Deep Learning with Keras


Use python to build deep learning models for regression and classification. Learn how to create, train, evaluate and tune neural networks using Python and Keras.

Duration: 2 days

Who is it for: Anyone who has an interest in deep learning using Keras

Layout: This is an intense, fast paced course containing a lot of theory and modelling content, pdfs and coding exercises.


Introduction to Machine Learning, Deep Learning, and Generative AI.

  • Machine Learning vs Deep Learning vs Generative AI
  • Supervised, Unsupervised and Reinforcement Learning
  • Structure of artificial neural networks

Overview of machine learning and deep learning concepts.

  • Introduction to deep learning and its applications
  • Weights and Bias
  • Cost functions
  • Back propagation

Building blocks of neural networks.

  • Hands-on exercises using Keras for regression and classification.
  • Perceptrons
  • Activation Functions
  • Weights and Bias
  • Cost functions
  • Back propagation
  • Test, Train and Validation Data

Image processing.

  • Convolutional Neural Networks
  • CNN Hyperparameters
  • LeNet-5 Architecture
  • CNN Design
  • Residual Networks
  • Transfer Learning

Natural language processing.

  • NLP Definitions
  • Embeddings & Vectors
  • Classification Metrics
  • NLP Deep Learning Architectures
  • CNN, RNN, LSTM Architectures

Advanced topics in deep learning.

  • Guidance on further exploration and resources
  • Where to source Data
  • Hyperparameter tuning
  • Popular Deep Learning Libraries
  • Software 2.0
  • Advances in Technology

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