Module 1: AI Basics
1.1. Classification of AI concepts
1.2. Practical applications of Generative AI
1.3. Key considerations when using AI
1.4. Introduction to common AI tools
Module 2: Basic Prompt Writing Techniques
2.1. Understanding prompts and their importance
2.2. RTIO Framework
2.3. Language optimization in prompt writing
2.4. Practice writing basic prompts
Module 3: Advanced Prompt Techniques
3.1. Role-based prompt writing
3.2. Using markdown formatting in prompts
3.3. Practicing advanced prompts
Module 4: Deep Research – Information Search Skills
4.1. Deep Research features
4.2. How to use Deep Research effectively
4.3. Deep Research practice
Module 5: Data Analysis with AI
5.1. Types of data that can be analyzed
5.2. Chain-of-thought technique for unstructured data
5.3. Structured data analysis
5.4. Live demo: data analysis
5.5. Practice with big data analysis
Module 6: Report and Presentation Slide Creation
6.1. Structuring reports logically
6.2. Visualizing data with AI
6.3. Using Gamma to design professional slides
6.4. Practice: Creating a complete report
Module 7: Project Planning and Management
7.1. Setting objectives using the SMART model
7.2. Allocating resources with the RACI framework
7.3. Prioritizing tasks effectively
7.4. Applying the Self-Consistency technique in planning
7.5. Using project management tools
7.6. Practice: Project planning simulation
Module 8: AI Assistants and Automation
8.1. Differentiating types of personal AI
8.2. Machine learning techniques for personal AI
8.3. Few-shot learning techniques in prompt engineering
8.4. Designing a personal AI assistant
8.5. Demo: Building a complete AI assistant
Module 9: Hands-on: Building a Personal AI System
9.1. Identifying individual needs
9.2. Creating a personal AI assistant
9.3. Testing and optimization
9.4. Sharing and feedback