Program Modules
Term 1: Foundations of Computing and AI
: Provides a comprehensive introduction to AI concepts, history, applications, and future trends.
Modules:
- History and Evolution of AI - AI generations, major milestones, AI winters
- AI Fundamentals - Artificial Intelligence concepts, intelligent agents, rational decision making
- AI Domains - Machine Learning, Deep Learning, NLP, Computer Vision, Robotics
- AI Applications - Healthcare, Finance, Education, Cybersecurity, Smart Cities
- Future of AI - AGI concepts, emerging trends, AI careers
Labs: AI tools exploration, AI use-case analysis, AI project ideation
Modules:
- Python Fundamentals - Variables, Data types, Operators
- Control Structures - Loops, Conditions, Functions
- Object-Oriented Programming - Classes, Objects, Inheritance
- Data Structures - Lists, Dictionaries, Tuples, Sets
- Python Libraries - NumPy, Pandas, Matplotlib
- Data Processing - File handling, Data cleaning, Data transformation
Labs: Python coding exercises, Data manipulation projects, Mini AI applications
Modules:
- Linear Algebra - Vectors, Matrices, Matrix operations, Eigenvalues
- Statistics - Probability, Distributions, Hypothesis testing
- Calculus - Derivatives, Gradients, Optimization
- Optimization Methods - Gradient Descent, Cost Functions
- Data Analysis Mathematics - Correlation, Regression concepts
Labs: Mathematical modeling, Data analysis exercises, Visualization activities
Term 2: Machine Learning
Modules:
- Data Collection - Structured data, Unstructured data
- Data Preparation - Cleaning, Transformation
- Exploratory Data Analysis - Visualization, Pattern discovery
- Feature Engineering - Selection, Extraction
- Data Storytelling - Dashboards, Reporting
Labs: Data analysis projects, Dashboard development
Modules:
- Machine Learning Process - Problem definition, Data preparation, Model training
- Supervised Learning - Linear Regression, Logistic Regression, Decision Trees, Random Forest
- Unsupervised Learning - Clustering, K-Means, Hierarchical Clustering
- Model Evaluation - Accuracy, Precision, Recall, F1 Score
- Model Optimization - Hyperparameter tuning, Cross-validation
Labs: Scikit-learn projects, Predictive modeling
Modules:
- Jupyter Notebooks
- Google Colab
- Git and GitHub
- AI Development Environments
- Model Management
- MLOps Fundamentals
Labs: Version control projects, Collaborative development
Term 3: Advanced AI Technologies
Modules:
- Neural Networks - Perceptrons, Activation Functions
- Deep Neural Networks - Architecture design, Backpropagation
- Convolutional Neural Networks (CNN) - Image processing, Feature extraction
- Recurrent Neural Networks (RNN) - Sequence modeling, Time-series prediction
- Transformers - Attention mechanisms, Modern AI architectures
Labs: TensorFlow, Keras, PyTorch
Modules:
- Digital Images
- Image Processing
- Object Detection
- Image Classification
- Facial Recognition
- Vision Applications
Labs: OpenCV projects, Image recognition systems
Modules:
- Text Processing
- Tokenization
- Language Models
- Sentiment Analysis
- Text Classification
- Chatbots
Labs: NLP pipelines, Language processing applications
Term 4: Generative AI and Industry Applications
Modules:
- Introduction to Generative AI
- Foundation Models
- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents
- Fine-Tuning Models
Labs: Prompt engineering, AI assistant development, RAG implementation
Modules:
- AI Ethics
- Bias and Fairness
- Explainable AI (XAI)
- AI Risk Management
- Privacy and Security
- AI Governance Frameworks
Labs: Ethical AI assessments, Bias detection exercises
Modules:
- AI in Healthcare
- AI in Business
- AI in Finance
- AI in Education
- AI in Cybersecurity
- AI Entrepreneurship
Labs: Industry case studies, AI business solution design
Capstone Graduation Project (100 Hours)
Students must complete an end-to-end AI project.
Project Stages::
- Stage 1: Problem Definition - Business case development
- Stage 2: Data Collection - Dataset preparation
- Stage 3: Model Development - AI model creation
- Stage 4: Testing and Validation - Performance evaluation
- Stage 5: Deployment - Cloud or web deployment
- Stage 6: Presentation and Defense
Example Projects::
- AI Chatbot
- Medical Diagnosis Assistant
- Fraud Detection System
- Recommendation Engine
- Smart Education Platform
- AI Cybersecurity Assistant
- Computer Vision Attendance System
- Arabic NLP Application