Deep learning is the engine behind today’s most remarkable AI breakthroughs, from image recognition and natural language to generative models that are reshaping entire industries. This program takes participants deep into neural networks, building both the conceptual understanding and the practical skills to design, train, and deploy deep learning models that solve real problems.
As deep learning drives the AI revolution, professionals who can build and apply neural networks are among the rarest and most highly rewarded in technology. This course combines rigorous hands-on model building with clear conceptual grounding and focuses throughout on emerging trends in deep learning that define the cutting edge of artificial intelligence.
Course Objectives
Upon the successful completion of this program, attendees will be able to:
- Understand deep learning concepts and applications
- Explain how neural networks work
- Apply the fundamentals of perceptrons and layers
- Understand activation functions
- Apply forward and backward propagation
- Train neural networks with gradient descent
- Apply loss functions and optimisation
- Build models with deep learning frameworks
- Design and train deep neural networks
- Apply convolutional neural networks (CNNs)
- Apply recurrent neural networks (RNNs)
- Prevent overfitting with regularisation
- Apply transfer learning techniques
- Evaluate and tune deep learning models
- Deploy deep learning models
- Apply emerging trends in deep learning and generative AI
Course Outline
- Module 1: Deep Learning Concepts & Applications
- Module 2: How Neural Networks Work
- Module 3: Perceptrons, Layers & Architecture
- Module 4: Activation Functions
- Module 5: Forward & Backward Propagation
- Module 6: Training with Gradient Descent
- Module 7: Loss Functions & Optimisation
- Module 8: Deep Learning Frameworks
- Module 9: Designing & Training Deep Networks
- Module 10: Convolutional Neural Networks (CNNs)
- Module 11: Recurrent Neural Networks (RNNs)
- Module 12: Regularisation & Overfitting Prevention
- Module 13: Transfer Learning
- Module 14: Model Evaluation, Tuning & Deployment
- Module 15: Emerging Trends: Generative AI & Advanced Architectures
Who Should Attend
This course is intended for data scientists, machine learning practitioners, developers, and engineers who want to build deep learning and neural network skills. A foundation in Python and basic machine learning is recommended.
Registration & Inquiry
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