AI Prompt Engineering Foundation
Master the fundamentals of prompt engineering and learn how to create effective prompts that generate accurate, reliable, and high-quality AI outputs. This self-paced online course provides practical, hands-on training in working with today’s leading large language models (LLMs), enabling you to use AI confidently across content creation, research, customer support, business analysis, automation, and more.
Through engaging video lessons, guided demonstrations, and interactive labs, you’ll gain practical experience using leading AI platforms such as ChatGPT (OpenAI), Claude (Anthropic), and Google AI (Gemini). The course also introduces key enterprise concepts, including APIs, function calling, Retrieval-Augmented Generation (RAG), AI governance, and prompt optimization.
Who Should Enroll?
This course is ideal for:
* Marketing professionals, content creators, copywriters, and social media specialists looking to improve productivity and content quality using AI.
* Customer support and operations teams seeking to automate responses, summarize conversations, and generate structured outputs.
* Product managers, project managers, and business analysts leveraging AI for research, documentation, and decision support.
* Developers, automation specialists, and no-code builders creating AI-powered workflows without requiring advanced machine learning knowledge.
* Educators, trainers, and instructional designers developing learning materials, quizzes, and assessments using generative AI.
* Business professionals interested in applying AI effectively and responsibly within their organizations.
Learning Outcomes
By the end of this course, you will be able to:
* Understand how Large Language Models (LLMs) process prompts, context, tokens, and instructions.
* Design clear, structured, and effective prompts for different business and creative use cases.
* Apply advanced prompting techniques including Zero-Shot, Few-Shot, Chain-of-Thought (CoT), ReAct, Self-Consistency, and Tree-of-Thought (ToT).
* Improve AI output quality using roles, constraints, delimiters, and structured formats such as JSON.
* Identify and reduce hallucinations, bias, and unreliable responses using prompt guardrails and grounding techniques.
* Evaluate and optimize prompts using testing frameworks, rubrics, golden datasets, and A/B testing.
* Use AI effectively across ChatGPT, Claude, and Google AI while understanding API integration and enterprise AI concepts.
* Apply AI responsibly through governance, security, compliance, and ethical prompting practices.
Course Format
Delivery Mode:100% Online, Self-Paced eLearning
Access: Start anytime and learn at your own pace
Recommended Duration: Approximately 25–30 hours (2 weeks)
Learning Experience: Short video lessons, guided demonstrations, interactive labs, and knowledge checks
Resources Included: Prompt templates, downloadable worksheets, checklists, and sample datasets
Support: Self-assessments, discussion prompts, and practice activities (no live instructor sessions)
Course Curriculum
Module 1: Foundations of Prompt Engineering
* Introduction to Generative AI
* Prompt engineering principles
* AI capabilities and limitations
Module 2: Language Model Fundamentals
* Tokens and context windows
* Embeddings
* Roles and system prompts
* How LLMs generate responses
Module 3: Prompt Construction Techniques
* Writing effective prompts
* Context and specificity
* Personas and role prompting
* Output formatting
* JSON schemas
Module 4: Advanced Prompting Patterns
* Zero-Shot Prompting
* Few-Shot Prompting
* Chain-of-Thought (CoT)
* Self-Consistency
* ReAct
* Tree-of-Thought (ToT)
Module 5: Domain-Specific Prompting
* Business productivity
* Marketing and content creation
* Education
* Coding assistance
* Data analysis
* Creative applications
Module 6: Multimodal Prompting
* Text-to-image prompting
* OCR and visual question answering
* Audio and video prompting
* Accessibility considerations
Module 7: AI Tools and Platforms
* ChatGPT (OpenAI)
* Claude (Anthropic)
* Google AI (Gemini)
* API concepts
* Function calling
* Retrieval-Augmented Generation (RAG)
* Workflow automation
Module 8: Prompt Evaluation and Optimization
* Prompt testing strategies
* Evaluation metrics
* Rubrics
* A/B testing
* Reliability and guardrails
Module 9: Enterprise AI Adoption
* AI governance
* Security and compliance
* Responsible AI practices
* Business implementation
* Measuring AI value and ROI
Assessment & Certification
Upon completing the course, learners will take an online certification exam.
Examination Details
* Format: Multiple Choice
* Delivery: Web-Based Online Exam
* Duration: 60 Minutes
* Attempts: Two
* Pass Mark: 60%
* Exam Type: Open Book
Successful candidates will receive the AI Prompt Engineering Foundation digital certificate.
What You’ll Receive
* Comprehensive course materials (200+ presentation slides)
* Practical prompt templates
* Interactive lab exercises
* Ready-to-use prompt library
* Downloadable worksheets and checklists
* Evaluation rubrics
* Sample datasets
* Post-course resource pack
* Practice roadmap for continued learning
Technologies and Topics Covered
* ChatGPT (OpenAI)
* Claude (Anthropic)
* Google AI (Gemini)
* Prompt Engineering Best Practices
* Zero-Shot and Few-Shot Prompting
* Chain-of-Thought (CoT)
* ReAct Framework
* Tree-of-Thought (ToT)
* Function Calling
* API Fundamentals
* Retrieval-Augmented Generation (RAG)
* AI Safety and Guardrails
* AI Governance and Enterprise Adoption
