This training program is open to anyone interested in expanding their professional skills. The practical examples and exercises are chosen so they map well to the daily work of Executive Assistants; participation is expressly open to everyone, regardless of current professional role. The course teaches methods, tools, and content that can be applied in many different work contexts.
The following typical tasks from the daily work of Executive Assistants serve as worked examples in the exercises; they can be adapted to other fields of activity during the course:
- Briefing dossiers
- Research syntheses
- Top-management reports
- Travel choreography
- Board templates
Content
- Fundamentals of communication in project management
- Advanced communication skills
- Conflict management as a key competency for project leaders
- Final project and certification
Learning Objectives
- Apply effective communication strategies in project settings.
- Identify and manage conflicts within project teams.
- Develop and implement conflict resolution plans.
- Successfully complete a final project demonstrating acquired skills.
Course 2: AI-Powered Data Analysis
Content
- Introduction to AI analysis cockpit with Co-Pilot
- Data preparation and visualization
- AI code acceleration using GitHub Copilot
- The AI analysis pipeline: From raw data to business strategy
- Fundamentals of machine learning
- Supervised learning: Concepts and applications
- Building a personal AI engine with KNIME and a final project
- Unsupervised learning and clustering
- Data cleaning techniques
- Deep learning in data analysis
- Feature engineering and dimensionality reduction
- Model evaluation and performance metrics
- Interpretability and explainability of AI models
- Ethics and data privacy in AI-powered data analysis
- Utilizing AI-powered analysis tools and software solutions
- Practical project: Implementing an AI-powered data analysis
Learning Objectives
- Utilize AI tools for data analysis and pattern recognition.
- Prepare and visualize data effectively.
- Automate coding tasks with AI assistance.
- Understand and apply machine learning concepts (supervised and unsupervised).
- Implement deep learning techniques for data analysis.
- Evaluate and interpret AI model performance.
- Address ethical considerations and data privacy in AI applications.
- Complete a practical project involving AI-powered data analysis.
Career Prospects
The combined skill set from this program is applicable in various professional fields, including IT project management, software development, data science, business analysis, and consulting. Graduates will be prepared for roles involving the development, implementation, and management of AI-driven projects and data analysis initiatives. The program provides a foundation for positions requiring strong communication, conflict resolution, and advanced analytical capabilities.