Generative AI: Prompt Engineering Basics

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Generative AI: Prompt Engineering Basics

Coursera · Beginner ·🧠 Large Language Models ·3mo ago

Key Takeaways

Covers prompt engineering basics for Generative AI

Original Description

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 c
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
A Silent Crash in Megatron-LM’s Gradient Clipping (and a Reviewer Who Made My Fix Better)
Learn how a reliability bug in Megatron-LM's gradient clipping was fixed and why the simplest solution isn't always the first one you write
Medium · Machine Learning
📰
Had issue with Token usage limits, so converting my text prompts to image
Convert text prompts to images to bypass token usage limits with near-perfect accuracy using optical compression
Reddit r/webdev
📰
Part 3: The Ablation — When Fairness and Language Model Quality Conflict
Learn how bias-aware IPW loss affects fairness and language model quality in real-world scenarios, and understand the trade-offs between these two goals
Medium · Data Science
📰
Nemotron Labs: How Open Models Give Enterprises and Nations AI They Can Trust, Control and Customize
Learn how open models can give enterprises and nations AI they can trust, control, and customize to improve workflows and exceed accuracy standards
NVIDIA AI Blog
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →