
What happened
A SAP engineer with about 20 years on the job passed E資格(2026#2) after roughly 240 hours of study, using AVILEN courses and Claude Code to build runnable samples and quiz himself.
Why it matters
His experience suggests AI assistants can act as a study aid for hard technical material—especially for weak areas like reinforcement learning—when answers are independently verified.
Summaries like this, every morning.
The author's background shaped his study plan. He had already earned G検定 in 2023#5, so machine learning fundamentals came relatively easily, but probability and statistics were long-standing weak points and information theory and Python were new to him. He chose AVILEN courses because they advertised a high pass rate, and he spent roughly a month on the machine learning course before moving to the E資格 course from late January to mid-May 2026. The first chapter's programming test on MLP basics was a major hurdle: he resubmitted about 10 times and took roughly a week to pass, repeatedly returning to the probability, statistics, and information theory material.
He passed the course completion exam in the first week of June 2026, though just barely, and then worked through additional problem sets. He assigned high, medium, and low priorities to each topic, but in the final week before the exam he also touched the low-priority topics—and several questions from that range appeared on the test. On exam day, he found fewer questions than expected from areas he had predicted, while about 10 questions came from the ViT area, which he believed had rarely been tested. His advice to future test-takers is to check the new syllabus rather than rely only on past-question trends, and to expect a topic to reappear later in the exam even after it has appeared early.
On AI use, he did not take Claude Code's answers at face value and verified them himself. He also distinguishes the certifications by purpose: G検定 is sufficient for those who want to use generative AI in business, while E資格 suits people who want to understand model internals and the math, and treating it as a hobby is a valid choice.
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