Azure AI Fundamentals in Seoul
Microsoft's entry-level AI certification covering machine learning, computer vision, NLP, and generative AI on Azure.
What is Azure AI Fundamentals?
The Azure AI Fundamentals certification (AI-900) is Microsoft's entry-level credential covering core AI and machine learning concepts on the Azure cloud platform. It validates your understanding of AI workloads, machine learning principles, computer vision, natural language processing, and responsible AI practices. In Seoul, where global tech firms like Samsung, LG, Kakao, and a growing cluster of Microsoft Azure partners are actively building AI-driven products, this certification signals that you speak the language of modern cloud AI. No prior technical experience is required, making it one of the most accessible starting points for IT professionals, career changers, and business analysts in Seoul's competitive tech market.
At an exam cost of $165 USD, the Azure AI Fundamentals certification offers one of the sharpest ROI profiles for entry-level IT credentials in Seoul. With the average IT salary in Seoul sitting around $55,000 per year, a verified average uplift of $7,000 annually means this certification can pay for itself within weeks of landing your next role or promotion. Seoul's AI job market is expanding rapidly, with local enterprises and multinational firms prioritizing Azure-fluent candidates as cloud adoption accelerates across Korea. Renewing every two years keeps your credential current with minimal ongoing cost. For anyone starting an AI or cloud career path in Seoul, AI-900 is a low-risk, high-return first move.
Exam details
Prerequisites: None required
12-week study plan
Exam tips
Know the specific Azure service for each AI use case cold — examiners frequently present a scenario and ask you to identify whether the answer is Azure Bot Service, Cognitive Services, Azure Machine Learning, or another tool. Mixing these up is the most common mistake.
Memorize Microsoft's six responsible AI principles (fairness, reliability, privacy, inclusiveness, transparency, accountability) and be ready to apply them to scenario questions, not just recite them — AI-900 tests application, not definitions.
Understand the difference between machine learning model types: classification, regression, and clustering. You won't write code, but you must know which type solves which kind of problem and how Azure Machine Learning supports each.
Pay close attention to natural language processing services — questions on sentiment analysis, key phrase extraction, language detection, and Azure's Language Studio appear frequently and are easy marks if you've done the hands-on demos.
Use the official AI-900 exam skills outline from Microsoft's certification page as your study checklist — every topic on the exam is listed there by percentage weight, so prioritize AI workloads and Azure AI services, which together account for the majority of scored questions.