AI & Machine Learning
Deep Learning & Neural Networks
Architect and train neural networks with TensorFlow and PyTorch.
5 DaysAdvancedTensorNova Certificate of Completion
Course Curriculum
Module 1Neural Network Foundations
- Perceptrons and multi-layer networks
- Activation functions and weight initialisation
- Backpropagation and gradient descent
- Batch normalisation and dropout regularisation
Module 2Convolutional Neural Networks
- CNN architecture: conv, pooling, FC layers
- Image classification with ResNet and EfficientNet
- Object detection with YOLO
- Data augmentation strategies
Module 3Recurrent Networks & Transformers
- LSTM and GRU for sequence modelling
- Attention mechanism explained
- BERT and GPT architecture overview
- Fine-tuning pretrained Transformers with HuggingFace
Module 4Training at Scale
- GPU acceleration with CUDA
- Mixed precision training
- Learning rate schedulers
- Distributed training concepts
Module 5Deployment & MLOps
- TensorFlow Serving and TorchServe
- Model quantisation and pruning
- ONNX for framework interoperability
- Experiment tracking with MLflow
Prerequisites
- Solid Python programming skills
- Completion of Machine Learning with Python or equivalent
- Linear algebra and calculus fundamentals
Who Should Attend
- ML engineers deepening neural network expertise
- Research scientists applying deep learning
- Software engineers building AI-powered products
Get Started
Interested in Deep Learning & Neural Networks?
Our training advisors will help you choose the right batch format, dates, and pricing for your team or individual goals.