NZAI-AI-PENG-001

Prompt Engineering: From Foundation to Core Techniques

Prompt Engineering: From Foundation to Core Techniques is a practical, hands-on course designed to equip learners with the essential skills needed to effectively interact with AI large language models. In this course learners will develop practical skills to craft precise prompts, apply context effectively, and optimize AI outputs using structured, real-world prompting strategies.

Mode of Delivery:
Online
$20 USD

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Prompt Engineering: From Foundation to Core Techniques
Prompt Engineering: From Foundation to Core Techniques
Duration
1-2 Weeks
Mode of Delivery
Self Paced (Online)
Basic/Foundational Level
Suitable for Students, Executives, Professionals, Experts, Teachers.
Learning Resources
Explainer Videos, Lesson Plan, Interactive Activities, Practice Test & Quizes, Glossary

Objective

Prompt Engineering: From Foundation to Core Techniques course aims to build a strong foundation in prompt engineering by helping learners understand how AI models interpret and generate responses. It equips participants with the ability to design clear, structured, and context-rich prompts using key components such as instruction, context, persona, output format, and constraints. Learners will develop practical skills in applying core prompting techniques, including zero-shot, one-shot, and few-shot approaches. By the end of the course, participants will be able to create, refine, and optimize prompts to generate accurate, relevant, and high-quality outputs for real-world and professional applications.

Curriculum

Prompt Engineering: From Foundation to Core Techniques course will cover the given below modules.
Module 1: Foundation of prompt engineering
1.1 What is Prompt Engineering
1.2 How AI Models Think
1.3 Anatomy of a Good Prompt
1.4 First Steps with AI Tools
Module 2: Core Prompting Techniques
2.1 Clear Instructions
2.2 Providing Context
2.3 Output Format & Constraints
2.4 Few-shot / One-shot / Zero-shot prompting

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What Will You Learn

Upon completion of the course the learners will be able to : 
  • Understand the fundamentals of prompt engineering, including its definition, importance, and benefits
  • Explain how AI language models work, including tokenization, next-token prediction, and their limitations
  • Identify and apply the core components of an effective prompt such as instruction, context, persona, output format, and constraints
  • Construct clear, specific, and unambiguous prompts using best practices like conciseness and active verbs
  • Provide relevant and structured context to improve the quality and accuracy of AI-generated responses
  • Define and control output formats such as lists, markdown, JSON, and tables for better usability and integration
  • Apply constraints related to tone, length, style, and content to guide AI behavior effectively
  • Use zero-shot, one-shot, and few-shot prompting techniques based on different use cases
  • Interact with AI tools effectively using an iterative approach to refine and improve outputs
  • Build, test, and optimize prompts for practical, professional, and scalable real-world applications

Program Delivery & Engagement

This program is delivered as a self-paced online course designed to be completed over 1–2 weeks, allowing learners the flexibility to progress according to their own schedule. The course content is organized into structured modules that include concise lessons in the form of Lesson Notes, Explainer Videos, Practice exercises, Quizzes, and Module-end quizzes to reinforce learning. Participants can access the materials anytime, enabling them to revisit concepts, practice prompt creation, and refine their skills at their convenience. Learner support is typically provided through discussion forums, Q&A boards, or asynchronous feedback channels, where participants can ask questions and engage with instructors or peers. This flexible delivery model ensures that learners can balance their learning with other commitments while still gaining hands-on experience.
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