Generative AI: Prompt Engineering Basics
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Generative AI: Prompt Engineering Basics
Instructor: Board Infinity
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What you'll learn
Master the fundamentals of Generative AI and prompt engineering for real-world applications in text, code, and automation.
Create effective prompts that generate accurate, context-aware, and high-quality AI responses across diverse domains.
Apply advanced prompting methods like zero-shot, few-shot, and chain-of-thought for optimized AI outputs.
Analyze and refine prompts using performance metrics while ensuring ethical and responsible AI usage.
Skills you'll gain
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13 assignments
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There are 2 modules in this course
The course provides a comprehensive introduction to Generative AI and Prompt Engineering, equipping learners with the knowledge and skills to craft effective prompts that produce accurate, high-quality outputs across multiple domains. It is designed for professionals, students, and enthusiasts aiming to optimize AI interactions, enhance digital workflows, and leverage tools like GPT, ChatGPT, Bard, and IBM Watson.
Learners will explore foundational AI concepts, the evolution of large language models, and the mechanics of prompt engineering. Practical lessons cover crafting prompts for diverse applications such as text generation, code debugging, content creation, and automation. Advanced sections dive into strategies like zero-shot and few-shot prompting, chain-of-thought techniques, and refining prompts for accuracy, context, and tone. The course also emphasizes ethical considerations in AI use, including bias, fairness, and responsible deployment. By combining theory, hands-on practice, and real-world case studies, learners will gain confidence in designing prompts that deliver consistent, reliable, and domain-specific outcomes. By the end of this course, you will be able to: - Understand Generative AI fundamentals and their applications across industries. - Craft prompts that yield precise, high-quality AI responses. - Apply advanced techniques such as chain-of-thought and zero/few-shot prompting. - Evaluate prompt effectiveness using key metrics and refine strategies for optimization. Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.
This module introduces learners to the principles of Generative AI, the evolution of AI models, and the basics of prompt engineering. It covers practical use cases such as content creation, automation, and code generation. Learners will gain hands-on experience with crafting simple prompts, evaluating outputs, and applying effective strategies like zero-shot and few-shot learning.
What's included
16 videos2 readings6 assignments1 discussion prompt1 plugin
16 videosβ’Total 59 minutes
- Introduction to the Courseβ’2 minutes
- Meet your Instructorβ’1 minute
- Overview of Generative AI and how it worksβ’3 minutes
- The evolution of Generative AI in various sectorsβ’2 minutes
- Key models (GPT, BERT, T5, etc.) and their use casesβ’4 minutes
- Real-world applications: Text generation, content creation, and automationβ’3 minutes
- Practical Implementation: Content Creation and Writing Tasksβ’6 minutes
- What is prompt engineering, and why is it important?β’3 minutes
- How prompts shape AI responsesβ’3 minutes
- Key principles for crafting effective promptsβ’4 minutes
- Common pitfalls in prompt design and how to avoid themβ’4 minutes
- Practical Implementation: Problem-Solving and Analysisβ’4 minutes
- Zero-shot and Few-shot Learningβ’4 minutes
- Chain-of-Thought (CoT) and Tree-of-Thought (ToT) strategiesβ’4 minutes
- Using creative and specific prompt modifiersβ’4 minutes
- Practical Implementation: Industry-Specific Applicationsβ’7 minutes
2 readingsβ’Total 20 minutes
- Syllabusβ’5 minutes
- Read more about Generative AI: Foundations, Applications, and Best Practicesβ’15 minutes
6 assignmentsβ’Total 65 minutes
- Practice Quiz: Introduction to Generative AI and Industry Applicationsβ’10 minutes
- Untitledβ’15 minutes
- Practice Quiz: The Essentials of Prompt Engineeringβ’5 minutes
- Untitledβ’15 minutes
- Practice Quiz: Techniques for Crafting Effective Promptsβ’5 minutes
- New Quiz -Techniques for Crafting Effective Promptsβ’15 minutes
1 discussion promptβ’Total 5 minutes
- What Do You Want AI to Help You Do Better?β’5 minutes
1 pluginβ’Total 15 minutes
- Quick Course Check-Inβ’15 minutes
This module delves into advanced prompt engineering techniques, equipping learners with the skills to craft precise, effective, and optimized prompts for AI interactions. Learners will explore techniques for refining prompts, structuring them for clarity, and iterating to improve AI-generated responses. The module also covers industry applications of prompt engineering, such as content creation, automation, multimedia generation, and coding. Additionally, learners will gain insights into evaluating AI performance, addressing ethical concerns, and understanding emerging trends in prompt engineering. By the end of this module, learners will have a deep understanding of how to optimize AI interactions across various domains.
What's included
11 videos1 reading7 assignments1 discussion prompt
11 videosβ’Total 42 minutes
- Refining and fine-tuning prompts for accuracyβ’4 minutes
- Experimenting with prompt structures, specificity, and contextβ’4 minutes
- Iterative prompting for better resultsβ’3 minutes
- Tools and platforms for advanced prompt engineering (IBM Watsonx, LangChain, etc.)β’4 minutes
- Using AI for content creation (SEO, blog writing, digital marketing)β’5 minutes
- Prompt engineering for code generation and automationβ’5 minutes
- Exploring multimedia AI: image, video, and audio generationβ’4 minutes
- Key metrics to evaluate prompt performanceβ’4 minutes
- Ethical AI: Addressing biases and ensuring responsible useβ’5 minutes
- The future of prompt engineering: Trends, career paths, and emerging technologiesβ’2 minutes
- Course Closure - Gratitude !β’1 minute
1 readingβ’Total 15 minutes
- Read more about Optimizing AI Prompts: Refinement, Evaluation, and Ethical Considerationsβ’15 minutes
7 assignmentsβ’Total 120 minutes
- Graded Quizβ’60 minutes
- Practice Quiz: Advanced Prompt Engineering Techniquesβ’5 minutes
- New Quiz: Advanced Prompt Engineering Techniquesβ’15 minutes
- Practice Quiz: Real-World Applications of Prompt Engineeringβ’5 minutes
- New Quiz Real-World Applications of Prompt Engineeringβ’15 minutes
- Practice Quiz: Evaluating AI Performance and Ethical Considerationsβ’5 minutes
- Untitledβ’15 minutes
1 discussion promptβ’Total 10 minutes
- Where Could Better Prompts Make the Biggest Impact?β’10 minutes
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Reviewed on Dec 6, 2025
Well Designed and explained the content with example in simple way
Reviewed on Oct 14, 2025
already have made improvement toward my goals just from this course and would highly suggest if you're feeling behind the times.
Reviewed on Jul 6, 2025
Excellent Content. Easy to understand and well presented.
Frequently asked questions
Prompt engineering is the practice of designing and refining inputs to AI models like GPT or ChatGPT to generate accurate, context-specific, and reliable outputs. This course provides practical training on using prompt engineering across text, code, marketing, and automation tasks.
Learning prompt engineering helps professionals, developers, and students harness AI tools effectively. By mastering prompts, you can improve AI accuracy, reduce errors, and create optimized workflows in software development, content creation, and business processes.
You will learn how to design prompts for multiple domains, apply advanced techniques like zero-shot and chain-of-thought prompting, evaluate outputs with performance metrics, and integrate ethical considerations in AI-powered solutions.
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