AI Engineering Bootcamp: From Beginner to Expert [Arabic]

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AI Engineering Mastery: From Zero to Hero

Master AI from Fundamentals to Advanced Deep Learning, NLP, Computer Vision, and Generative AI with Real-World Projects

Course Description:
Artificial Intelligence is transforming industries and opening new career opportunities. This comprehensive course is based on recorded live sessions and is designed to take you from beginner to advanced AI engineer by covering both foundational concepts and cutting-edge technologies.

These sessions were originally conducted live, ensuring an interactive teaching style, real-world discussions, and in-depth explanations. Now, they are fully available as on-demand recordings, allowing you to learn at your own pace, revisit lessons anytime, and follow a structured step-by-step approach.

Whether you are new to programming or already familiar with AI basics, this course provides hands-on experience with industry-standard tools like Python, TensorFlow, and Hugging Face. You will work on real-world projects to solidify your skills and prepare for real-life AI challenges.

What You Will Learn:

1. Foundations of AI & Machine Learning

• Core concepts in statistics and linear algebra for AI

• Python essentials: Data structures, control flow, and object-oriented programming

• Key libraries: NumPy, Pandas, Matplotlib, and Seaborn

• Hands-on projects: Titanic Survival Prediction and California Housing Project

2. Core Machine Learning Techniques

• Linear and polynomial regression

• Data preparation, feature selection, and overfitting control

• Decision trees, K-nearest neighbors (KNN), Naïve Bayes, and support vector machines (SVM)

• Ensemble methods: Bagging, boosting, and advanced evaluation techniques

• Clustering methods for unsupervised learning

3. Deep Learning & Neural Networks

• Neural network architecture and implementation

• Overfitting control, regularization, and optimization techniques

• TensorFlow for deep learning and model fine-tuning

• Applied deep learning: Titanic Survival Prediction

4. Natural Language Processing (NLP)

• Core concepts and text encoding techniques

• Sequential data modeling with RNNs, GRU, and LSTMs

• Transformer models and attention mechanisms

• Advanced NLP frameworks: Hugging Face, BERT, and T5

• Retrieval-Augmented Generation (RAG) and LangChain integration

5. Computer Vision & Image Processing

• Convolutional neural networks (CNNs)

• Transfer learning and image classification techniques

• Object detection models: RCNN, Fast-RCNN, and YOLO

• Generative Adversarial Networks (GANs) and their applications

6. Generative AI & Practical Implementations

• Generative AI concepts and model deployment

• Prompt engineering techniques for language models

• Building AI-driven applications using Streamlit and other frameworks

Why Take This Course?

• Comprehensive Learning Path: From AI fundamentals to advanced applications.

• Practical Projects: Gain hands-on experience with real-world datasets.

• Industry-Ready Skills: Learn the tools and techniques used in leading AI applications.

• Structured and Accessible: Suitable for both beginners and experienced professionals.

• Portfolio Development: Build AI projects that showcase your expertise.

Who This Course Is For:

• Beginners seeking a clear and practical introduction to AI.

• Software developers and engineers looking to integrate AI into their applications.

• Data scientists and analysts want to expand their deep learning and NLP expertise.

• Entrepreneurs and tech enthusiasts aiming to understand and apply cutting-edge AI.

By the end of this course, you will have a solid understanding of AI engineering principles and the ability to develop advanced models for a variety of real-world use cases.

Enroll today and begin your journey toward becoming an AI engineer.