Star Prompt Engineering

EXAM CODES S03-101

Star Prompt Engineering

Prompt engineering optimizes language model responses by strategically designing clear and effective prompts. It involves carefully crafting the wording, structure, and context of prompts to effectively communicate desired tasks or queries to the model. It unlocks the model's full potential by providing explicit instructions for precise outputs. Prompt engineering, a widely recognized and discussed practice, has garnered significant interest among researchers, developers, and industry experts. Its versatile application spans research, data science, AI products, Conversational AI Designs, quality assurance, and AI policy analysis, contributing to the advancement of the AI revolution.

 The Star Prompt Engineering certification program aims to help the learner acquire an understanding of the basics of prompt engineering, language models, Chain of thought prompting, Zero-Shot and Few-Shot Prompting crafting effective prompts, guiding model behaviour, evaluating model outputs, practical applications, ethical implications of prompt engineering, and the future of language models.

Audience

Beginners in either IT or non-IT domains who possess limited or no prior knowledge of AI may benefit from this. Familiarity with AI Essentials, basic programming & communication skills is preferred.

Course Objectives:

In this course, you will learn about:

Understanding language models

Exploring prompt engineering

Crafting Effective prompts

Evaluating model outputs

Experimenting with prompts

Concepts of reinforcement learning

Discussing the ethical implications of prompt

Exploring practical applications

Course Outcomes:

After completing this course, you will be able to recognize and/or demonstrate:

Understand how ML and DL work

Explain prompt engineering and its future

Explore language models with prompts

Describe the four pillars of prompt perfection

Craft effective prompts and Demonstrate image prompting techniques

Explain different OpenAI Applications and Evaluate model outputs

Experiment with Prompts and enhance Prompt Reliability

Explain real-world applications

Table of Contents Course Outline

1. Introduction to Large Language Models

2. AI, ML, DL, and NLP Basics

3. Introduction to prompt engineering

4. Understanding prompts

5. The four pillars of prompt perfection

6. Crafting effective prompts

7. Techniques of Text Prompting

8. Applications of Effective Prompting

9. Experimenting with prompts

10. Zero-Shot & Few-Shot Prompting

11. Different OpenAI Applications

12. Techniques of Image Prompting

13. Enhancing Prompt Reliability

14. Guiding model behaviour

15. System messages and tone

16. Evaluating model outputs

17. Chain of thought prompting

18. Advanced Prompt Engineering

19. LLM Embedding and Fine-tuning

20. Introduction to reinforcement learning

21. Responsible AI and ethical considerations

22. Practical applications and case studies

23. Future of language models and prompt engineering

Exam Details


Exam Codes Star Prompt Engineering S03-101 (Academy customers use the same codes)
Launch Date Jan 15 2024
Exam Description The Star Prompt Engineering certification program aims to help the learner acquire an understanding of the basics of prompt engineering, language models, Chain of thought prompting, Zero-Shot and Few-Shot Prompting crafting effective prompts, guiding model behaviour, evaluating model outputs, practical applications, ethical implications of prompt engineering, and the future of language models.
Number of Questions 60
Type of Questions Multiple choice questions
Length of Test 90 Minutes
Passing Score 70
Recommended Experience Beginners level
Languages English

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