Full AI Prompting Course with Andrew Ng

2026-05-18 · Source: DeepLearningAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Data Science & Analytics · Depth: Intermediate, extended

Summary

This content provides a comprehensive guide to becoming an "AI power user" in 2026, highlighting advanced prompting techniques beyond basic queries. It contrasts novice AI usage with expert strategies across several domains, including answering complex questions, providing sufficient context, obtaining objective feedback, and effective writing. The guide details how AI models acquire knowledge, distinguishing between pre-trained knowledge and real-time information gathering via web search and "deep research." It also explores multimodal prompting for generating images, videos, voices, and code, and introduces AI desktop applications for agentic context management. The content emphasizes reasoning capabilities, managing AI's sycophancy, and iterative workflows for brainstorming, writing, and editing. Practical labs and a final project are suggested to apply these skills in building games, websites, and performing data analysis.

Key takeaway

For AI Engineers and Data Scientists aiming to maximize AI utility, focus on providing comprehensive context and adopting iterative prompting strategies. Your ability to frame neutral questions and leverage AI's deep research and multimodal generation capabilities will significantly enhance output quality and efficiency, moving beyond generic "AI slop" to truly valuable, customized results.

Key insights

Mastering AI involves advanced prompting, context provision, and iterative workflows to leverage its reasoning and multimodal capabilities.

Principles

• Provide ample context for accurate AI responses.
• Frame questions neutrally to avoid AI sycophancy.
• Iterate with AI for refined, creative outputs.

Method

Utilize progressive outlining for writing, provide rubrics for objective critique, and employ iterative feedback loops for brainstorming and complex problem-solving with AI.

In practice

• Upload documents for complex car shopping trade-offs.
• Use rubrics to get objective feedback on written work.
• Start new conversations for unrelated AI tasks.

Topics

• Advanced AI Prompting
• Context Management
• Deep Research
• Multimodal AI Generation
• Agentic AI Systems

Best for: AI Student, AI Engineer, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by DeepLearningAI.