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Deep Learning MiniCamp [Arabic]
Highest Rated
Rating: 4.6 out of 5(184 ratings)
4,098 students

Deep Learning MiniCamp [Arabic]

Level up Your ML Skills with Deep Learning, Computer Vision and Natural Language Processing
Created byAhmad Mostafa
Last updated 3/2026
Arabic

What you'll learn

  • Neural Networks
  • Backpropagation Algorithm
  • Tensorflow / Keras
  • Hyperparameters Tuning
  • Computer Vision Foundation
  • Convolutional Neural Networks
  • Image Classification
  • Natural Language Processing Foundation
  • Recurrent Neural Networks
  • Text Classification

Course content

13 sections37 lectures5h 18m total length
  • Intro to Deep Learning11:03
  • Backpropagation Algorithm7:49
  • How the gradients calculated11:15

Requirements

  • Basic Python Programming
  • Basic Machine Learning Knowledge

Description

This course is designed to equip you with the essential knowledge and hands-on practice needed to elevate your machine learning skills, especially if you already have a foundational understanding of machine learning concepts. Whether you're aiming to deepen your expertise in deep learning or looking to explore more advanced neural networks, this course provides a comprehensive journey into the world of artificial intelligence.

Throughout the course, you will dive deep into Neural Networks, exploring the foundational concepts, their structure, and how they can be built from the ground up. We will guide you through the process of constructing a neural network from scratch, helping you understand the underlying mechanics. Additionally, you'll learn how to train neural networks using Keras, a powerful and user-friendly deep learning library in Python, which simplifies the process of building, training, and testing models.

Moreover, you'll gain practical insights and expert tips on deep learning training techniques, covering topics like avoiding overfitting, optimizing your training process, and choosing the right network architecture for various tasks. These tips are drawn from real-world experience, ensuring that you can apply them effectively in your own deep learning projects.

To solidify your learning, you will engage in a hands-on project, where you'll experiment with hyperparameter tuning—an essential skill for optimizing deep learning models. This project will challenge you to apply the concepts you’ve learned, test different configurations, and fine-tune your model for the best performance.

Computer Vision is now added with Image Classification Project.

All course materials, including PDFs for theoretical concepts and interactive coding notebooks, are provided to help you follow along and reinforce your learning. The coding notebooks allow you to not only experiment with the code but also modify and extend it as you gain confidence.

You are encouraged to take personal notes, write your own code, and experiment freely with the tools provided. By the end of this course, you will have the confidence and practical experience to tackle more complex deep learning problems and the knowledge to continue your learning journey in the field of artificial intelligence.

This course offers a balanced combination of theory, practical implementation, and expert guidance, making it a valuable stepping stone for those looking to level up in machine learning and deep learning.

Enjoy your learning experience!

Who this course is for:

  • Machine Learning Students or Professionals who aims to extend their skills to the power of Deep Learning