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Generative AI Prompt Engineering Certification Course

Name: Generative AI Prompt Engineering Certification Course
Rating: 4.2 (19 reviews)

Comprehensive prompt engineering roadmap covering ChatGPT, tools, techniques, and real-world Gen AI use cases.

Role Play

Created byStarweaver Experts, Ritesh Vajariya, Paul Siegel

Last updated 4/2026

English

What you'll learn

Apply GenAI system architecture principles to design scalable applications using structured Prompt Engineering for Generative AI frameworks.
Construct advanced AI prompt engineering patterns tailored to diverse business use cases, including customer support, automation, and analytics.
Implement interactive prompt engineering workflows with real-time LLM prompt optimization and context management strategies.
Develop production-ready customer support chatbot systems using prompt engineering best practices and quality assurance protocols.
Design multi-step prompt chains using generative AI prompt engineering techniques to improve response accuracy and consistency.
Integrate enterprise LLM providers using scalable GenAI application development strategies and prompt engineering tools.
Optimize AI outputs through systematic testing, evaluation metrics, and advanced prompt engineering examples across business scenarios.
Build structured AI solutions that demonstrate how prompt engineering works in real-world enterprise environments.

Course content

9 sections • 40 lectures • 2h 18m total length

Course Introduction3:58
Overview of the course for students to understand what is the course about and instructor introduction.

Generative AI Impact on Engineering4:58
Comprehensive overview of how GenAI is transforming software engineering and development practices.
Fundamentals of Generative AI Systems Architecture3:08
Detailed breakdown of fundamental components that power modern generative AI systems.
Setting Up GenAI Development Environments: Local & Cloud11:48
Step-by-step walkthrough of setting up local and cloud development environments for GenAI.
Enterprise Implementation Success Stories3:10
Analysis of successful GenAI implementations across different industry sectors with metrics.
Hands-On-Learning: Introduction to Generative AI0:14
A Survey of Generative Artificial Intelligence0:15
Introduction to Generative AI

LLM Components and Core Mechanics5:22
Deep dive into the foundational elements that make up modern language models.
Enterprise LLM Model Comparison3:08
Comprehensive comparison of leading LLM models with their strengths and use cases.
LLM Integration and API Setup5:59
Practical demonstration of integrating different LLM APIs into development workflows.
Strategic Model Selection Framework3:13
Systematic approach to choosing the right LLM based on project requirements and constraints.
Hands-On-Learning: LLM Integration and API Setup0:17
A Brief Survey of Large Language Models0:14
Large Language Models

Enterprise GenAI Application Matrix5:29
Structured analysis of GenAI applications across different business functions and departments.
Industry-Specific Solution Architecture4:01
Detailed examination of GenAI solutions customized for different industry requirements.
Support Assistant System Design7:51
Complete walkthrough of designing and planning a customer support AI assistant system.
ROI Measurement and Metrics3:57
Comprehensive framework for measuring and tracking GenAI implementation success metrics.
Hands-On-Learning: Support Assistant System Design0:16
Generative AI Use Cases: A Primer0:14
GenAI Use Cases

Prompt Engineering Core Principles2:59
Comprehensive introduction to the fundamental concepts and principles of effective prompt design.
Structural Elements of Prompts2:59
Detailed analysis of key components that make up well-structured and effective prompts.
Interactive Prompt Building Workflow8:39
Hands-on demonstration of building, testing, and iterating different types of prompts.
Prompt Design Pattern Library2:47
Exploration of proven prompt patterns and when to apply each for optimal results.
Hands-On-Learning: Interactive Prompt Building Workflow0:12
Prompt Engineering Guide0:13
Prompt Engineering Basics

Multi-Step Prompt Chain Design5:14
Advanced techniques for creating complex, multi-step prompt chains for sophisticated tasks.
Context Window Optimization Techniques3:13
Strategies for maximizing context window usage and managing long-form prompt interactions.
Advanced Prompt Implementation Guide12:46
Step-by-step implementation of advanced prompting techniques with real-world examples.
Error Handling Strategy Framework3:04
Comprehensive approach to handling edge cases and errors in prompt responses.
Hands-On-Learning: Advanced Prompt Implementation Guide0:16
A Survey on Prompt Engineering for Large Language Models0:15
Advanced Prompt Engineering
Defending Your Fine-tuning Strategy to a Skeptical Customer Experience Leader

Support Bot Conversation Design5:33
Detailed approach to designing natural and effective customer support conversations.
Response Template Architecture Design3:03
Framework for creating flexible and maintainable customer support response templates.
Template System Implementation Guide10:54
Complete walkthrough of building and testing a support response template system.
Quality Assurance Testing Framework3:09
Comprehensive system for testing and validating support bot responses and interactions.
Hands-On-Learning: Template System Implementation Guide0:16
Prompt Engineering for Developers0:13
Use Case Implementation

Course Conclusion3:51
Instructor recaps key skills, encourages continued experimentation, and highlights additional courses.
Capstone Project: GenAI Engineering System Design Challenge0:09
This project gives you hands-on experience designing a complete GenAI system for a real business challenge. You'll develop practical skills in system architecture, model selection, integration planning, and ROI measurement while applying foundational concepts from generative AI engineering.

Requirements

Participants should have a solid foundation in working with APIs and web services, be comfortable writing and debugging Python code, possess general familiarity with core machine learning concepts, and feel at ease navigating command-line tools. A willingness to experiment and iterate with AI tools will help you get the most out of the hands-on activities.

Description

Have you ever wondered what prompt engineering really means in the context of generative AI and how to apply it beyond basic ChatGPT interactions?

Most professionals understand the power of Generative AI, yet struggle to move from simple prompts to structured, scalable systems that deliver measurable business value. This course bridges that gap.

This comprehensive Prompt Engineering for Generative AI course transforms you from an AI beginner into a skilled AI prompt engineer capable of designing production-ready GenAI applications. You will gain a deep introduction to prompt engineering for generative AI, mastering both foundational concepts and advanced implementation strategies used in real-world AI prompt engineering work.

You’ll explore:

What is prompt engineering in AI and how prompt engineering works

Generative AI prompt engineering basics and advanced optimization techniques

ChatGPT prompt engineering frameworks and structured prompt design

Multi-step prompt chains and LLM prompt optimization

Prompt engineering best practices for enterprise environments

Prompt engineering tools and workflow automation systems

Through hands-on development, you will build sophisticated conversation systems, customer support chatbot architectures, and scalable GenAI applications that integrate multiple LLM providers. You’ll learn how to design structured prompt engineering workflows that consistently produce high-quality, professional outputs across diverse industries.

This program also addresses key career-focused questions:

Does prompt engineering require coding?

What are essential prompt engineering skills?

Is prompt engineering the future of AI-driven work?

How to follow a practical prompt engineering roadmap?

By the end of this course, you will confidently architect Generative AI prompt engineering systems, implement enterprise LLM integrations, and apply AI prompt engineering techniques that create real business impact.

Whether you're pursuing prompt engineering certification, exploring generative AI prompt engineering jobs, or building AI-powered products, this course provides the structured foundation you need.

Start your journey into Prompt Engineering for Generative AI and become the professional who transforms business processes through intelligent AI systems.

Target Audience:

This prompt engineering course is ideal for:

Software Engineers building GenAI applications
Product Managers implementing AI solutions
Data Scientists expanding into generative AI prompt engineering
Business Analysts optimizing AI-driven workflows
Professionals seeking a structured introduction to prompt engineering for generative AI online

Prerequisites:

Basic understanding of APIs and web services
Familiarity with Python programming
General knowledge of machine learning concepts
Experience with command-line tools

(No advanced AI background required.)

Main Outcome:

Learners will be able to design, implement, and optimize complete Prompt Engineering for Generative AI systems, from foundational concepts to advanced multi-step prompt architectures that deliver consistent, production-grade results.

Learning Objectives:

Master generative AI prompt engineering fundamentals and LLM integration strategies
Apply advanced prompt engineering techniques and best practices
Build scalable GenAI application development workflows
Implement customer support chatbot systems using structured prompt engineering
Optimize LLM prompt performance using context engineering and template systems
Design enterprise-ready AI applications with measurable ROI

Key Takeaways:

Complete guide to Prompt Engineering for Generative AI
Production-grade AI prompt engineering mastery
Enterprise LLM integration and provider strategy
Advanced prompt engineering examples and optimization frameworks
Real-world GenAI application architecture

Skills Gained:

Prompt Engineering in AI
Advanced ChatGPT Prompt Engineering
Generative AI Application Development
LLM Prompt Optimization
AI System Architecture
Enterprise AI Solution Design

Who this course is for:

Software engineers embedding generative AI and LLMs into scalable applications using structured prompt engineering techniques.
Product managers implementing AI-driven features and applying ChatGPT prompt engineering to deliver intelligent user experiences.
Data scientists expanding into generative AI prompt engineering, prompt optimization, and production-grade model integration.
Business analysts optimizing workflows through AI prompt engineering tools and advanced automation strategies.

Generative AI Prompt Engineering Certification Course

What you'll learn

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Course content

Course Introduction1 lecture • 4min

Introduction to Generative AI6 lectures • 24min

Large Language Models6 lectures • 18min

GenAI Use Cases6 lectures • 22min

Prompt Engineering Basics6 lectures • 18min

Advanced Prompt Engineering7 lectures • 25min

Use Case Implementation6 lectures • 23min

Course Conclusion2 lectures • 4min

Bonus Lecture1 lecture • 1min

Requirements

Description

Who this course is for: