Introduction to AI-Driven Decision Making Training by Tonex
This course introduces the concepts and techniques of AI-driven decision making. Participants will learn how AI can enhance decision-making processes, the tools and algorithms used, and the ethical considerations involved in AI-driven decisions.
Learning Objectives
- Understand the principles of AI-driven decision making.
- Identify AI tools and algorithms for decision making.
- Develop AI models for decision support.
- Analyze data for AI-driven insights.
- Address ethical considerations in AI decisions.
- Implement AI-driven decision-making systems.
Audience
- Data Scientists
- Business Analysts
- Decision Makers
- AI Developers
- Project Managers
- Policy Makers
Program Modules
- Introduction to AI-Driven Decision Making
- Definition and importance of AI-driven decision making
- Historical context
- Benefits of AI in decision making
- Challenges and limitations
- Key components of AI-driven decision systems
- Case studies
- AI Tools and Algorithms
- Overview of AI tools
- Machine learning algorithms
- Decision support systems
- Data analytics tools
- Natural language processing
- Practical exercises
- Developing AI Models
- Steps in building AI models
- Data collection and preparation
- Training and testing models
- Model validation and optimization
- Deployment of AI models
- Practical exercises
- Data Analysis for Decision Making
- Importance of data quality
- Techniques for data analysis
- Extracting insights from data
- Visualizing data for decision support
- Data-driven decision frameworks
- Case studies
- Ethical Considerations
- Bias and fairness in AI decisions
- Transparency and explainability
- Accountability in AI-driven decisions
- Ethical guidelines for AI use
- Managing ethical risks
- Practical exercises
- Implementing AI-Driven Decision Systems
- Planning and designing decision systems
- Integration with existing processes
- Monitoring and evaluation
- Continuous improvement
- Change management
- Practical exercises