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
This course is part of the IBM AI Engineering Professional Certificate
AI Capstone Project with Deep Learning
Offered By
100% online
Course 6 of 6 in the
Flexible deadlines
Advanced Level
Approx. 17 hours to complete
English
Syllabus - What you will learn from this course
Module 1 - Loading Data
Module 2
In this Module, you mainly learn how process image data and prepare it to build a classifier using pre-trained models.
Module 3
Module 4
Instructors
Alex Aklson
Ph.D., Data Scientist
Joseph Santarcangelo
Ph.D., Data Scientist at IBMAbout IBM
About the IBM AI Engineering Professional Certificate
Frequently Asked Questions
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Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
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