Introduction to Deep Learning

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Course overview
  • Level: Intermediate | EQF 5/6
  • Study time: 10-12 hours
  • Assessment: 60 activities

Course Prerequisites:
To take this course, you should have basic knowledge in:

  • Calculus (derivatives, integrals)
  • Programming (Python)
  • Optimization (e.g., gradient descent)
  • Machine Learning (regression, classification)
Course overview
The Introduction to Deep Learning

course introduces you to the key techniques and models driving modern AI. You’ll explore foundational concepts like Regression, Classification, and Neural Networks (MLPs, CNNs, RNNs) used in applications such as image recognition and NLP. The course also covers advanced models like Transformers and GANs, which are transforming industries like entertainment and autonomous vehicles. With hands-on labs, you’ll gain practical experience in building and optimizing deep learning models, preparing you to tackle real-world AI challenges.

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Certification included
Upon completing the course, you will receive a Certificate of Completion that can be added to your resume and LinkedIn profile, recognizing your mastery of AI concepts and skills.

Course contents

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