AdvancedFree to startAlisonAffiliateoptional paid certificate

Basics of Prompt Engineering

by Alison

ProviderAlison

Formatmixed

LevelAdvanced

Accessfree to learn

Certificateoptional paid certificate

Last verified2026-03-30

Affiliate disclosure: Affiliate link. We may earn a commission if you purchase a certificate or diploma, at no extra cost to you. The course content itself is free to enrol, study, and complete on Alison.

About this course

Alison course covering prompt engineering basics including image prompting techniques and advanced prompt patterns.

Last verified: 2026-03-30

Official source

Related courses

See all

Prompt Engineering

DeepLearning.AI

BeginnerFree

ChatGPT Prompt Engineering for Developers

Official DeepLearning.AI short course on prompt engineering for developers.

DeepLearning.AIView

Prompt Engineering

Alison

IntermediateFreeAffiliateCertificate

Prompt Engineering for AI Applications

Learn how to craft effective prompts for AI applications and language models.

32,031 enrolled

AlisonOpen on Alison

Prompt Engineering

Harvard Hks

BeginnerFree

Prompt Engineering

Hands-on Harvard Kennedy School workshop covering prompt engineering techniques including TIC, Chain-of-Thought, and Few-Shot patterns for real-world tasks.

Harvard HksView

Prompt Engineering

AWS

BeginnerFree

Foundations of Prompt Engineering

Official AWS Skill Builder course on prompt engineering fundamentals.

AWSView

Related AI insights

Learning Path: Prompt Engineer

- Prompt engineering has evolved into a technical discipline centered on the precise design and refinement of language model instructions. - Successful practitioners must master three core competencies: system prompt design, few-shot example curation, and chain-of-thought structuring. - Integrating these three specific methodologies into production pipelines is now a requirement for reliable AI deployment. - Predictable application development depends entirely on the mastery of prompt architecture. Technical proficiency in prompt design is the primary requirement for moving AI applications from experimental prototypes to stable production environments.

Read →