AI Fundamentals for IT Professionals
Do you think visionary, are ready for innovation and would you like to know how the use of AI in your company or for your tasks is best? If you want to assess everything related to the application of AI and deal with the best practices, then look forward to this training. Together we look at current application areas of artificial intelligence, large language models and modern prompt engineering. You will not only learn the basics, but also how to use AI tools effectively in a corporate context and prepare yourself optimally for AI integration in your company.
Certificate of attendance from Spirit in Projects Foundation
Goals
- Understand differences between artificial and natural intelligence
- Get to know and evaluate innovative areas of application of AI
- Overview of various AI techniques and methods, especially Large Language Models
- Know the practical uses of AI in the company and assess the impact on business processes
- Understand relevant methods to effectively implement AI
- Promptly master engineering techniques and apply them in practice
- Gain hands-on experience with current LLMs and AI tools
Target Groups
Content
1. Basics
- AI vs. natural intelligence
- Benefits of using AI
- Weak and Strong AI
- Difference between AI, Machine Learning and Data Science
- Problems and limitations
- When does using AI pay off?
- ROI consideration and profitability analysis
2. Basic application areas of AI
- Natural Language Processing & Speech Recognition
- Image recognition & facial recognition
- Intelligent systems or autonomous systems & robots
- Expert systems
- Generative AI and its fields of application
3. Basic implementation methods of AI
- Machine learning
- Deep learning
- statistics
- Logic & Planning
- Large Language Models (LLMs)
- Transformer architecture
- Multimodal models
4. Large Language Models in Practice
- Overview of current LLMs (ChatGPT, Claude, Gemini, etc.)
- Open source LLMs (Llama, DeepSeek, etc.)
- Multimodal capabilities: text, vision, audio
- Application scenarios in a corporate context
- Retrieval Augmented Generation (RAG)
- Hallucinations and their avoidance
- Security and data protection when using LLM
5. Prompt Engineering – Basics and Best Practices
- What is prompt engineering and why is it important?
- Zero-shot prompting for simple tasks
- Few-shot prompting for domain-specific applications
- Chain-of-Thought (CoT) prompting for complex problems
- Structured prompts and templates
- System prompts vs. user prompts
- Cost optimization through efficient prompts
- Practical exercise: Prompt optimization for various use cases
6. Areas of application
- Customer support and chatbots
- Content creation and marketing
- Software development with AI copilots
- Predictive analytics and forecasting
- Transportation & Autonomous Vehicles
- Medicine and Healthcare
- Finance and fraud detection
- Supply Chain Optimization
7. AI and society
- Ethical aspects of AI
- Regulatory framework conditions
- AI governance
- Responsible AI
8. AI tools and platforms 2026
- OpenAI (ChatGPT)
- Anthropic Claude family
- Google Gemini Pro/Flash
- Microsoft Copilot with multi-model integration
- Google TensorFlow
- PyTorch
- Microsoft Azure AI Services
- Amazon AWS AI Services
- Cloud platforms and their advantages and disadvantages
- Programming languages for AI development
9. Hands-on workshop
- Practical work with various LLMs (open source and closed source)
- Prompt engineering for real business scenarios
- Evaluation of different LLM models (Small Language Models vs Large Language Models)
- Use case development for your company
- Best practices and lessons learned
Certification
For this training you will receive a certificate of participation from Spirit in Projects.
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