Demystifying the algorithms behind AI
This course breaks down the core algorithms that drive AI, making them easy to understand for beginners and Intermediate alike. From supervised and unsupervised learning to neural networks, this guide explores how AI systems learn and make decisions. Perfect for those seeking a deeper understanding of AI's mechanics without heavy technical jargon.
Content
- Introduction to AI Algorithms
- Key Types of Learning: Supervised, Unsupervised, Reinforcement
- Deep Dive into Neural Networks
- Popular Algorithms (e.g KNN, Linear Regression, K-Means)
- Practical Examples and Use Cases
- Emerging Trends in AI Algorithms
- Ethical Considerations and Limitations of AI Algorithms
Learning Outcomes
- Understand the foundational algorithms behind AI systems.
- Differentiate between types of machine learning.
- Gain insights into neural networks and their applications.
- Learn how AI algorithms solve real-world problems.
- Explore trends and ethical challenges in algorithm design.
Training Method
Interactive presentation and practical examples as well as use cases
Certification
Certificate of ParticipationPrerequisites
- Basic familiarity with programming concepts (Python recommended).
- Understanding of basic mathematical concepts (algebra, probability).
- No prior AI experience required; beginner-friendly
Beginner to Intermediate: Designed for individuals with minimal AI knowledge but curious to understand the "how" behind AI. Advanced learners can also benefit from practical insights and simplified explanations.
Planning and location
Session
1
16/12/2025
-
Tuesday
09:00 - 16:00
09:00 - 16:00
