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Certification

Certification in Building Neural Network and NLP Models

Become certified in AI concepts and neural network engineering. You'll prove you can build CNNs for image recognition, implement RNNs for sequence modeling, and apply NLP techniques to real problems,skills ready for immediate use.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner · Intermediate
IT and developmentScience and researchProduct development
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The exam

Take the certification exam

Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 15 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01What is AI?30:20
  2. 02Introduction to deep learning85:11
  3. 03Convolutional neural networks40:30
  4. 04CNN architecture29:36
  5. 05Applying networks and padding23:57
  6. 06Types of padding105:19
  7. 07Filter values19:48
  8. 08Recurrent neural networks63:39
  9. 09RNN architecture and embeddings39:27
  10. 10Tanh, memory and RNN summary25:37
  11. 11Named entity recognition40:01
  12. 12NLP and NLG22:41
  13. 13The NLP pipeline and lemmatization33:31
  14. 14Stop words, parsing and POS tagging36:17
  15. 15Hands-on NLP and project ideas41:56
About the course

The Master AI Concepts: Neural Networks, CNNs, RNNs & NLP (Video Course) certification is designed for anyone who's ready to move beyond being a passive user of AI. You'll gain practical skills that translate directly into increased productivity, improved decision-making, and a future-proof career built on adaptability and growth. If you've ever wondered what's actually happening under the hood, this course gives you the clarity and confidence to start building with AI yourself.

This certification covers the following topics:

  • What Artificial Intelligence Actually Is
  • The Four Types of Artificial Intelligence
  • Understanding Digital Images: Pixels and Representation
  • Neural Network Architecture: The Foundation
  • Convolutional Neural Networks: How They Work
  • Recurrent Neural Networks: Processing Sequential Data
  • Natural Language Processing: The Complete Pipeline
  • NLP in Action: Sentiment Analysis on Airline Data
  • Emerging Technology: Model Context Protocol (MCP) Servers
  • Practical AI Projects to Build Your Skills
  • Best Practices for Learning AI Effectively