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Week - 1 |
Introduction to Deep Learning |
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Week - 2 |
Mathematical Foundations: Linear Algebra and Derivatives |
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Week - 3 |
EN: Python, NumPy, and Deep Learning Development Environment |
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Week - 4 |
Fundamentals of Artificial Neural Networks |
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Week - 5 |
Activation Functions and Forward Propagation |
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Week - 6 |
Backpropagation and Loss Functions |
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Week - 7 |
Optimization Algorithms and Hyperparameter Tuning |
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Week - 8 |
Overfitting, Underfitting, and Regularization Techniques |
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Week - 9 |
Data Preprocessing and Model Evaluation |
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Week - 10 |
Fundamentals of Convolutional Neural Networks (CNNs) |
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Week - 11 |
CNN Architectures and Image Processing Applications |
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Week - 12 |
Fundamentals of Recurrent Neural Networks (RNNs) |
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Week - 13 |
LSTM and GRU Networks for Text and Time-Series Analysis |
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Week - 14 |
Transformer Models, Large Language Models, and Current Trends in Deep Learning |