What you will learn in Neural Networks and Deep Learning Course
- Understand the foundational concepts of neural networks and deep learning.
- Build, train, and apply fully connected deep neural networks.
- Implement efficient (vectorized) neural networks.
- Identify key parameters in a neural network’s architecture.
- Apply deep learning techniques to real-world applications.
Program Overview
Introduction to Deep Learning
⏱️2 hours
- Analyze the major trends driving the rise of deep learning.
- Understand where and how deep learning is applied today.
Neural Networks Basics
⏱️5 hours
- Learn the structure and functioning of neural networks.
- Implement forward and backward propagation.
Shallow Neural Networks
⏱️ 6 hours
- Build a shallow neural network and understand its components.
- Apply vectorization to optimize computations.
Deep Neural Networks
⏱️ 6 hours
- Construct deep neural networks with multiple layers.
- Understand the role of activation functions and parameters.
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Job Outlook
- Proficiency in neural networks and deep learning is essential for roles such as Machine Learning Engineer, Data Scientist, and AI Researcher.
- Skills acquired in this course are applicable across various industries, including technology, healthcare, finance, and more.
- Completing this course can enhance your qualifications for positions that require expertise in deep learning and neural network architectures.
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Introduction to Deep Learning & Neural Networks with Keras Course – Build foundational skills in deep learning using Keras to create and train neural networks efficiently.
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Introduction to Neural Networks and PyTorch Course – Explore neural network fundamentals and practical implementations using the PyTorch framework.
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