Artificial Intelligence & Machine Learning
- What is artificial intelligence and how did it evolve?
- Technical domains/areas under artificial intelligence (Machine Learning, Text-to-Speech/Speech-to-Text, Natural Language Processing, Image Processing, Computer Vision, Planning and Optimization, Robotics, Expert Systems)
- Basics of probabilistic reasoning, and supervised, unsupervised, reinforcement, and deep learning
- Applications of AI across different sectors (energy, health, e-commerce, hi-tech, defense, banking, insurance, manufacturing, etc.)
- Ethical and legal constraints and biases of artificial intelligence
- Trustworthy AI: AI solutions that address human needs, safety, and privacy
Learning Outcomes
- Distinguish between the core technical domains of AI (ML, NLP, computer vision, robotics, etc.)
- Understand the differences between supervised, unsupervised, reinforcement, and deep learning
- Evaluate concrete AI application areas within one’s own sector
- Recognize the ethical, legal, and bias-related risks of artificial intelligence
- Apply trustworthy AI principles to business decisions
Target Audience
Relevant for the following roles:
- Managers and professionals who want to leverage AI in business decisions
- Product managers, business analysts
- Software developers, testers
- Project managers, product owners, Scrum Masters, Agile coaches
Prerequisites
There is no formal prerequisite.
Course Duration: 1 day
Format: Presentation supported by sector application examples
Certificate: Certificate of attendance (not a formal/accredited certification)
This course covers the business fundamentals of artificial intelligence, including technical domains such as machine learning, natural language processing, computer vision, robotics, and expert systems, the basics of supervised, unsupervised, reinforcement, and deep learning, and application examples across different sectors. It also addresses AI’s ethical and legal constraints, bias risks, and the principles of trustworthy AI.