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IBM: 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.

Applied Deep Learning Capstone Project
5 weeks
2–4 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

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Starts Mar 27
Ends Jun 30

About this course

Skip 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'lluse a Deep Learning library ofyour choice to develop, train, and test a Deep Learning model.Loadand 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 yourmodel andyour proficiency in the field of deep learning.

Awards

Applied Deep Learning Capstone Project

At a glance

  • Institution: IBM
  • Subject: Data Analysis & Statistics
  • Level: Advanced
  • Prerequisites:
    • Completed all courses in the Deep Learning Professional Certification Program
  • Language: English
  • Video Transcript: English
  • Associated programs:
  • Associated skills:Keras (Neural Network Library), Deep Learning, PyTorch (Machine Learning Library), Data Preprocessing

What you'll learn

Skip 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

Who can take this course?

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This course is part of Deep Learning Professional Certificate Program

Learn more 
Expert instruction
6 skill-building courses
Self-paced
Progress at your own speed
7 months
2 - 4 hours per week

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