AI For Everyone Course Review – Completing the AI Literacy Course by Andrew Ng

If you want to build AI literacy, there’s one course you should take first: Coursera’s AI For Everyone. But many people wonder “Is it really useful?” or “Is it too difficult?” In this article, I’ll give an honest review of the course content, difficulty level, and the value of the completion certificate, having actually completed the AI literacy course myself. The bottom line: it’s the perfect first step for anyone interested in AI.

What Is “AI For Everyone”?

AI For Everyone is a course developed by Professor Andrew Ng, a leading AI researcher and co-founder of Coursera. It’s designed for general business professionals, not engineers — no programming or math knowledge is required whatsoever. Over 8 million people have taken Professor Ng’s AI courses, making it a global standard in AI education.

The Japanese version is supervised by JDLA (Japan Deep Learning Association) and includes additional content by Professor Yutaka Matsuo of the University of Tokyo, covering what DX (Digital Transformation) means, the importance of AI in DX, and the current state of AI utilization in Japan.

Why AI Literacy Is in Demand

According to Japan’s Ministry of Economy, Trade and Industry estimates, there will be a shortage of up to 124,000 AI professionals by 2030. However, “AI professionals” doesn’t just mean engineers. There’s a shortage of business professionals across all roles who understand AI’s possibilities and limitations and can appropriately apply AI to their work.

In reality, many organizations introduce AI tools only to see them go unused. This is almost always caused not by technical issues but by a lack of AI understanding. Without basic knowledge of “what AI can and cannot do” and “how to approach AI projects,” even the most powerful tools won’t deliver results. AI For Everyone is designed precisely to solve this challenge.

Course Structure and Content

The course consists of 4 modules with approximately 6 hours of total learning time. It progresses through watching videos and answering quizzes, allowing you to learn at your own pace.

Week 1: “What Is AI?” — Covers basic concepts of machine learning and deep learning, differences between supervised and unsupervised learning, and what AI can and cannot do. Technical details are avoided, focusing on the level business professionals need to understand.

Week 2: “Building AI Projects” — Covers how to run AI projects, how to collect data, and how to collaborate with technical teams. The focus is on the practical perspective of “how to make AI projects succeed” rather than “what AI can do.”

Week 3: “Building AI in Your Company” — Covers how to develop AI strategy, organize AI teams, and common failure patterns in AI implementation and how to avoid them. Particularly valuable for executives and management.

Week 4: “AI and Society” — Discusses AI ethics, bias issues, AI’s impact on employment, and skills needed in the AI era. Provides perspective for understanding AI in a social context, not just technical.

My Honest Impressions After Completing the Course

Honestly, the difficulty level is low. Almost everything is provided in the target language, and you progress simply by watching videos and answering quizzes. I set aside dedicated time and was able to complete it quickly. Interestingly, the basic concepts of AI literacy are simpler than you might imagine. Technical terms are carefully explained, making the structure resistant to beginner dropout.

Professor Ng’s explanations are exceptionally clear — his skill at explaining complex concepts through simple analogies is masterful. On the other hand, for those who already have foundational AI knowledge or regularly use generative AI tools like ChatGPT, the content may feel too basic. This course is strictly about going “from zero to one” in AI literacy.

Value of the Completion Certificate

Upon completion, a certificate is issued jointly by DeepLearning.AI and JDLA. The certificate bears signatures from Professor Andrew Ng and Professor Yutaka Matsuo, along with Coursera’s certification mark. It can be listed on resumes and LinkedIn as proof of AI literacy training.

As an additional practical benefit, presenting this certificate qualifies you for a 30% discount on the JDLA G-Exam (Generalist Exam) fee. The G-Exam is gaining recognition as Japan’s standard AI literacy certification and can serve as a learning path from AI For Everyone.

However, honestly, the direct career impact of the certificate itself is limited. It’s more appropriate to view this course as a “first step in learning” rather than a “credential.” The real value lies not in the certificate itself but in the foundational AI literacy knowledge gained and the perspective for applying it to work.

Pricing and How to Enroll

AI For Everyone is available through Coursera’s subscription (approximately $49/month). Since total learning time is about 6 hours, most learners can complete it within one billing cycle — making the effective cost around $49.

Coursera also offers an “Audit” mode where all video content and readings are accessible for free. However, graded quizzes and the completion certificate are only available with paid plans. It’s a smart approach to check the content for free first, then switch to paid if you decide you want the certificate.

Tips for Efficient Learning

Set video playback speed to 1.25x or 1.5x to learn more efficiently. Professor Ng’s English is clear and easy to follow, and with subtitles available, increasing speed doesn’t hinder comprehension.

Always take the quizzes at the end of each module. They serve not just as comprehension checks but also help solidify learning. While not particularly difficult, they’re designed so you can’t answer correctly without properly understanding the course content.

Even more effective is applying what you learn to your own work. For example, while listening to Week 2’s approach to AI projects, write down 3 business processes where AI could be utilized in your workplace. After learning about AI’s limitations in Week 3, consider the limitations of AI tools already deployed in your company. This exercise of converting course content into personal relevance dramatically improves knowledge retention.

Pros and Cons from a Course Graduate

The biggest benefit I felt after completion was building a foundation for understanding AI-related news and discussions. Before the course, I only had vague impressions of terms like machine learning and neural networks. After completion, I could correctly understand these concepts and explain AI-related information in my own words. This is extremely useful in business settings.

Another benefit was gaining advance awareness of AI project pitfalls. Knowledge of AI project workflows and common failure patterns immediately proves useful when negotiating with AI vendors or proposing AI adoption internally. You become able to judge how much data a project needs and why 100% accuracy shouldn’t be expected.

As for drawbacks, the content is basic. Those who’ve experienced the generative AI boom since 2024 may find some familiar content. The convenience of approximately 6 hours, conversely, means that’s all the depth you get. For deeper technical understanding, you’ll need to proceed to more specialized courses like Professor Ng’s Machine Learning Specialization.

What to Study Next

After completing AI For Everyone, here are your next step options. For generative AI specialization, Professor Ng’s “Generative AI for Everyone” is recommended — over 100,000 people enrolled within just 2 months of its 2023 release. For AI literacy certification, challenge the JDLA G-Exam with the 30% discount from your completion certificate. For practical AI use, start by incorporating generative AI tools like ChatGPT and Claude into daily work tasks.

Difference from Generative AI for Everyone

Professor Ng has also released “Generative AI for Everyone” as a sequel to AI For Everyone. The names are similar and easily confused, but they cover distinctly different domains.

AI For Everyone surveys the entire landscape of AI — basic concepts of machine learning and deep learning, how to run AI projects, and social impact. Generative AI for Everyone focuses on how large language models (LLMs) work, prompt engineering, and business applications of generative AI.

The ideal sequence is to first solidify AI fundamentals with AI For Everyone, then proceed to Generative AI for Everyone. The foundational concepts learned in AI For Everyone — supervised learning, the importance of data, AI’s limitations — are essential for understanding generative AI. Combined, the total learning time is about 12 hours, easily digestible over a weekend.

Frequently Asked Questions

Should I take the English or Japanese version?

If you’re comfortable with Japanese, the Japanese version is recommended. Professor Matsuo’s additional content on Japan’s AI landscape offers unique value not found in the English version. The G-Exam discount also applies with the Japanese version’s certificate. If you want to improve your English, the English version is also a valid choice.

Is it worth it for engineers?

The technical content may feel insufficient for AI engineers. However, from the perspective of “how to explain AI to non-technical people” and “how to drive AI projects within an organization,” there are learnings even for engineers. Particularly beneficial for engineers who serve as bridges between business and technical sides.

Is the content still relevant in 2026?

AI For Everyone centers on AI “principles and concepts” and doesn’t depend on specific tools or models, so it hasn’t significantly become outdated. However, the generative AI revolution since 2022 isn’t fully covered. For the latest generative AI developments, supplementing with “Generative AI for Everyone” is the best approach.

Can it be adopted as corporate training?

Coursera offers a corporate plan (Coursera for Business) that enables team-based enrollment management and progress tracking. Since AI For Everyone requires no programming and centers on business perspectives, it’s highly suitable for AI literacy training in non-engineering departments. Many companies have already incorporated it into their internal training curricula.

Conclusion: The Perfect First Step for AI Literacy

AI For Everyone provides not deep technical knowledge but “perspective for understanding AI.” Being able to cover AI’s basic concepts, project management approaches, and social impact in approximately 6 hours is highly efficient.

AI knowledge is becoming an essential skill for future careers. Regardless of whether you’re an engineer, the era of working alongside AI has already begun. Once you have your completion certificate, the next step is to actually use AI tools in your work. Knowledge only has value when put to use.

Start by opening the AI For Everyone page on Coursera and playing the first video with a free trial. Six hours later, your perspective on AI will have changed.

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AIを使って、毎日の生活をもっと快適にするアイデアや将来像を発信しています。 初心者にもわかりやすく、すぐに取り入れられる実践的な情報をお届けします。 Sharing ideas and visions for a better daily life with AI. Practical tips that anyone can start using right away.