Free to audit
Skills you'll gain
AI Product Strategy AI Security Artificial Intelligence Automation ChatGPT Cloud Applications Generative AI Large Language Modeling Prompt Engineering Responsible AI Social Impact
What our experts say
- Don’t watch the course like a movie
- Avoid getting lost halfway & losing the interest
- Don’t enroll to many courses at a time
- Decide your learning path and enroll one course at a time
- Make the smart combo of Courses & Books
- Pause the lectures for hands-on practice
- Refer to Terms when necessary
- Watch Talks & Podcasts for motivation, during the breaks
*Disclaimer: Our experts work continuously on shortlisting the best free courses for you. However, you need to ensure the latest pricing structure of each course provider. If they make it paid, we will try to bring you the best free alternative soon.
Is this course completely free?
The course can be audited for free on DeepLearning.AI’s platform or Coursera, allowing you to watch all video lectures and access readings without charge. However, if you want a shareable certificate and access to graded quizzes, you’ll need to pay approximately $49 for Coursera’s monthly subscription. Most learners complete the course within one month, keeping costs minimal. Financial aid is available through Coursera if you cannot afford the fee—simply apply when enrolling. The educational content itself is accessible to everyone regardless of ability to pay.
Do I need any technical background or coding skills?
Absolutely not. This course requires no coding skills, mathematics knowledge, or prior AI experience. It’s intentionally designed for non-technical learners including business leaders, marketers, designers, educators, and anyone curious about generative AI. Andrew Ng explains complex concepts in plain language without equations or programming, focusing on practical applications and strategic thinking. If you can use a web browser and are curious about ChatGPT, Midjourney, or other generative AI tools, you’re fully qualified to take this course. The hands-on exercises involve using AI tools through simple interfaces, not writing code.
How does this differ from “AI For Everyone”?
While “AI For Everyone” provides a broad introduction to all types of AI including traditional machine learning, “Generative AI For Everyone” focuses specifically on the recent revolution in generative AI technologies like ChatGPT, DALL-E, and Stable Diffusion. This course dives deeper into how large language models work, practical prompt engineering techniques, and modern applications of generative AI in writing, coding, and creative tasks. It covers newer concepts like RAG, fine-tuning, and AI agents that weren’t prominent when “AI For Everyone” was created. Think of “AI For Everyone” as foundational AI literacy, while this course focuses specifically on the generative AI tools transforming work today.
What practical skills will I gain?
You’ll learn effective prompt engineering techniques to get better results from tools like ChatGPT, understand when to use generative AI for writing assistance, document summarization, or conversational interfaces, and gain hands-on experience with AI tools through exercises. The course teaches you to analyze jobs and workflows to identify automation opportunities, choose appropriate models and technologies for different use cases, and understand advanced techniques like RAG for improving AI responses with your own data. You’ll also develop strategic thinking about implementing generative AI in organizations, managing costs, and building teams for AI projects, enabling you to lead AI initiatives even without technical skills.
What are the hands-on exercises like?
The course includes practical exercises where you’ll directly use generative AI tools to accomplish real tasks. You’ll practice crafting effective prompts for different purposes, experiment with AI for writing and reading tasks, and explore conversational AI applications. There’s an optional exercise where you can try generative AI code yourself to see how these tools integrate into software applications. The exercises use web-based interfaces requiring no installation or setup—you simply use your browser to interact with AI tools. This hands-on approach ensures you gain practical experience, not just theoretical knowledge, making you immediately productive with generative AI in your own work.
How long does it take to complete this course?
The course contains approximately 3-4 hours of video content spread across three weeks, with an estimated time commitment of 1-2 hours per week. Most learners complete the entire program in 3-4 weeks at this recommended pace, though the self-paced format offers flexibility. Some motivated learners finish in a weekend by dedicating concentrated time, while others spread it over a month to thoroughly explore the tools and complete exercises. The compact format makes it one of the most efficient ways to become literate in generative AI, providing comprehensive knowledge without requiring a major time investment.
What topics related to AI safety and ethics are covered?
The course seriously addresses responsible AI and societal impacts of generative AI. Week 3 explicitly covers concerns about AI including bias, misinformation, privacy issues, and potential job displacement across sectors. Andrew discusses artificial general intelligence (AGI) to help you separate realistic concerns from science fiction hype. The course teaches responsible AI principles and best practices for deploying generative AI ethically in organizations. You’ll learn to think critically about automation potential across different jobs and sectors, understand the technology’s limitations to avoid misuse, and consider broader societal implications. This balanced perspective helps you harness generative AI’s benefits while being mindful of risks and ethical considerations.
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