Courses

The Artificial Intelligence Specialist program builds deep technical expertise in AI models, neural networks,
and learning architectures. Students will explore how artificial intelligence systems learn, reason, and adapt
to deliver real business and operational value through autonomous data processing and decision-making.

This program develops practical understanding of AI learning approaches—including supervised,
unsupervised, and reinforcement learning—and focuses on neural network architectures, neuron cell types,
and activation functions. Graduates will be able to design and train models capable of advanced pattern recognition,
natural language processing, and predictive analytics.

What You’ll Learn

• Fundamentals of Artificial Intelligence and Machine Learning
• Supervised, unsupervised, and reinforcement learning techniques
• Neural network architectures: feedforward, convolutional (CNN), recurrent (RNN), and transformer-based models
• Neuron cell types, activation functions, and layer connectivity
• Model training, testing, tuning, and optimization methods
• Natural Language Processing (NLP) and computer vision foundations
• Ethical AI principles and responsible model deployment

Topics Covered

• AI vs. Machine Learning vs. Deep Learning: key distinctions and use cases
• Training data pipelines and preprocessing for high-quality models
• Activation functions: sigmoid, ReLU, tanh, softmax
• Loss functions and optimization algorithms (SGD, Adam, RMSprop)
• Building and deploying AI models using TensorFlow and PyTorch
• Integrating AI into business systems and cybersecurity applications

Format & Materials

• Instructor-led sessions with guided neural network labs
• Hands-on projects in Python, TensorFlow, or PyTorch
• Capstone project: design, train, and deploy a custom AI model

Prerequisites

• Basic programming experience in Python
• Familiarity with algebra, statistics, or prior Machine Learning coursework recommended

Outcomes & Next Steps

• Develop deep understanding of neural networks and AI system design
• Apply AI models to automate data analysis and predictive decision-making
• Prepare for the Artificial Intelligence Specialist Certification Exam
• Advance toward roles such as AI Engineer, Machine Learning Specialist, or AI Solutions Architect