Deep Learning - Deep Neural Network for Beginners Using Python

In this 6 hr course, you will dive into the fundamentals of deep learning and learn how to implement Deep Neural Networks (DNNs) using Python. By combining theoretical discussions with practical implementations, this course provides a comprehensive primer for those interested in machine learning and neural network design.

What I will be able to do after this course

• Grasp the core principles of machine learning and neural networks.
• Demystify the gradient descent algorithm as it pertains to training DNNs.
• Implement DNNs step by step using Python and NumPy.
• Understand the data preprocessing steps required for DNN projects.
• Execute a hands-on project, applying learned DNN techniques to the IRIS dataset.

Course Instructor(s)

AI Sciences, the team behind this course, brings a wealth of expertise in machine learning and artificial intelligence. They specialize in creating beginner-friendly tutorials that distill complex concepts into clear, actionable lessons. Their practical approach ensures learners can immediately apply what they've learned.

Who is it for?

Ideal for budding data scientists, this course caters to learners with an interest in machine learning. If you're a professional or student aiming to understand or utilize DNNs in projects, this is an excellent choice. Basic Python knowledge is recommended to fully benefit.