NGI Academy · UpSkill
Training built by the engineers who do the work
At NGI Academy we shape future-ready professionals through advanced programmes in engineering, software, and emerging technologies. Our deep-tech curriculum combines hands-on projects, industry tools, and expert mentorship to deliver real-world skills.
NGI Academy
Empowering innovation through next-generation skills
At NGI Academy we shape future-ready professionals through advanced programmes in engineering, software, and emerging technologies. Our deep-tech curriculum combines hands-on projects, industry tools, and expert mentorship to deliver real-world skills.
Why train with us
- Taught by engineers who ship hardware and software, not by full-time trainers
- Assessed on working output — a running application, a board that can be built
- Access to our own laboratories, instruments, and manufacturing line
Training enquiries
Programme outlines, cohort dates, and corporate training.trainings@nxgeninventors.com+91 89258 58615
Programmes & certifications
What we teach
Module syllabuses below are drafted from current industry curricula and are being confirmed with the academy. Contact us for the definitive outline of any programme.
Engineering
3 modulesSub-modules
- Embedded C & Microcontroller ArchitectureMemory model, registers, interrupts, startup code and the linker script
- RTOS FundamentalsFreeRTOS tasks, scheduling, queues, semaphores and priority inversion
- Peripheral InterfacingGPIO, ADC, timers, PWM, UART, I2C, SPI and sensor bring-up
- Wireless ConnectivityBLE, Wi-Fi, LoRaWAN and NB-IoT — choosing and implementing the link
- IoT Protocols & CloudMQTT, CoAP, HTTP REST, device provisioning and telemetry ingest
- Low-Power DesignSleep modes, duty-cycle measurement and building an energy budget
- Debugging & TestJTAG/SWD, logic analyser, oscilloscope technique and unit testing firmware
- Capstone ProjectA connected sensor node, from schematic through firmware to a live dashboard
What you will be able to do
- Write, debug and profile firmware on a real microcontroller, not a simulator
- Select a wireless stack against duty cycle, range and cost, and justify the choice
- Take a device from breadboard to a dashboard showing its live telemetry
Tools
STM32CubeIDEESP-IDFFreeRTOSNordic nRF ConnectMQTTLogic analyserOscilloscope
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- TinyML FoundationsWhat fits on a microcontroller, and why most published models do not
- Data Collection & LabellingCapturing sensor data from the target device and building a usable dataset
- Model Training for the EdgeCompact architectures for audio, vibration and motion classification
- Quantisation & OptimisationPost-training quantisation, pruning, and the accuracy you trade for it
- TensorFlow Lite for MicrocontrollersModel conversion, the interpreter, and the tensor arena
- Edge VisionPerson and object detection on constrained camera modules
- Anomaly DetectionAutoencoders and statistical baselines for condition monitoring
- Deployment & Field UpdateBenchmarking on target, memory profiling, and over-the-air model update
What you will be able to do
- Convert and deploy a trained model onto a microcontroller and measure it on target
- Hold a stated latency and memory budget through quantisation
- Build an anomaly detector from vibration data captured on real equipment
Tools
TensorFlow Lite MicroEdge ImpulsePythonCMSIS-NNSTM32Cube.AINetron
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- Schematic CaptureSymbol libraries, hierarchical sheets, net naming and electrical rule checks
- Component & Library ManagementFootprint creation to IPC-7351, lifecycle status and second sourcing
- PCB Layout FundamentalsStack-up, placement strategy, routing, copper pours and clearance rules
- Signal & Power IntegrityControlled impedance, return paths, decoupling and plane splits
- High-Speed & RF LayoutLength matching, differential pairs, antenna keep-outs and shielding
- Design for ManufacturePanelisation, fiducials, solder-mask relief and assembly-friendly placement
- Design for TestTest points, boundary scan access and in-circuit test provision
- Output & HandoverGerbers, ODB++, drill files, pick-and-place data and a complete fabrication pack
What you will be able to do
- Produce a manufacturable multi-layer board with a complete fabrication pack
- Pass a DFM and DFT review conducted by our own manufacturing engineers
- Justify a stack-up and impedance decision rather than accepting a default
Tools
Altium DesignerCadence OrCADZuken CADSTARKiCadAutodesk EagleIPC standards
Syllabus drafted from current industry curricula — being confirmed with the academy.
Software
6 modulesSub-modules
- SAP S/4HANA FoundationsArchitecture, Fiori, the data model, and what changed from ECC
- SAP HANAIn-memory modelling, calculation views, CDS views and performance tuning
- ABAP DevelopmentObjects, internal tables, ALV reporting, BAPIs, enhancements and ABAP on HANA
- SAP FICOFinancial accounting and controlling — GL, AP, AR, asset accounting, cost centres
- SAP MMMaterials management — procurement, inventory, valuation and invoice verification
- SAP SDSales and distribution — order to cash, pricing, delivery and billing
- SAP BW/4HANA & Analytics CloudData warehousing, extraction, modelling and reporting on SAP data
- Integration & AutomationOData services, SAP BTP, Integration Suite, and RPA for the manual steps
What you will be able to do
- Work confidently in at least one functional module and one technical discipline
- Build and consume an OData service exposing SAP data to an external application
- Automate a repetitive business process end to end and evidence the time saved
Tools
SAP S/4HANASAP HANA StudioABAP Development ToolsSAP FioriSAP BTPSAP Analytics CloudUiPath
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- Web FoundationsHTML, CSS, accessibility, responsive layout and the browser rendering model
- Modern JavaScript & TypeScriptLanguage fundamentals, async patterns, modules and the type system
- Front-End FrameworksReact and Next.js — components, state, routing and server rendering
- Back-End & APIsNode.js, REST and GraphQL design, validation and error handling
- DatabasesRelational modelling with PostgreSQL, indexing, migrations and query tuning
- Authentication & SecuritySessions, OAuth 2.0, JWT, and the OWASP Top Ten in practice
- Testing & QualityUnit, integration and end-to-end testing; code review and static analysis
- Deployment & CI/CDContainers, pipelines, environment configuration and observability
What you will be able to do
- Ship a deployed, authenticated, tested application built from scratch
- Design a relational schema and defend the indexing decisions behind it
- Work in a code-review culture, giving and receiving review as routine
Tools
TypeScriptReactNext.jsNode.jsPostgreSQLPrismaPlaywrightDockerGitHub Actions
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- Cloud FundamentalsService models, regions, availability zones, and the shared responsibility model
- Amazon Web ServicesEC2, S3, VPC, IAM, RDS, Lambda, CloudFormation and CloudWatch
- Microsoft AzureVirtual Machines, Blob Storage, VNet, Entra ID, App Service and Functions
- Google Cloud PlatformCompute Engine, Cloud Storage, VPC, IAM, BigQuery and Cloud Run
- Identity & Access ManagementLeast privilege, roles, federation and credential lifecycle across providers
- Networking & SecuritySubnets, security groups, private endpoints, encryption and key management
- Serverless & ContainersFunctions, managed Kubernetes, and choosing between them honestly
- Cost Management & ArchitectureRight-sizing, reserved capacity, tagging discipline and well-architected review
What you will be able to do
- Deploy the same workload on all three providers and compare cost and effort
- Design a network and identity model that follows least privilege by default
- Sit an associate-level certification with the syllabus already covered
Tools
AWSMicrosoft AzureGoogle CloudTerraformAWS CLIAzure CLIgcloud
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- Git & Branching StrategyTrunk-based development, review workflow, and resolving real merge conflicts
- CI/CD PipelinesJenkins, GitHub Actions and GitLab CI — build, test, gate and deploy
- ContainersDocker images, layer caching, multi-stage builds and registry hygiene
- KubernetesPods, deployments, services, ingress, config, secrets and Helm
- Infrastructure as CodeTerraform and Ansible — state, modules, drift and safe change
- Monitoring & ObservabilityPrometheus, Grafana, structured logging, tracing and useful alerting
- Security in the PipelineSecret management, dependency and image scanning, and signed artefacts
- Release & Incident PracticeBlue-green and canary releases, rollback, on-call and blameless postmortems
What you will be able to do
- Take an application from commit to production through a pipeline you built
- Describe infrastructure as code and rebuild an environment from scratch
- Run an incident exercise, roll back cleanly, and write the postmortem
Tools
GitDockerKubernetesTerraformAnsibleJenkinsGitHub ActionsPrometheusGrafana
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- Mathematics for MLLinear algebra, probability, statistics and optimisation, applied not abstract
- Classical Machine LearningRegression, trees, ensembles, clustering, and honest cross-validation
- Feature Engineering & EvaluationLeakage, class imbalance, and choosing a metric that matches the decision
- Deep LearningNeural networks, CNNs, RNNs and transformers with PyTorch and TensorFlow
- Computer VisionClassification, detection and segmentation on industrial imagery
- Natural Language & LLMsEmbeddings, retrieval-augmented generation, prompting and tool use
- MLOpsExperiment tracking, model registry, serving, monitoring and retraining
- Responsible AIBias, explainability, data governance and knowing when not to use a model
What you will be able to do
- Frame a business problem as a modelling problem, or correctly reject it as one
- Train, evaluate and deploy a model with a monitored retraining path
- Build a retrieval-augmented application grounded in a document set you control
Tools
PythonPyTorchTensorFlowscikit-learnHugging FaceMLflowPandasJupyter
Syllabus drafted from current industry curricula — being confirmed with the academy.
Sub-modules
- SQL & Data ModellingJoins, window functions, CTEs, indexing and dimensional modelling
- Python for DataPandas, NumPy, and reproducible analysis in notebooks and scripts
- Statistics & InferenceDistributions, hypothesis testing, confidence intervals and A/B analysis
- Data Cleaning & QualityMissing data, outliers, deduplication and building a quality baseline
- Data PipelinesETL and ELT, orchestration with Airflow, and incremental loading
- Visualisation & StorytellingPower BI and Tableau; choosing a chart that answers the actual question
- Business MetricsDefining a metric that cannot be gamed, and reporting it consistently
- Capstone AnalysisAn end-to-end analysis on a real operational dataset, presented and defended
What you will be able to do
- Write SQL against a real schema without waiting for someone to prepare an extract
- Build a pipeline that refreshes a dashboard reliably and unattended
- Present an analysis and defend the method under questioning
Tools
SQLPythonPandasAirflowPower BITableauPostgreSQLExcel
Syllabus drafted from current industry curricula — being confirmed with the academy.
How it runs
Projects first, lectures second
Every module is built around something the learner produces and defends. The theory arrives when it is needed to get the next part working, which is the order in which it actually sticks.
Scope
A brief drawn from live engineering work
Build
Weekly output on real hardware or a real repo
Review
Critiqued by the delivery team, not auto-marked
Certify
A record of what was built, not hours attended
Who it is for
Four routes into the programme
Students and graduatesBridging the gap between a syllabus and a first engineering role
Working professionalsAdding a discipline — SAP, cloud, embedded — to an existing career
Corporate cohortsTeam programmes scoped to a client stack and delivered on site
InstitutionsCurriculum support and laboratory access, through our university programme
Inside the academy
Where the work happens
Ready to start a programme?
Tell us where you are starting from and what you want to be able to build.