Course Curriculum
10 interactive lessons with real-time autograding
1
Module 1
Introduction to Keras
Deep learning fundamentals, Keras vs TensorFlow, and your first model.
2
Module 2
Tensors and Data
Tensor shapes, data pipelines with tf.data, and feature preprocessing.
3
Module 3
Sequential API
Building feedforward networks with Dense, Dropout, and Activation layers.
4
Module 4
Compiling Models
Loss functions, optimizers (Adam, SGD), and evaluation metrics.
5
Module 5
Training & Evaluating
fit(), batch sizes, epochs, validation splits, and history analysis.
6
Module 6
Functional API
Multi-input, multi-output, and residual connection architectures.
7
Module 7
Regularisation
L1/L2 penalties, EarlyStopping, and learning rate schedulers.
8
Module 8
Image Classification
Convolutional layers (Conv2D), MaxPooling, and computer vision.
9
Module 9
Text & Sequences
Embedding layers, LSTM, GRU, and sequential NLP models.
10
Module 10
Pretrained Models
Transfer learning with ResNet, MobileNet, and fine-tuning weights.