Deep Learning Pro
This advanced course dives deep into neural networks, CNNs, RNNs, transformers, and real-world deep learning use cases. Designed for learners with prior ML knowledge, it focuses on building scalable deep learning models using modern frameworks.
Course Modules
Module 1: Introduction to Deep Learning
- What is Deep Learning?
- Neural Networks Overview
Module 2: Neural Network Fundamentals
- Forward & Backward Propagation
- Activation Functions
Module 3: Building Neural Networks with TensorFlow
- TensorFlow Basics
- Creating Sequential Models
Module 4: Model Optimization
- Hyperparameter Tuning
- Regularization Techniques
Module 5: Convolutional Neural Networks (CNNs)
- Convolution & Pooling
- Image Classification with CNNs
Module 6: Recurrent Neural Networks (RNNs)
- Time Series & Sequence Data
- LSTM and GRU Networks
Module 7: Transformers & Attention
- Attention Mechanism
- Intro to BERT and GPT
Module 8: Transfer Learning
- Pretrained Models
- Fine-Tuning Techniques
Module 9: Generative Models
- Autoencoders
- GANs (Generative Adversarial Networks)
Module 10: Deploying Deep Learning Models
- Model Serialization
- Using Flask & FastAPI
Module 11: Real-World Project
- End-to-End Deep Learning Application
- Team Collaboration
Module 12: Final Assessment & Certification
- Capstone Evaluation
- Certificate of Completion