Modern GM vehicles require advanced diagnostic systems capable of secure communication, real time analysis, and compliance with OEM regulations. GDS2 is the official platform that replaces legacy tools, enabling structured diagnostics, calibration updates, and integration with connected vehicle ecosystems. Its significance lies in enhancing service governance, ensuring module compatibility, and embedding cybersecurity protocols within diagnostic workflows. This training program presents frameworks, analytical structures, and governance models that define the institutional role of GDS2 in modern automotive service environments.
Analyze the institutional role of GDS2 as a next-generation GM diagnostic system.
Evaluate advanced frameworks for ECU communication and encrypted data exchange.
Classify models of calibration, reprogramming, and multi-module integration.
Interpret diagnostic datasets through structured analytics and predictive fault modeling.
Examine governance strategies linking GDS2 with cybersecurity, compliance, and connected vehicle management.
Senior automotive diagnostic professionals.
ECU calibration and software integration specialists.
Technical compliance officers in OEM workshops.
Fleet service and operations managers.
Automotive IT and cybersecurity professionals.
Evolution of diagnostic ecosystems from legacy tools to GDS2.
Institutional role of GDS2 in modern GM vehicle service.
Core architecture of the GDS2 platform and its functional modules.
Governance of licensing, subscription, and update cycles.
Integration of GDS2 with OEM compliance standards.
Advanced protocols including CAN, GMLAN, and Ethernet in GDS2.
Frameworks for encrypted ECU-to-ECU communication.
Secure authentication and session management structures.
Governance of data integrity in module networking.
Standards for global diagnostic communication.
Models of ECU calibration and firmware update workflows.
Institutional integration with SPS for secure file distribution.
Structures supporting multi-module programming and synchronization.
Governance of adaptive resets and reconfiguration procedures.
Compliance alignment with J2534 pass-thru and SAE standards.
Structured interpretation of Diagnostic Trouble Codes (DTCs).
Models for analyzing freeze-frame, snapshot, and streaming data.
Institutional frameworks for detecting intermittent and predictive faults.
Role of big data and analytics in advanced fault management.
Governance of diagnostic records and institutional traceability.
Institutional role of cybersecurity in modern diagnostics.
Governance frameworks for subscription and license security.
Structures for remote updates and secure reprogramming workflows.
Integration of GDS2 with connected vehicle platforms.
Institutional outlook on AI driven diagnostics and future service models.