Prompt Engineering: Advanced Module

Prompt Engineering: Advanced Module

Duration: Max 20 hours
Mode: Online/Hybrid

Course Description:
The Advanced Prompt Engineering module is designed for experienced prompt engineers and AI professionals who want to achieve expert-level skills in prompt crafting. In this 20-25 hour course, learners will tackle complex prompt structures, including multi-step prompts, dynamic chaining, and adaptive response tuning. This module provides advanced strategies for managing high-level AI interactions and creating prompts that can generate highly specialized outputs for niche tasks.

Participants will engage in in-depth projects, developing prompts for use cases such as interactive storytelling, dynamic chatbots, and AI-assisted decision-making tools. The course also explores optimization techniques, allowing learners to maximize output efficiency and quality. By the end of the module, participants will be equipped with the skills to design and implement sophisticated AI-driven solutions.

Modules Overview:

Module 1: Multi-Step Prompt Engineering

• Planning Multi-Step Prompts: Structuring a sequence of tasks
• Integration with APIs: Combining prompt engineering with API calls
• Chaining Outputs: Using outputs as inputs in complex workflows

Module 2: Dynamic Chaining and Prompt Sequencing

• Dynamic Prompt Chaining: Linking prompts based on previous outputs
• Adaptive Sequencing: Modifying the sequence based on response flow
• Practical Applications: Building interactive and adaptive systems

Module 3: Advanced Response Tuning Techniques

• Fine-Grained Control of Tone and Style: Adjusting language and nuance
• Sentiment Manipulation: Crafting prompts to convey specific emotions
• Optimizing Responses for Different Audiences: Adapting for audience types
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Module 4: Adaptive Prompts for Niche Applications

• Domain-Specific Prompts: Crafting prompts for specialized fields
• Real-Time Adaptation: Creating prompts that respond to changing data
• Interactive Storytelling: Developing dynamic narratives

Module 5: Optimization for Output Efficiency and Quality

• Evaluating Prompt Efficiency: Reducing token usage
• Optimizing for Speed: Structuring prompts for faster response times
• Quality Control: Techniques to ensure accuracy and relevance

Module 6: Real-World Scenarios and Advanced Use Cases

• Dynamic Chatbots: Building prompts for complex chatbot interactions
• Decision-Making Tools: Designing prompts for AI-assisted decision-making
• Personalized Recommendations: Advanced techniques for customization

Module 7: Capstone Project: Building a Dynamic AI-Driven Solution

• Project Selection and Planning: Choosing a real-world application
• Solution Development: Creating, testing, and optimizing prompts
• Final Presentation: Demonstrating the project and receiving feedback