Build advanced AI models by mastering neural networks and deep learning techniques used in real-world applications.
The Deep Learning course focuses on building intelligent systems using neural networks and advanced learning algorithms.
You will understand how machines learn complex patterns from large datasets and how deep learning powers technologies like image recognition, speech processing, and natural language understanding.
This course is hands-on and project-driven, designed for learners who want to move into advanced AI and deep learning roles.
A structured deep learning roadmap covering neural networks, computer vision, NLP, and advanced AI projects.
What is Deep Learning, ML vs Deep Learning, deep learning applications.
Perceptron & neural networks, activation functions, forward & backward propagation.
NumPy for neural networks, TensorFlow & Keras basics, building neural models.
Loss functions, optimizers (SGD, Adam), regularization & tuning.
Image processing basics, CNN architecture, image classification projects.
Sequence modeling, RNN, LSTM & GRU, time-series & text data.
Text preprocessing, word embeddings, NLP use cases.
Transfer learning, pre-trained models, introduction to transformers.
Model evaluation metrics, optimization techniques, image & text-based deep learning projects, end-to-end AI case study.
To build a career in artificial intelligence by developing advanced deep learning models that solve complex, real-world problems.
Move beyond basics and build intelligent AI systems with expert mentoring and real-world projects.
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