Deep Learning Fundamentals

  • Free
  • Certificate included
  • Course certificate
  • 3 hours
Provider
IBM
Cost
Free
Certificate
Included, free
Duration
3 hours
Format
Self-paced
Language
English
Subjects
Data Science, Computer Science
Source
IBM SkillsBuild
Last verified
14 Sep 2026

Deep Learning Fundamentals, course code ML0115EN, is a concept-only crash course produced by DeepLearning.TV and hosted on Cognitive Class. The page states an estimated effort of three hours, describes the course as free and self-paced with no prerequisites, and says it can be audited as many times as you wish; it does not state a level. Four modules of short concept videos run in order: deep learning concepts, covering what a neural network is, why deep learning matters, how to choose between networks, the vanishing gradient problem, restricted Boltzmann machines and deep belief networks; more concepts, including convolutional networks, recurrent nets, autoencoders, recursive neural tensor networks and use cases; platforms for deep learning; and deep learning software libraries.

The page notes the platform and library modules discuss tools of their era, so treat the fourth module as historical context. There is no coding and no maths beyond intuition; the aim is to show that the ideas are simpler than they sound before you pick a framework. The course is free of charge and the page says a certificate is offered on completion at no cost.

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What you’ll learn

  • Explain what a neural network is and why deep learning became practical
  • Describe the vanishing gradient problem, restricted Boltzmann machines and deep belief networks
  • Compare convolutional, recurrent, autoencoder and recursive neural tensor networks and their use cases
  • Survey deep learning platforms and software libraries

Who it’s for

Curious beginners who want the ideas behind neural networks in an afternoon; skip it if you already train models and want hands-on TensorFlow or PyTorch work.

Source: IBM SkillsBuild (opens in a new tab) · Verified · Report a change

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