Course curriculum
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1
Understanding the working of Neural Networks
- How are Neural Networks trained - Forward Propagation
- Understanding Loss Functions + Hands on
- Reading: Creating a Custom Loss Function (Optional)
- Optimization Techniques - Gradient Descent
- What is Back Propagation?
- Types of Gradient Descent
- Common Optimization Techniques - Part 1
- Common Optimization Techniques - Part 2
- Building a Deep Neural Network (Hands-on Regression Model)
- Building a Deep Neural Network (Hands-on Classification Model)
- Quiz
The Working of Neural Networks
This free course will help you understand the end-to-end working of neural networks in a simple manner. By the end of this course, you will be able to build advanced Deep Learning models using the PyTorch framework. With a carefully curated list of resources and exercises, this course serves as your comprehensive guide to mastering deep learning. It is recommended that you complete the advanced Machine Learning course before taking up this course.
Who Should Enroll:
- Professionals: Individuals looking to expand their skill set and apply deep learning across different industries.
- Aspiring Students: For those setting out on their journey to mastering deep learning and making a mark in the tech world.
Key Takeaways from the course
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Utilize leading AI tools like ChatGPT, Microsoft Copilot, and DALL·E3 to create text and image content, enhancing your ability to innovate and streamline your creative processes.
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Hands-On Experience: Engage with exercises designed to reinforce your learning and apply concepts in real-world scenarios.