Applied Deep Learning Capstone
Master practical deep learning by building real models using Keras or PyTorch. Create, train, and validate solutions for real-world problems.
Master practical deep learning by building real models using Keras or PyTorch. Create, train, and validate solutions for real-world problems.
This intensive capstone project challenges students to apply advanced deep learning concepts in a practical setting. Participants will develop, train, and test deep learning models using either Keras or PyTorch frameworks. The course emphasizes hands-on experience with real-world data, requiring students to handle the entire machine learning pipeline from data preprocessing to model validation. Students will demonstrate their expertise through a comprehensive project report, showcasing their ability to implement effective deep learning solutions and communicate technical results professionally.
4.7
(6 ratings)
10,907 already enrolled
Instructors:
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What you'll learn
Select appropriate deep learning methods for specific problems
Build and validate deep learning models using real-world data
Implement complete deep learning pipelines from preprocessing to validation
Optimize models using advanced deep learning techniques
Present and communicate technical results effectively
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Module Description
This capstone project focuses on applying deep learning concepts to real-world problems. Students will develop complete deep learning solutions using either Keras or PyTorch, covering the entire machine learning pipeline from data preprocessing to model validation. The course emphasizes practical implementation and project presentation skills, preparing participants for professional deep learning roles.
Fee Structure
Instructor
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.
Testimonials
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4.7 course rating
6 ratings
Frequently asked questions
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