH DEEP LEARNING

by SMJul 23, 2020

Very Good course. Learnt a lot from this course. Also got good hands-on experience.

by MPFeb 12, 2021

The Keras part of the course is more attractive just because its final assignment is much better structured than that of PyTorch.

by TGJan 27, 2021

Great course content! One thing that can be improved is the Skills Network portal. It's incredibly difficult to train any of the pre-trained models there.

by MADec 19, 2022

This Project was simply outstanding for the deep learning point of view

View all reviews

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