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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

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Applied Deep Learning Capstone

This course includes

5 Weeks

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

12,295

Audit For Free

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

Deep Learning
Neural Networks
Keras
PyTorch
Data Preprocessing
Model Validation
Machine Learning Pipeline
Project Management

This course includes:

PreRecorded video

Graded assignments, exams

Access on Mobile, Tablet, Desktop

Limited Access access

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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

Joseph Santarcangelo
Joseph Santarcangelo

4.9 rating

18,630 Reviews

17,12,849 Students

33 Courses

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.

Applied Deep Learning Capstone

This course includes

5 Weeks

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

12,295

Audit For Free

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.7 course rating

6 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.