The training diploma in Artificial Intelligence (AI) is designed to provide participants with comprehensive knowledge and skills to develop and implement AI solutions across various industries.
After completing the training diploma, participants will be able to:
• Understand the concept and importance of artificial intelligence.
• Knowing the future of the world under artificial intelligence.
• How to establish and build an artificial intelligence system in the country.
• How to evaluate the effectiveness of artificial intelligence.
• Developing and programming artificial intelligence algorithms
• Use specialized programming tools and libraries in artificial intelligence
• Analyzing data and extracting knowledge from it
• Understand the ethical issues related to artificial intelligence applications
Key Components of an AI Diploma Program
Introduction to Artificial Intelligence
History and evolution of AI
Core concepts and terminology
Overview of AI applications and impact
Programming and Machine Learning
Programming languages used in AI (e.g., Python)
Basic and advanced machine learning algorithms
Tools and libraries such as TensorFlow, PyTorch, and scikit-learn
Deep Learning
Fundamentals of neural networks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM)
Natural Language Processing (NLP)
Text analysis and understanding
Natural language generation
Applications like chatbots, sentiment analysis, and language translation
Computer Vision
Image and video processing
Pattern and object recognition
Practical applications in healthcare, automotive, and security
6. Problems of artificial intelligence
o Reasoning, logical thinking, and the ability to solve problems
o Representing knowledge
o Planning
o Learning
o How natural language works
o Movement and the possibility of change
o Perception
o social intelligence
7. Creativity
o General intelligence
8. Introductions to artificial intelligence
o Cybernetics and brain simulation
o Traditional symbolic artificial intelligence
o Semi-symbolic artificial intelligence
o Statistical artificial intelligence
o Integrating curricula
9. Artificial intelligence research tools
o Research and improvement
o Logic
o Probabilistic methods of uncertain reasoning
o Classifiers and statistical learning methods
o Neural networks
o Control theory
o Specialized languages
Career Opportunities
Data Scientist
Machine Learning Developer
AI Consultant
Roles in research and development in IT companies and major corporations
By completing a diploma in AI, you will be well-equipped to develop cutting-edge AI solutions, making you a valuable asset in the rapidly evolving tech industry.
