Talk to us Student login

Corporate Training

Build practical engineering capability.

Structured programmes, hands-on labs on real boards and toolchains, practical projects and assessment — designed for engineering teams and new graduates.

Browse the five tracks →Discuss a training plan
5learning tracks, fundamentals to advanced
19programmes inside them
3delivery modes · on-site, online, hybrid
Instructor leading an engineering training session
Lab-first deliveryEmbedded Linux · Day 3Yocto build, drivers and OTA on real boards

01 · Training in practice

Practical learning. Hardware labs. Working projects.

Programmes combine short concept sessions, guided bench work on boards and tools, and projects reviewed against the same quality bar we use on live engineering work.

Instructor-led session
Instructor-led sessions Concepts, then practice
Trainee working on an embedded board with an oscilloscope
Hands-on lab benches Real boards and probes
Team reviewing a project result
Project review & assessment Quizzes, labs, capstone
Lab-first

Every concept session is paired with guided bench work.

Real toolchains

The same tools, boards and workflows used on live projects.

Assessed

Quizzes, lab checks and a capstone project with feedback.

Flexible

On-site, online or hybrid delivery, scheduled around your team.

02 · Learning tracks

Five tracks. Each one a ladder from fundamentals to advanced.

Nineteen programmes, grouped into five tracks. Start where your team is, move up the ladder, and open any syllabus in place. Enquire for duration, dates and a plan for your group.

01Automation Software02Embedded, IoT & Industrial03AI & Machine Learning04Software, Cloud & DevOps05Testing, Quality & Security Levels · Foundation Intermediate Advanced Specialist
Track 01 · 4 programmes

Automation Software

From vehicle E/E basics to AUTOSAR, advanced ECU integration and HIL validation.

Designed forGraduate engineers joining automation programmes · teams moving onto AUTOSAR or validation work
Plan this track for a team
Foundation 1.1 · Automation

Automation Fundamentals

Vehicle E/E architecture basics

AUTOSARCAN / CAN-FD
Enrol
Fresher bootcamp 1.2 · Automation

AUTOSAR Freshers Bootcamp

Vehicle ECU software lifecycle and E/E architecture

AUTOSAR Classic conceptsARXML
Enrol
Advanced 1.3 · Automation

Advanced Automation Engineering

Advanced ECU and vehicle E/E architecture

AUTOSARCAN / CAN-FD
Enrol
Specialist 1.4 · Testing

HIL Testing

Hardware-in-the-loop architecture and real-time simulation

HIL test benchesReal-time simulators
Enrol
Track 02 · 4 programmes

Embedded, IoT & Industrial

Firmware and Linux on real boards, then connected devices and factory automation.

Designed forFirmware and device teams · engineers moving into IoT or industrial control
Plan this track for a team
Foundation 2.1 · Embedded

Embedded Systems

MCU/MPU architecture and embedded system fundamentals

Embedded C/C++MCU development boards
Enrol
Intermediate 2.2 · Embedded

Embedded Linux

Embedded Linux architecture and boot flow

LinuxU-Boot
Enrol
Intermediate 2.3 · IoT

IoT & Edge Computing

IoT architecture from device to cloud

MQTTBLE / Wi-Fi / Ethernet / LoRa concepts
Enrol
Specialist 2.4 · Automation

Industrial Automation & Manufacturing

Industrial automation architecture and production systems

PLC conceptsSCADA
Enrol
Track 03 · 4 programmes

AI & Machine Learning

Python first, then machine learning, deep learning and GenAI systems that ship.

Designed forEngineers new to Python and ML · teams building AI features into products
Plan this track for a team
Foundation 3.1 · Software

Python for Engineers

Python syntax, data types and control flow

Python 3VS Code / IDEs
Enrol
Foundation 3.2 · AI & ML

AI & ML with Python

AI and machine-learning workflow fundamentals

PythonNumPy
Enrol
Intermediate 3.3 · AI & ML

AI & Machine Learning

Machine-learning problem formulation and data pipelines

Pythonscikit-learn
Enrol
Advanced 3.4 · AI & ML

Advanced AI & Intelligent Systems

Deep learning and intelligent-system architecture

PythonPyTorch / TensorFlow
Enrol
Track 04 · 4 programmes

Software, Cloud & DevOps

Digital product engineering, cloud foundations, delivery pipelines and MLOps.

Designed forApplication teams · engineers taking on cloud, CI/CD or production-ML responsibilities
Plan this track for a team
Foundation 4.1 · Software

Digital Software Engineering

Digital product lifecycle and requirements

HTML / CSS / JavaScriptREST APIs
Enrol
Foundation 4.2 · Cloud

Cloud Fundamentals

Cloud computing models and shared-responsibility concepts

AWS / Azure / GCP conceptsLinux
Enrol
Intermediate 4.3 · DevOps

DevOps & CI/CD

DevOps culture and software delivery lifecycle

GitCI/CD platforms
Enrol
Advanced 4.4 · AI & ML

AI, Cloud & MLOps

End-to-end AI lifecycle from experiment to production

PythonDocker
Enrol
Track 05 · 3 programmes

Testing, Quality & Security

Structured testing, verification & validation evidence and secure-by-design basics.

Designed forQA and V&V teams · any engineer who signs off a release
Plan this track for a team
Foundation 5.1 · Testing

Software & Application Testing

Software quality fundamentals and test lifecycle

API testing toolsBrowser automation
Enrol
Intermediate 5.2 · Testing

Testing, Verification & Validation

Verification versus validation and quality gates

Requirements traceability toolsTest management platforms
Enrol
Essentials 5.3 · Cybersecurity

Cybersecurity Essentials

Security principles, threat modelling and attack surfaces

TLS / PKI conceptsOWASP concepts
Enrol

03 · Lab & tooling

What trainees actually work with.

Hardware, software and simulation environments used across the programmes — the same stack our engineers use on client delivery.

BoardsSTM32, NXP, TI, Raspberry Pi, Arduino, ESP32, Jetson
DebugJTAG / SWD probes, oscilloscopes, logic analysers, CAN interfaces
VehicleCANoe / CANalyzer-class tools, UDS and OBD-II stacks
AI stackPython, PyTorch, TensorFlow, OpenCV, Jupyter, ONNX
Cloud labsDocker, Kubernetes, GitHub Actions, AWS / Azure sandboxes
SimulationMATLAB / Simulink, Proteus, Gazebo, Wokwi

04 · Training architecture

Learn → practise → validate → apply.

Each programme follows the same arc, so skills transfer to the next project rather than stopping at the certificate.

01
Learn

Short concept sessions with the theory needed for the lab — no more.

02
Practise

Guided bench work on real boards, buses, models and toolchains.

03
Validate

Lab checks, quizzes and a reviewed capstone project.

04
Apply

A plan to use the skills on your team’s next engineering work.

Training enquiry

Plan a programme for your team.

Share the skills you need, the group size and the preferred delivery mode. We will propose a syllabus, duration and schedule.

Discuss a training plan → Academic programmes (AIIE)
Automation Software · 1.1 · Foundation

Automation Fundamentals

Core topics

Vehicle E/E architecture basicsAUTOSAR layering (application, RTE, basic software)In-vehicle networks: CAN, CAN-FD, LIN, EthernetECU diagnostics with UDS

Skills you build

Reading network communication matricesBasic ECU application configurationCAN bus message analysisDiagnostic trouble-code interpretation

Tools & technologies

AUTOSARCAN / CAN-FDVector / CANoe-class toolsUDS diagnostics
Request enrolment
Automation Software · 1.2 · Fresher bootcamp

AUTOSAR Freshers Bootcamp

Core topics

Vehicle ECU software lifecycle and E/E architectureAUTOSAR Classic Platform concepts, layers and responsibilitiesApplication software, RTE and Basic Software interactionSWC interfaces, runnables, ports and communication concepts

Skills you build

Reading AUTOSAR architecture and ECU configurationUnderstanding ARXML-based configuration conceptsTracing signals from application to communication stackBuilding a structured fresher-level AUTOSAR workflow

Tools & technologies

AUTOSAR Classic conceptsARXMLRTE / BSW conceptsCAN / CAN-FDVector / CANoe-class tools
Request enrolment
Automation Software · 1.3 · Advanced

Advanced Automation Engineering

Core topics

Advanced ECU and vehicle E/E architectureAUTOSAR communication and diagnostics conceptsCAN-FD, in-vehicle Ethernet and gateway architecturesVehicle software integration, validation and release flow

Skills you build

System-level ECU analysisCommunication and diagnostic troubleshootingGateway and connected-vehicle architecture analysisIntegration and validation planning

Tools & technologies

AUTOSARCAN / CAN-FDIn-vehicle EthernetUDSCANoe-class tools
Request enrolment
Automation Software · 1.4 · Specialist

HIL Testing

Core topics

Hardware-in-the-loop architecture and real-time simulationPlant, vehicle and ECU model conceptsI/O, ECU interfaces and restbus simulationFault injection and automated test execution

Skills you build

Designing HIL test scenariosConnecting ECU interfaces to a real-time test benchCreating automated regression testsAnalysing test results and failure traces

Tools & technologies

HIL test benchesReal-time simulatorsCAN / CAN-FDRestbus simulationAutomation scripting
Request enrolment
Embedded, IoT & Industrial · 2.1 · Foundation

Embedded Systems

Core topics

MCU/MPU architecture and embedded system fundamentalsEmbedded C/C++ and memory conceptsInterrupts, timers, GPIO, ADC/DAC and communication peripheralsRTOS fundamentals and embedded software architecture

Skills you build

Writing and debugging firmwarePeripheral configuration and driver integrationUsing serial and bus communication for debuggingStructuring reliable embedded applications

Tools & technologies

Embedded C/C++MCU development boardsUART / SPI / I2C / CANRTOS conceptsJTAG/SWD-class debuggers
Request enrolment
Embedded, IoT & Industrial · 2.2 · Intermediate

Embedded Linux

Core topics

Embedded Linux architecture and boot flowU-Boot, Linux kernel and device tree conceptsRoot filesystem, packages and cross-compilationYocto / Buildroot concepts and OTA fundamentals

Skills you build

Building and configuring embedded Linux systemsReading kernel and boot logsWorking with device trees and driversCreating reproducible embedded Linux images

Tools & technologies

LinuxU-BootYoctoBuildrootDevice TreeCross-compilers
Request enrolment
Embedded, IoT & Industrial · 2.3 · Intermediate

IoT & Edge Computing

Core topics

IoT architecture from device to cloudSensors, gateways and edge processingMQTT and device communication conceptsDevice management, telemetry and dashboards

Skills you build

Designing connected-device data flowsConnecting sensors to edge gatewaysWorking with telemetry and messagingBuilding an end-to-end IoT prototype

Tools & technologies

MQTTBLE / Wi-Fi / Ethernet / LoRa conceptsEdge gatewaysREST APIsCloud IoT concepts
Request enrolment
Embedded, IoT & Industrial · 2.4 · Specialist

Industrial Automation & Manufacturing

Core topics

Industrial automation architecture and production systemsPLC programming concepts and control logicSCADA, HMI and industrial data flowSensors, actuators, alarms and manufacturing integration

Skills you build

Developing basic PLC control sequencesReading industrial I/O and process diagramsDesigning HMI/SCADA monitoring conceptsTroubleshooting automation workflows

Tools & technologies

PLC conceptsSCADAHMIIndustrial EthernetModbus / OPC-class interfaces
Request enrolment
AI & Machine Learning · 3.1 · Foundation

Python for Engineers

Core topics

Python syntax, data types and control flowFunctions, modules, packages and object-oriented programmingFiles, JSON/CSV data and exception handlingAutomation, scripting and engineering data processing

Skills you build

Writing reusable engineering scriptsParsing logs and test dataAutomating repetitive validation tasksBuilding small command-line utilities

Tools & technologies

Python 3VS Code / IDEspip / virtual environmentsJSON / CSVpytest basics
Request enrolment
AI & Machine Learning · 3.2 · Foundation

AI & ML with Python

Core topics

AI and machine-learning workflow fundamentalsData preparation, features and supervised learningModel evaluation, overfitting and validationIntroductory neural networks and inference

Skills you build

Preparing datasets for MLTraining and evaluating baseline modelsInterpreting model metricsBuilding small Python-based ML experiments

Tools & technologies

PythonNumPyPandasscikit-learnJupyterMatplotlib
Request enrolment
AI & Machine Learning · 3.3 · Intermediate

AI & Machine Learning

Core topics

Machine-learning problem formulation and data pipelinesRegression, classification and clusteringFeature engineering and model evaluationDeep-learning foundations and practical inference

Skills you build

Selecting suitable ML approachesBuilding training and validation pipelinesComparing models using appropriate metricsPackaging a practical AI prototype

Tools & technologies

Pythonscikit-learnPandasPyTorch / TensorFlow conceptsJupyter
Request enrolment
AI & Machine Learning · 3.4 · Advanced

Advanced AI & Intelligent Systems

Core topics

Deep learning and intelligent-system architectureComputer vision, NLP and multimodal AI conceptsGenerative AI, LLMs, RAG and agent workflowsEdge AI, optimisation, deployment and monitoring

Skills you build

Designing AI system architecturesBuilding retrieval-augmented workflowsEvaluating AI outputs and system behaviourConnecting AI models to real applications and devices

Tools & technologies

PythonPyTorch / TensorFlowLLM APIs / local modelsVector databasesRAG frameworksOpenCV
Request enrolment
Software, Cloud & DevOps · 4.1 · Foundation

Digital Software Engineering

Core topics

Digital product lifecycle and requirementsSystem and software architectureWeb, mobile and API engineering conceptsDatabases, integration, testing and release practices

Skills you build

Breaking requirements into software componentsDesigning APIs and application flowsWorking across frontend/backend boundariesPlanning quality and release checkpoints

Tools & technologies

HTML / CSS / JavaScriptREST APIsSQLGitTesting frameworksCI/CD concepts
Request enrolment
Software, Cloud & DevOps · 4.2 · Foundation

Cloud Fundamentals

Core topics

Cloud computing models and shared-responsibility conceptsCompute, storage, networking and managed servicesIdentity, security, observability and cost basicsCloud application architecture and deployment flow

Skills you build

Mapping applications to cloud servicesDesigning basic cloud architecturesUnderstanding identity and network boundariesDeploying and monitoring a simple cloud workload

Tools & technologies

AWS / Azure / GCP conceptsLinuxContainersCloud CLI conceptsMonitoring dashboards
Request enrolment
Software, Cloud & DevOps · 4.3 · Intermediate

DevOps & CI/CD

Core topics

DevOps culture and software delivery lifecycleSource control, branching and build automationCI/CD pipelines, artifact management and release flowContainers, infrastructure and deployment observability

Skills you build

Designing a basic CI/CD pipelineAutomating builds and testsPackaging applications for deploymentAdding quality and release gates

Tools & technologies

GitCI/CD platformsDockerArtifact repositoriesLinuxInfrastructure-as-code concepts
Request enrolment
Software, Cloud & DevOps · 4.4 · Advanced

AI, Cloud & MLOps

Core topics

End-to-end AI lifecycle from experiment to productionModel packaging, serving and cloud deploymentData/model versioning, pipelines and monitoringMLOps governance, reproducibility and continuous improvement

Skills you build

Designing production-oriented ML pipelinesDeploying model inference servicesMonitoring data and model behaviourConnecting ML workflows with CI/CD practices

Tools & technologies

PythonDockerCloud ML platformsMLflow-class toolingCI/CDMonitoring / observability
Request enrolment
Testing, Quality & Security · 5.1 · Foundation

Software & Application Testing

Core topics

Software quality fundamentals and test lifecycleFunctional, regression, integration and UI testingAPI testing and test-data managementTest automation concepts and defect lifecycle

Skills you build

Creating test cases from requirementsExecuting structured manual testsAutomating repeatable application checksReporting defects with reproducible evidence

Tools & technologies

API testing toolsBrowser automationPostman-class toolsSelenium / Playwright conceptsJira-class defect tracking
Request enrolment
Testing, Quality & Security · 5.2 · Intermediate

Testing, Verification & Validation

Core topics

Verification versus validation and quality gatesRequirements, traceability and test planningUnit, integration, system and acceptance testingCoverage, regression, evidence and release readiness

Skills you build

Building verification strategiesCreating requirement-to-test traceabilityAnalysing test failures and evidencePreparing validation and release reports

Tools & technologies

Requirements traceability toolsTest management platformsCI test executionAutomation frameworksDefect tracking systems
Request enrolment
Testing, Quality & Security · 5.3 · Essentials

Cybersecurity Essentials

Core topics

Security principles, threat modelling and attack surfacesAuthentication, authorisation and secure communicationEncryption, keys, certificates and secretsSecure software and vulnerability-management basics

Skills you build

Identifying common security risksApplying basic secure-design controlsInterpreting vulnerability findingsCreating practical security checklists

Tools & technologies

TLS / PKI conceptsOWASP conceptsVulnerability scannersLinux security toolsGit security practices
Request enrolment