Advanced Certificate in Applied Artificial Intelligence (AI) Programming Module 4: Deep Learning Fundamentals (Synchronous E-Learning)
Training Provider: SINGAPORE MANAGEMENT UNIVERSITY
Course Reference: TGS-2024049057
S$600
Original: S$2,000
Save S$1,400
About This Course
Deep Learning is a branch of machine learning that utilises neural networks. But how does a neural network work, and how does deep learning solve machine learning problems? In this module, participants will learn how to get started with deep learning using one of the most popular application programming interfaces (APIs) for implementing deep learning – Keras (built on top of TensorFlow). They will also use another API – fastai, which is built on top of PyTorch, to make deep learning more user-friendly and accessible.
What You'll Learn
At the end of the 2-day module, participants will be able to:
• Understand what is a neural network
• Understand the various types of neural network such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Transformer, etc
• Learn the various features of a neural network – layers, weights and biases, activation functions, back propagation, loss functions, optimisers, and more
• Build models to perform face detection and face recognition
• Use the Keras application programming interface (API) to create neural network and train models using sample datasets
• Use the fastai API to build deep learning models
• Understand what is a neural network
• Understand the various types of neural network such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Transformer, etc
• Learn the various features of a neural network – layers, weights and biases, activation functions, back propagation, loss functions, optimisers, and more
• Build models to perform face detection and face recognition
• Use the Keras application programming interface (API) to create neural network and train models using sample datasets
• Use the fastai API to build deep learning models
Entry Requirements
• Basic programming experience using Python
• Knowledge of NumPy and Pandas (covered in Module 2)
Course Details
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