AI Capstone Project with Deep Learning
Apply advanced deep learning concepts to build and evaluate image classification models using PyTorch and Keras.
Apply advanced deep learning concepts to build and evaluate image classification models using PyTorch and Keras.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM AI Engineering Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.5
(561 ratings)
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Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Build and implement deep learning models for image classification
Master data preprocessing techniques for computer vision
Utilize transfer learning with pre-trained models
Evaluate and compare model performance
Present and communicate project outcomes effectively
Develop end-to-end deep learning solutions
Skills you'll gain
This course includes:
0.2 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This advanced capstone project focuses on applying deep learning concepts to solve real-world image classification problems. Students work with both PyTorch and Keras to build and evaluate models using pre-trained architectures like ResNet and VGG16. The curriculum covers data loading, preprocessing, model development, and performance evaluation through hands-on implementation and peer review assessments.
Loading Data
Module 1 · 2 Hours to complete
Data Preparation
Module 2 · 2 Hours to complete
Building Classifiers
Module 3 · 2 Hours to complete
Final Project
Module 4 · 8 Hours to complete
Fee Structure
Instructors
Dr. Alex Aklson: Crafting Data-Driven Solutions and Innovating Smart Health Systems at IBM
Dr. Alex Aklson is a data scientist in IBM Canada’s Digital Business Group, where he has contributed to innovative projects, including the development of a smart system to detect early signs of dementia by analyzing walking speed and home activity patterns in older adults. Prior to IBM, Alex worked at Datascope Analytics in Chicago, where he crafted data-driven solutions using a human-centered approach. He holds a Ph.D. in Biomedical Engineering from the University of Toronto.
Pioneering Data Scientist Bridging AI Research and Education
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
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4.5 course rating
561 ratings
Frequently asked questions
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