Beginner
CAN & CAN-FD Fundamentals
Frame formats, arbitration, bit-timing, error handling, and DBC authoring with CANalyzer / CANoe.
Training
Automotive Automation & AI Tools Training
Two structured tracks for automotive engineers — master the Automation Domain (CAN, UDS, DoIP, CAPL, HIL) and apply modern AI Tools (LLMs, RAG, Agents) to accelerate validation and the ASPICE V-cycle.
Track 01
Automation Domain Training Topics
Core automotive automation skills — protocols, tooling, and bench validation.
Intermediate
UDS (ISO 14229) Diagnostics
Service IDs, sub-functions, sessions, security access, routine control, and diagnostic sequences.
Intermediate
DoIP & Ethernet Diagnostics
ISO 13400 stack, vehicle identification, TCP/UDP transport, and gateway routing for service-oriented diagnostics.
Beginner
OBD-II & KWP2000 Legacy
Mode/PID structure, freeze-frame data, KWP2000 service set, and legacy ECU compatibility testing.
Intermediate
CAPL Scripting (Vector CANoe)
Event handlers, message manipulation, simulation nodes, test modules, and XML test reports.
Intermediate
Python-CAN & python-uds
Build automation harnesses with python-can, isotp, and udsoncan for CI-driven ECU validation.
Advanced
HIL / SIL / MIL Test Benches
dSPACE, NI VeriStand, and Vector VT System workflows — model-in-loop to hardware-in-loop validation.
Advanced
AUTOSAR Classic & Adaptive
BSW configuration, RTE generation, ARXML, and Adaptive AUTOSAR services for SDV architectures.
Advanced
ASPICE & Functional Safety
ASPICE V-cycle process areas (SYS.1–SWE.6), ISO 26262 ASIL decomposition, and traceability practices.
Track 02
AI Tools Training Topics
Apply LLMs, RAG, and agentic AI to real automotive engineering workflows.
Beginner
LLM Foundations for Engineers
Prompt design, context windows, function calling, and choosing models (GPT-5, Gemini 2.5, Claude) for automotive use cases.
Intermediate
RAG over Engineering Specs
Embed and retrieve from DOORS / Polarion / PDF specs using pgvector, LangChain, and reranking pipelines.
Advanced
AI Agents & Tool Use
Build multi-step agents with LangGraph & MCP — wire LLMs to CAN tools, diagnostic stacks, and ALM systems.
Intermediate
AI for Requirement Analysis
Automate INCOSE quality scoring, ambiguity detection, and requirement-to-test traceability with LLMs.
Intermediate
AI Test Case Generation
Generate functional, boundary, and negative cases from specs using prompt chains, EP/BVA, and pairwise tools.
Advanced
AI Test Script Conversion
Migrate legacy CAPL / TestStand scripts to Python or Robot Framework using LLM-assisted refactoring.
Advanced
Vision & ADAS Scenario AI
Synthesize edge-case driving scenarios with CARLA + diffusion models for ADAS validation coverage.
Beginner
Lovable AI Gateway in Practice
Build production AI features without managing API keys — streaming, structured output, and model routing.
Advanced
AI Defect Triage & RCA
Cluster duplicate defects, predict severity, and generate root-cause hypotheses from logs and CAN traces.