Course description
This course provides a deep dive into the fundamentals of deep learning using TensorFlow and PyTorch. You will learn about neural networks, backpropagation, convolutional and recurrent neural networks, and various deep learning architectures. Hands-on coding exercises and real-world projects will help you build AI models effectively.
What will i learn?
- Understand deep learning fundamentals and architectures
- Implement neural networks using TensorFlow and PyTorch
- Work with convolutional and recurrent neural networks
- Train, optimize, and deploy deep learning models
- Develop AI applications using real-world datasets
Requirements
- Basic Python programming knowledge
- Familiarity with machine learning concepts is recommended
- Enthusiasm to learn deep learning frameworks
Frequently asked question
Data scientists, AI engineers, and anyone interested in deep learning.
Basic Python and AI concepts are recommended.
Neural networks, CNNs, RNNs, and real-world AI model implementation.
