Mujo’s Prompt Engineering curriculum is a comprehensive courseware solution designed specifically for higher education instructors teaching prompt engineering, large language model interaction, and generative AI communication skills. This complete prompt engineering textbook and curriculum package equips students with practical, job-ready competencies in crafting effective prompts, optimizing AI outputs, and leveraging LLMs across business, technical, and creative applications.
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Why Mujo's Prompt Engineering Curriculum Stands Out
Designed as Complete Prompt Engineering Courseware
Unlike standalone prompt engineering courses or fragmented resources, this curriculum provides everything instructors need for a complete semester course in prompt engineering. From foundational prompt design principles to advanced techniques like chain-of-thought reasoning, few-shot learning, and prompt optimization strategies, this courseware covers the full spectrum of prompt engineering education.
Prompt Engineering Syllabus
Aligned with learning outcomes and educational best practices, the syllabus provides a proven framework for teaching prompt engineering concepts progressively, ensuring students build competency from basic prompting techniques to sophisticated prompt engineering strategies.
Hands-On Prompt Engineering Training
Students gain practical experience through structured prompt engineering projects and assignments that develop real-world skills in:
- Writing effective prompts for ChatGPT, Claude, Gemini, and other large language models
- Prompt engineering patterns including role-based prompting, chain-of-thought, and few-shot examples
- Prompt optimization and iterative refinement techniques
- Context management and conversation design for LLM applications
- Evaluating and improving AI-generated outputs through prompt engineering
- Domain-specific prompt engineering for business, technical writing, data analysis, and creative applications
- Ethical considerations in prompt engineering and AI interaction
- Prompt engineering for multimodal AI systems (text, image, code generation)
Prompt Engineering Curriculum Table of Contents
1
Ch 1: Introduction to Large Language Models
• Large language model fundamentals
• Strengths and limitations of LLM technology
• History of LLMs
• Strengths and limitations of LLM technology
• History of LLMs
2
Ch 2: Natural Language Processing
• Key concepts
• Analyzing human and computer parsing
• Use cases and limitations
• Analyzing human and computer parsing
• Use cases and limitations
3
Ch 3: Model Training and Fine-Tuning
• LLM training processes
• Preparing additional data for fine-tuning
• Training data management
• Preparing additional data for fine-tuning
• Training data management
4
Ch 4: Prompt Engineering
• Strategies to improve outputs
• One-shot prompting
• Prompt patterning
• One-shot prompting
• Prompt patterning
5
Ch 5: Frameworks, Libraries, and Applications
• Expanding LLM capacities
• Additional databases and libraries
• Function-calling
• Additional databases and libraries
• Function-calling
6
Ch 6: Evaluating Outputs
• Key Metrics for performance evaluation
• LLM benchmarking
• Aligning LLMs with organizational needs
• LLM benchmarking
• Aligning LLMs with organizational needs
7
Ch 7: LLM Platforms and Providers
• Key LLM platforms
• Strengths and weaknesses of LLM platforms
• Selecting a provider for your needs
• Strengths and weaknesses of LLM platforms
• Selecting a provider for your needs
8
Ch 8: Workflows, Governance, and Strategic Implementation
• Implementation strategies
• Workflow development
• Ethical uses and legal considerations
• Workflow development
• Ethical uses and legal considerations
Prompt Engineering Teacher Manual
The Prompt Engineering textbook is accompanied by a comprehensive prompt engineering teacher manual, providing instructors with valuable resources to enhance the learning experience. These teacher manuals go well beyond the textbook content and include:
- Prompt Engineering lesson plans
- Handy post-it notes
- Prompt Engineering assignments
- Prompt Engineering case studies
- Prompt Engineering projects
- Prompt Engineering exams
Prompt Engineering & LLM's Teacher Resource Cloud and Courseware
In addition to the teacher manual, the Prompt Engineering textbook also provides instructors with access to a teacher resource cloud and courseware, offering a wealth of valuable content to further support their teaching efforts. This dedicated platform includes:
- Instructional prompt engineering video tutorials
- Ready-to-use prompt engineering PowerPoint presentations
- Supplemental content to extend hours such as SCORM packages
- Learning management systems (LMS) integration
- Prompt Engineering test bank exams
Prompt Engineering Curriculum Learning Outcomes
Upon completing this prompt engineering curriculum, students will be able to:
- Design and implement effective prompts for various large language models and AI systems
- Apply prompt engineering patterns and techniques to solve real-world problems
- Optimize prompts iteratively to improve AI output quality, accuracy, and relevance
- Evaluate and refine AI-generated content through strategic prompt engineering
- Understand the technical foundations of how LLMs process and respond to prompts
- Implement domain-specific prompt engineering solutions for business applications
- Apply ethical frameworks to prompt engineering practices
- Design complex prompt chains and workflows for multi-step AI tasks
- Measure and assess prompt effectiveness using quantitative and qualitative metrics
- Adapt prompt engineering strategies across different AI platforms and tools
Adopt Mujo's Prompt Engineering Curriculum
Ready to offer cutting-edge prompt engineering education at your institution?
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Prompt Engineering Curriculum FAQ’s
What prerequisite knowledge do students need for this prompt engineering course?
No technical prerequisites required. The curriculum starts with foundational concepts, making it accessible to students from any major. Basic computer literacy and familiarity with using web applications is helpful but not mandatory.
How does this compare to online prompt engineering courses?
Unlike short online prompt engineering courses, this is a comprehensive semester-long curriculum designed for higher education, with academic rigor, extensive instructor support, structured assessments, and alignment with college & university learning outcomes. It provides deeper coverage and hands-on practice than typical MOOC offerings.
Which LLM platforms are covered in the prompt engineering curriculum?
The curriculum covers prompt engineering principles that apply across all major platforms including ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Microsoft Copilot, and others. Students learn platform-agnostic skills while gaining hands-on experience with multiple tools.
Is the prompt engineering curriculum regularly updated?
Yes. Given the rapid evolution of generative AI and prompt engineering techniques, Mujo provides regular curriculum updates to adopting institutions, ensuring content reflects the latest developments, research, and best practices in prompt engineering.
Can this prompt engineering courseware be integrated into existing courses?
Absolutely. While designed as a standalone prompt engineering course, individual modules can be integrated into existing business, computer science, communications, or professional writing courses to add prompt engineering training components.
What LMS platforms is this prompt engineering curriculum compatible with?
The digital resources are SCORM-compliant and compatible with all major Learning Management Systems including Canvas, Blackboard, Moodle, D2L Brightspace, and others.
