Future Skill Unlock: An Introduction to Large Model Development on io.net

The “Vibe Coding” paradigm of tools like Cursor has left many developers disoriented, while the explosive growth of large models has caused students to feel uncertain about their future. If there’s one thing to do right now to alleviate this anxiety, learning large model development is undoubtedly an excellent choice. IO.net provides an ideal learning environment for this purpose.

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Our course centers on io.net services, teaching the foundational knowledge of large model development.

io.net offers relatively affordable GPU development resources and comprehensive technical stack support for large models, covering everything from basic inference services to RAG and Agents, as well as fundamental resources like VMs, Docker, and Ray. Unlike large model providers such as OpenAI, io.net primarily offers a service ecosystem based on open-source large models, making it highly suitable for learning, development, and even small-to-medium scale large model projects.

Here, we present a relatively complete course focused on io.net’s large model services.

Course Overview This course focuses on io.net services, using simple examples to explain the usage of specific services. It covers basic large model inference, RAG, Agents, and cloud-related resources such as VMs and containers.

Course Video Link: https://www.ioai.study/products/courses/ai-placeholder Course GitHub: https://github.com/maris205/learn_io_ai io.net Developer Community: t.me/io_devhub

See the detailed syllabus below.

2. Course Features Simple and practical, designed for immediate application. Learners will quickly master io.net’s large model resources and enter the field of large model development.

Clear & Concise:

Follows the OpenAI SDK style for clarity. Practice-Oriented: Each module includes a minimal runnable example. Hands-On Learning: Free course, fully open-source code, video tutorials, and a Q&A community.

Target Audience:

1. Researchers and students in computer science, electronics, control systems, drones, etc.
2. Individuals in unmanned systems (drones, robotics) seeking to learn large models.

Learning Outcomes:

1. Proficiently use io.net’s large model resources.
2. Quickly enter the field of large model development, grasp foundational knowledge, and understand the industry.
3. Support graduation projects, assignments, and course practices.

3. Course Syllabus 1. io.net Large Model Inference Services 1.1 io.net Intelligence Inference API 1.2 Multimodal Large Model Services 1.3 Integrating LangChain with io.net

2. io.net Agent Services 2.1 Agent Fundamentals 2.2 Complex Agents

3. io.net RAG 3.1 RAG Fundamentals 3.2 RAG Programming 3.3 Knowledge Graph + RAG 3.4 Building a Knowledge Graph from Scratch

4. io.net Agentic Workflows 4.1 Using Agents on the Web Interface 4.2 Agentic Programming

5. io.net Training Services

6. io.net Cloud Services 6.1 Introduction to io.net Cloud Services 6.2 io.net Virtual Machines 6.3 io.net Containers 6.4 io.net Ray Cluster