GenAI Foundations and Prompt Engineering
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GenAI Foundations and Prompt Engineering
This course is part of GenAI Data and Analytics Academy Specialization
Instructors: Ritesh Vajariya
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What you'll learn
Master GenAI foundations and LLM integration strategies for scalable enterprise applications.
Construct advanced prompt engineering workflows with multi-step chains and context optimization.
Implement enterprise GenAI use cases with systematic design and ROI measurement frameworks.
Develop production-ready conversation systems with template engines and quality assurance protocols.
Skills you'll gain
Tools you'll learn
Details to know
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- Gain a foundational understanding of a subject or tool
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- Earn a shareable career certificate
There are 3 modules in this course
Have you ever struggled to get consistent, high-quality responses from GenAI systems or wondered how to build chatbots that genuinely understand your customers’ needs? While many professionals recognize the power of Generative AI (GenAI), few understand how to effectively communicate with it to unlock its full potential.
This GenAI Foundations course transforms you into a prompt engineering expert. You’ll learn to design sophisticated interactions with large language models, master the architecture of GenAI systems, and explore real-world enterprise applications. By practicing advanced prompt engineering techniques, you’ll learn how to consistently deliver exceptional results. You’ll build multi-step prompt chains, optimize context windows, and create customer support chatbots that provide human-like interactions. Tailored for professionals aiming to deepen their AI integration skills, this course is ideal for software engineers embedding GenAI into applications, product managers implementing AI-driven features, data scientists expanding into generative AI models, and business analysts optimizing workflows with AI capabilities. Whether you’re developing prototypes or full-scale production systems, you’ll be equipped to elevate your AI initiatives. Participants should be comfortable with APIs, web services, Python coding, and general machine learning concepts. Familiarity with prompt engineering tools and a willingness to experiment will help you excel. By course end, you’ll be able to apply GenAI architecture principles to design scalable AI applications, craft advanced prompt engineering patterns for various business use cases, build interactive multi-step workflows, and create robust customer support systems. These skills will empower you to lead AI-driven innovation in your organization.
In this module, you’ll learn how to design and build robust GenAI applications by exploring the core architecture and components of modern AI systems. You’ll set up a professional development environment—configuring SDKs, tooling, and data pipelines—and examine real-world enterprise implementations to see how organizations leverage GenAI for competitive advantage. Through expert-led walkthroughs, hands-on setup exercises, and case-study analyses, you’ll gain the skills to deploy scalable, production-ready generative AI solutions.
What's included
13 videos4 readings1 assignment3 peer reviews3 discussion prompts
13 videos•Total 66 minutes
- Course Introduction •4 minutes
- Generative AI Impact on Engineering •5 minutes
- Fundamentals of Generative AI Systems Architecture •3 minutes
- Setting Up GenAI Development Environments: Local & Cloud •12 minutes
- Enterprise Implementation Success Stories •3 minutes
- LLM Components and Core Mechanics •5 minutes
- Enterprise LLM Model Comparison •3 minutes
- LLM Integration and API Setup •6 minutes
- Strategic Model Selection Framework •3 minutes
- Enterprise GenAI Application Matrix •5 minutes
- Industry-Specific Solution Architecture •4 minutes
- Support Assistant System Design •8 minutes
- ROI Measurement and Metrics •4 minutes
4 readings•Total 20 minutes
- Welcome to the Course: Course Overview•5 minutes
- A Survey of Generative Artificial Intelligence •5 minutes
- A Brief Survey of Large Language Models •5 minutes
- Generative AI Use Cases: A Primer •5 minutes
1 assignment•Total 20 minutes
- GenAI Foundations •20 minutes
3 peer reviews•Total 30 minutes
- Hands-On-Learning: Introduction to Generative AI•10 minutes
- Hands-On-Learning: LLM Integration and API Setup •10 minutes
- Hands-On-Learning: Support Assistant System Design •10 minutes
3 discussion prompts•Total 15 minutes
- Identifying High-Impact GenAI Opportunities in Your Organization•5 minutes
- Strategic LLM Selection and Trade-Off Analysis for Enterprise Use Cases•5 minutes
- Identifying Quick Wins and Strategic Bets for GenAI Implementation•5 minutes
In this module, you’ll master the art of prompt engineering by exploring the core principles of prompt design, the structural elements that drive model behavior, and the spectrum of prompt patterns—single-shot, few-shot, and chain-of-thought. You’ll learn how to craft, test, and refine prompts for diverse business scenarios, understand the trade-offs between prompt complexity and performance, and apply evaluation metrics to ensure consistent, high-quality outputs. Through expert-led demos, hands-on prompt labs, real-world case studies, and interactive assessments, you’ll gain the skills to engineer prompts that reliably unlock the full power of generative AI.
What's included
12 videos3 readings1 assignment3 peer reviews3 discussion prompts
12 videos•Total 66 minutes
- Prompt Engineering Core Principles •4 minutes
- Structural Elements of Prompts •3 minutes
- Interactive Prompt Building Workflow •9 minutes
- Prompt Design Pattern Library •3 minutes
- Multi-Step Prompt Chain Design •5 minutes
- Context Window Optimization Techniques •3 minutes
- Advanced Prompt Implementation Guide •13 minutes
- Error Handling Strategy Framework •3 minutes
- Support Bot Conversation Design •6 minutes
- Response Template Architecture Design •3 minutes
- Template System Implementation Guide •11 minutes
- Quality Assurance Testing Framework •3 minutes
3 readings•Total 15 minutes
- Prompt Engineering Guide •5 minutes
- A Survey on Prompt Engineering for Large Language Models •5 minutes
- Prompt Engineering for Developers •5 minutes
1 assignment•Total 20 minutes
- Prompt Engineering•20 minutes
3 peer reviews•Total 30 minutes
- Hands-On-Learning: Interactive Prompt Building Workflow•10 minutes
- Hands-On-Learning: Advanced Prompt Implementation Guide •10 minutes
- Hands-On-Learning: Template System Implementation Guide •10 minutes
3 discussion prompts•Total 15 minutes
- Applying Core Prompt Engineering Principles to Redesign Your AI Interactions•5 minutes
- Designing and Optimizing Multi-Step Prompt Chains for Complex Business Processes•5 minutes
- Designing Empathetic and Efficient Support Bot Conversation Flows•5 minutes
In this module, you’ll consolidate your GenAI and prompt engineering expertise by recapping core techniques, reflecting on real-world applications, and charting your continued growth path. You’ll integrate skills into end-to-end project scenarios, explore advanced topics like Retrieval-Augmented Generation and AI agents, and plan your specialization roadmap. Through instructor-led reflections, interactive planning exercises, and curated resource guides, you’ll finish ready to apply your learning confidently and pursue deeper mastery.
What's included
1 video1 peer review
1 video•Total 4 minutes
- Course Conclusion •4 minutes
1 peer review•Total 60 minutes
- Project: GenAI Engineering System Design Challenge•60 minutes
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Frequently asked questions
This course covers Generative AI Foundations, Prompt Engineering, ChatGPT workflows, AI prompting techniques, and practical applications of generative AI tools across industries.
Yes. This beginner-friendly GenAI Foundations course is designed for learners with no prior AI, programming, or technical experience.
You’ll learn prompt engineering best practices, prompt design techniques, AI communication strategies, and how to create effective prompts for ChatGPT and other generative AI tools.
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Financial aid available,
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.
