SAMURAI Adds 'AI Agent Engineer Course' to Subscription-based IT Learning Service 'Samurai Terakoya'

SAMURAI Inc. has launched the 'AI Agent Engineer Course' within its subscription-based IT learning service, 'Samurai Terakoya' (https://terakoya.sejuku.net/). The course is designed to quickly train job-ready engineers capable of handling AI agent development, including RAG and LLM applications. Learners can study step-by-step, starting from the basics of Python, GitHub, generative AI, and APIs, up to developing AI agents using RAG and CrewAI.

About the 'AI Agent Engineer Course' Due to rapid advancements in AI, its utilization is shifting from traditional chat-based 'tool usage' to 'agent construction,' where AI autonomously executes tasks. This paradigm is highly compatible with current business challenges such as automating complex workflows and addressing organizational dependency on individuals, enabling more effective operational improvements. The course aims to equip students with the ability to solve actual business problems by mastering the Python-based framework stack, including LangChain and CrewAI, and developing PoC (Proof of Concept) skills. It provides practical learning to step up from being a 'user' of generative AI to an 'agent builder' who automates business processes.

Course Features Students learn to use over 10 types of AI depending on the purpose, cultivating practical skills to generate revenue. The curriculum covers everything from creating deliverables (articles, videos, designs) to monetization mechanisms and the basics of acquiring projects. 1. Acquisition of Basic Implementation Skills (Python × API) Covers environment setup, the foundation of AI app development, and the implementation of 'chatbots' and 'summarization tools' using the OpenAI API. 2. Construction of Autonomous Systems (RAG × Latest Frameworks) Students learn design methods to assign 'investigation, judgment, and execution' roles to AI, and build RAG (Retrieval-Augmented Generation) infrastructure that references proprietary data. 3. Practical PoC Development Directly Linked to Business Cultivates the ability to design and complete prototypes that can be verified in real business environments.

Learning Path STEP 1: Learning Python × API Implementation Skills - Fundamentals: Python, GitHub, prompt design, and OpenAI API basics. - Mini-tool Development: Mastering API calls and conversation history management by creating CLI apps like 'AI Consultation Chatbots' and 'Article Summarization Tools.' STEP 2: Building AI Agents and RAG - RAG Implementation: Using Embeddings and FAISS (vector databases) to create a search infrastructure that references proprietary data like manuals. - Agent Design: Learning to decompose tasks and assign roles (e.g., 'Researcher,' 'Summarizer,' 'Decision-maker') to AI. - Framework Utilization: Building advanced systems where multiple AI agents work in coordination using LangChain and CrewAI. - Final Project (PoC Development): Completing practical AI app PoCs, such as 'FAQ Knowledge Response Agents' or 'Automated Customer Support Response Systems.'

About 'Samurai Terakoya' 'Samurai Terakoya' is one of the most affordable subscription services in Japan, providing a practical and high-quality learning environment. It features one-on-one online lessons with active engineers, over 150 practical materials with task functions, and a 'Q&A Bulletin Board' for instant help whenever a student hits a roadblock.