Applied Deep Learning Capstone Project
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In this capstone project, you'll use either Keras or PyTorch to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it.
Language
- English
Topic
- Deep Learning
Skills You Will Learn
- Data Preprocessing, Deep Learning, Keras (Neural Network Library), PyTorch (Machine Learning Library)
Offered By
- IBMSkillsNetwork
Estimated Effort
- 15 hours
Platform
- edX
Last Update
- June 4, 2025
About this Course
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
In this capstone project, you'll use a Deep Learning library of your choice to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it.
Finally, you will present a project report to demonstrate the validity of your model and your proficiency in the field of deep learning.
Course Syllabus
Chapter 1 - Loading Data
1.1 Loading Data - PyTorch
- Video: Loading Data - PyTorch
- Lab: Loading Data - PyTorch
- Quiz: Loading Data - PyTorch
1.2 Loading Data - Keras
- Video: Loading Data -Keras
- Lab: Loading Data - Keras
- Quiz: Loading Data - Keras
Chapter 2 - Data Preparation
- Learning Objectives
2.1 Processing Data - PyTorch
- Video: Image Preprocessing PyTorch
- Lab: Processing Data - PyTorch
- Quiz: Processing Data - PyTorch
2.2 Processing Data - Keras
- Video: Processing Data - Keras
- Lab: Processing Data - Keras
- Quiz: Processing Data - Keras
Chapter 3 - Assessment Training Model
- Learning Objectives
3.1 Training Models - PyTorch
- Video: Pre-trained Models PyTorch
- Lab: Training Model - PyTorch
- Peer Review: Training Models - PyTorch
3.2 Training Models - Keras
- Video: Pre-trained Models in Keras
- Lab: Training Models - Keras
- Peer Review: Training Models - Keras
Chapter 4 - Compare Two Models
- Learning Objectives
4.1 Compare Two Models - PyTorch
- Instruction: Compare Two Models - PyTorch
- Lab: Compare Two Models - PyTorch
- Quiz: Compare Two Models - PyTorch
4.2 Compare Two Models - Keras
- Instruction: Compare Two Models - Keras
- Lab: Compare Two Models - Keras
- Quiz: Compare Two Models - Keras
What you'll learn
- 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
Recommended Skills Prior to Taking this Course
Completed all courses in the Deep Learning Professional Certification Program
Language
- English
Topic
- Deep Learning
Skills You Will Learn
- Data Preprocessing, Deep Learning, Keras (Neural Network Library), PyTorch (Machine Learning Library)
Offered By
- IBMSkillsNetwork
Estimated Effort
- 15 hours
Platform
- edX
Last Update
- June 4, 2025
Instructors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
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