Spring AI Multi-LLM Architecture and Orchestration-focused Agent System

I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.

This course is a hands-on program for implementing generative AI applications based on text, images, voice, and documents using the OpenAI API. Starting from setting up the Anaconda and Jupyter Notebook environment, it covers essential development environment configurations for practical work, including API Key management and understanding costs and tokens. Based on the latest Responses API, you'll implement text generation, summarization, classification, Vision (image understanding), voice processing, and PDF input processing, while practicing core features used directly in the field step-by-step, such as Function Calling, Structured Outputs (Pydantic), Embedding, and RAG (File Search). Additionally, including Web Search, Code Interpreter, Streaming, Background tasks, and Conversation State management, you'll learn how to expand beyond simple API calls to 'intelligent AI services'. Finally, the goal is to implement agent-based AI systems that autonomously select and execute tools using the Agents SDK and MCP (Model Context Protocol), while learning the structure and design perspectives necessary for actual service development.

Currently, Android development can be done using both Java and Kotlin. You can develop the same Android applications regardless of which language you choose. This course covers most aspects of Android application development, from basics to advanced topics, and all code is written using Kotlin starting from the fundamentals. Additionally, it utilizes Google's latest UI library, Material 3. This course involves completing three projects throughout the entire Android curriculum. By working on these projects, you can master advanced techniques actually used in the industry, such as Hilt, Retrofit, Room Database, and MVVM. Furthermore, you can increase productivity using AI by performing "vibe coding" with Gemini within the Android development tools. Soft Campus will always strive to provide the most up-to-date lectures.

I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.

This course covers the entire process of designing and implementing generative AI services centered on LangChain 1.0 and LangGraph through step-by-step hands-on practice. Beyond simple LLM calls, you'll directly implement operational AI system architectures that include agent-based architecture, state management, memory, streaming, middleware, and Human-in-the-Loop. Through hands-on practice with document/PDF/web data-based RAG systems, SQL Agent (Chinook DB), tool-calling-based Agents, Supervisor pattern multi-agents, and state machine-based workflows using LangGraph Graph API, you'll build reusable agent pipelines that can be immediately applied in real-world scenarios. Additionally, through structured output (Pydantic-based), agent middleware (Summarization, HITL, Retry, PII protection), and token/step-by-step streaming, you'll complete generative AI applications with the stability, scalability, and controllability required in actual services. 👉 For those who want to accurately understand the internal structure and execution flow of LangChain/LangGraph 👉 For those who want to implement RAG·Agent as a real service structure, not just a "demo" 👉 This is the optimal course for those who need a realistic practical roadmap covering state-based agents, SQL·document automation, and multi-agent orchestration.

Apply the latest trends in generative AI directly to your work! The bible of prompt engineering lectures, containing only the essentials.

AI is no longer a choice, but a matter of survival. Shorten development tasks that used to take 3 days down to 30 minutes; leave repetitive tasks to AI and focus on solving more important problems. Through AI-native development methods that are practical rather than theoretical, we will show you the definitive way to be recognized as an "AI-savvy developer" at your company.

"AI will not replace people. People who master AI will replace those who rely on it." In the era of AI, where creating results has become easier than ever, human thinking and problem-solving skills are becoming even more critical. Jae-sung Kim, a former McKinsey consultant, will guide you step-by-step through advanced problem-solving skills using AI, powerful research strategies, and persuasion techniques to turn your results into reality.

Which AI tool should I learn first? Stop worrying now! - Rated 4.8 by 80 students ⭐️⭐️⭐️⭐️⭐️ - ChatGPT, Claude, Gemini, Genspark, NotebookLM, Gamma, Skywork, Manus, Antigravity, Claude Code, MiriCanvas, Opal, CapCut, and more - Learn the core features of over 15 tools very easily over 20 days. - Through weekly assignments, we provide a course you can "internalize" rather than just "passively listen to." - All-in-one coverage: Prompt Engineering > Image Generation > PPT & Video Creation > Vibe Coding - 4 hours of lecture videos + weekly study materials + assignment certification system

From meeting preparation to writing minutes, AI does it all! The first in our series on using AI Agents for company work!

You can learn everything from basic usage of generative AI to automation and creating customized AI chatbots for practical work applications all in one comprehensive course.

This course is a **practical-focused lecture** that covers how to apply **conversational AI (ChatGPT, etc.)** to actual company work. Beyond simple AI usage methods, it is structured to enable learning of specific cases such as work automation, document creation, idea generation, and data analysis assistance that can be utilized in various departments and job environments. Through this course, learners will master methods to streamline repetitive and time-consuming tasks with AI, and experience smart workflows that collaborate with AI. Additionally, by understanding AI's strengths and limitations, it helps make correct decisions in actual business situations. Upon completing this course, you will be able to utilize conversational AI including ChatGPT as a tool to enhance work productivity, which will serve as an important foundation for securing competitiveness in future work environments.

You can automate repetitive and tedious tasks using GPTs. Even non-developers can automate more complex tasks with GPTs by linking various external automation services!

GPT Lecture, 430K YouTube views! Meet the 2024 renewed online course!

Are your colleagues already working with ChatGPT while you're still doing everything manually? Don't worry! After taking this course, you'll become an AI expert too.

Building a TodoList with Claude + IntelliJ - Complete MCP Mastery Master the workings of MCP by creating a TodoList with Claude and IntelliJ!

We've ambitiously prepared a lecture packed with business plan writing know-how, leveraging ChatGPT, to help even beginners apply for the 2024 Pre-Startup Package.

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

The "How Far Can You Go with ChatGPT?" series: Creating a Stock Auto-Trading Application and Web Investment Reports!

"The resumes and cover letters companies want! Providing all-in-one ChatGPT prompts for fast and effective writing🚀" Increase your chances of getting hired with powerful job-specific keywords and differentiated storytelling!

Is your Excel work complex and time-consuming? Excel, essential for office work [VOD] Discover Excel Functions and Macros (VBA Code) using Chat GPT. It will be a reliable assistant for your Excel work.