TRACK 00 Beginner

Doing Academic Research

학술 연구 수행

Learn how to do all kinds of academic research: papers, projects, capstone design, conference presentations, journal publications.

TRACK 01 Beginner

Foundations of Physical AI

피지컬 AI 기초

Sensors, actuators, and the full AI stack from first principles. No prior ML experience required.

TRACK 02 Intermediate

Edge AI and Embedded Systems

엣지 AI 및 임베디드 시스템

TinyML, RTOS, and real-time inference on constrained hardware. Covers Arduino, ESP32, and Raspberry Pi.

TRACK 03 Advanced

Robotic Systems and Control

로봇 시스템 및 제어

Kinematics, ROS 2, and perception–action loops. Build and program a 4-DOF robot arm from scratch.

TRACK 04 Open

Datasets and Benchmarks

데이터셋 및 벤치마크

Lab-produced open datasets for Physical AI research. All released under CC-BY 4.0.

TRACK 05 Beginner

Arduino: Foundations of Physical Computing

아두이노: 피지컬 컴퓨팅 기초

Learn physical computing with Arduino — from blinking LEDs to sensor integration and motor control. No prior hardware experience required.

TRACK 06 Intermediate

ESP32: IoT and Wireless Physical AI

ESP32: IoT와 무선 피지컬 AI

Build Wi-Fi-enabled sensors, MQTT pipelines, and edge AI applications using the ESP32 microcontroller.

TRACK 07 Advanced

Jetson Nano: GPU-Accelerated Physical AI

Jetson Nano: GPU 가속 피지컬 AI

From JetPack setup to real-time neural inference — run YOLO, segmentation models, and ROS 2 nodes on NVIDIA Jetson Nano.