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PROUD GOLD PARTNER OF NASDAQ-LISTED iLEARNlNGENGlNES (TICKER: AILE)
Providing cutting-edge AI solutions in Healthcare | Education | Insurance | Retail | Oil & Gas
To learn more about iLE Solutions
GOLD PARTNER
PROUD GOLD PARTNER OF NASDAQ-LISTED iLEARNlNGENGlNES (TICKER: AILE)
Providing cutting-edge AI solutions in Healthcare | Education | Insurance | Retail | Oil & Gas
To learn more about iLE Solutions
International Professional Program in IoT, AIoT and Embedded AI, and 5G
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Objective
The International Professional Program is a 6-month an intensive and workforce development-oriented hands-on training led by German experts from IICT GmbH, designed to transform learners into global-ready professionals in IoT, AIoT, Embedded AI, and 5G communication technologies. The program is structured into two phases: 3 months of intensive, hands-on training followed by 3 months of guided project execution or internship at Vedhik -IICT CoE. Participants engage with advanced tools, virtual and hardware labs, and real-world project scenarios—ranging from programming IoT, embedded AI and 5G devices, system integration to wireless sensors and 5G network analysis and cloud-based AI applications development. By the end of the program, learners will be equipped with cutting-edge technical competencies and a strong project portfolio aligned with global industry needs.
How Will We Train You to Become an International Professional?
The International Professional Program is structured into two phases—3 months of hands-on training followed by 3 months of project execution or internship at CoE. Designed and led by German experts, the program builds deep technical skills and real-world experience in IoT, AIoT, Embedded AI, and 5G technologies through IICT’s proven, industry-aligned training methodology.
Phase 1 (3 Months): Hands-on Training Labs
- Level 1: Foundational Labs – Learn the Technology
- Build a strong foundation in IoT, AIoT, Embedded AI, and 5G technologies.
- Use IICT’s pre-configured virtual labs to understand full-stack systems—from sensor interfacing to data visualization and cloud integration.
- Level 2: Applied Labs – Practice and Build
- Engage in guided lab exercises using CoE’s physical and virtual labs and testbed environments.
- Work hands-on with industry-grade hardware, embedded stacks, communication protocols, and Edge AI platforms.
Hands on training Delivery (Hybrid Model)
- Onboarding physical workshop sessions with German Experts
- Followed by Flexible Blended Learning: Instructor led sessions at CoE + Live online sessions + self-paced virtual labs + onsite hardware-based labs
- IICT Certified Trainers and applications available throughout for training and support at CoE
Phase 2 (3 Months): Project Execution & Internship at CoE
- Level 3: Hands on Project Execution – Apply and Innovate
- Apply your learning to real-world use cases development through structured project execution.
- Start with example projects across three specialized tracks and develop further project with expert mentoring:
- IoT Track: MIOTY-based Environmental Monitoring System
- AIoT / Embedded AI Track: Intelligent Edge Device for Predictive Maintenance
- 5G/6G Track: Real-Time 5G Drone Surveillance and Video Streaming
- Collaborate in teams to build and extend one selected track project into a major final year, thesis-level or capstone project for professional development.
- Projects are executed with support from IICT-certified trainers at the CoE and mentored remotely by German experts.
- Participants receive guidance on how to publish, present, or extend their project work for academic or industry applications.
What Will You Learn? - Curriculum Overview
1. IoT : Programming End to End wireless and Industrial IoT systems
Module 1 - Introduction to the Hands-on Lab and Tools (Level 1: Foundational Labs)
Onboarding to technologies and hands-on lab setup and tools, including cloning and installing virtual machines, basic Linux command line and system monitoring. Hands-on practice with version control using Git, covering workflows and command-line usage. Recap of Python basics focused on handling various data types and hands-on practice in automation, debugging, and simple programming tasks.
Duration: 10 Hours
Module 2 - Programming and Configuring Embedded Systems for Wireless IoT (Level 1: Foundational Labs)
Learn about microcontrollers for IoT, basics of embedded systems programming in C, configuring hardware with bitmasks and registers, setting up development tools, and building simple applications using STM32 libraries and emulators.
Duration: 10 Hours
Module 3 - IoT Sensor Integration and Programming Microcontrollers (Level 2: Applied Labs)
Understand interfacing microcontrollers with other systems such as sensors and actuators using the popular protocols I2C and SPI. Gain knowledge of the various toolchains, Integrated Development Environments (IDEs), and development workflows used for programming microcontrollers and be able to setup an IDE and toolchain. Understand how to use the Hardware Abstraction Layer (HAL) to develop microcontroller applications.
Duration: 10 Hours
Module 4 - Transmitting Wireless IoT Data and MIOTY Technology based Application Programming (Level 2: Applied Labs)
Understand wireless and LPWAN networks, MIOTY technology and standards, configuring and testing serial communication with embedded stacks, and hands-on data logging and visualization for IoT applications.
Duration: 10 Hours
Module 5 - IoT data Performance Visualization, Data Persistence and integration with Cloud Platforms (Level 2: Applied Labs)
Understand data persistence methods and tools, practical querying of databases like SQLite and InfluxDB, real-time data visualization and anomaly detection techniques, and effective logging strategies including Python logging and Linux log rotation with visualization using Loki and Grafana.
Duration: 10 Hours
Module 6 - MIOTYSense: Smart Environmental Monitoring Over Wireless IoT (Level 3: Hands on Project Execution)
In this project, participants will design and implement a wireless environmental monitoring system using MIOTY technology. They will integrate sensors with embedded microcontrollers to collect environmental data and transmit it reliably over long-range LPWAN networks. The project emphasizes low-power communication, data logging, and visualization—preparing learners for real-world IoT deployment scenarios.
Duration: 20 Hours
2. AI: Artificial Intelligence of Things (AIoT) and Embedded AI
Module 1 - Introduction to AIoT and Edge Intelligence (Level 1: Foundational Labs)
Explore the intersection of AI and IoT through real-world use cases. Understand Edge AI, TinyML, and cloud-based AI, along with key AI concepts and the IoT system stack. Get hands-on with AI tools, model training/testing, emulated data collection, and MQTT-based data transmission.
Duration: 10 Hours
Module 2 - Fundamentals of AI and ML for Embedded Systems (Level 1: Foundational Labs)
Understand how machine learning differs from traditional algorithms and digital signal processing. Introduces key ML concepts like classification, regression, supervised learning, and feature extraction. You’ll also explore model optimization techniques such as quantization and get hands-on with tools like TFLite and CMSIS-NN. Labs including training models using Edge Impulse, Google Colab, and deploying them with ST Edge AI.
Duration: 10 Hours
Module 3 - Sensor Data Collection and Training (Level 2: Applied Labs)
Get familiar with embedded toolchains and how to interface with common sensors like IMUs and microphones. Learn to read sensor datasheets, understand Edge Impulse’s pipeline, and label data for training. Hands-on experience with STM32 HAL and ESP32 programming I2C and SPI sensors, and log data using UART.
Duration: 10 Hours
Module 4 - Deploying and Testing AI on Microcontrollers (Level 2: Applied Labs)
Learn how to convert models to TFLite format, optimize memory usage and inference speed, manage static buffers, and leverage hardware acceleration. Hands-on experience converting models to TFLite and performing live tests to measure and compare their performance and efficiency.
Duration: 10 Hours
Module 5 - Wireless Communication and Low-Power AIoT Design (Level 2: Applied Labs)
Wireless communication basics with focus on low-power technologies like LPWA and BLE. Understand protocol differences, data aggregation methods, and low-power strategies such as peripheral shutdown, clock management, timer wakeups, and deep sleep modes. Energy profiling and the fundamentals of energy harvesting and ultra-low-power processors. Hands-on activities include LPWA transmissions, MQTT messaging with NodeRED, and implementing deep sleep wakeups on STM devices.
Duration: 10 Hours
Module 6 - SmartSense: AI-Powered Edge Device for Real-Time Monitoring and Control (Level 3: Hands on Project Execution)
In this project, participants will build an Intelligent Edge Device that brings AI directly to embedded systems for real-time decision-making. They will design and implement smart applications such as predictive maintenance, gesture control using IMU sensors, and fall detection, combining edge intelligence with robust embedded programming. Alongside technical development, learners will apply best practices in project planning, version control, UML modeling, and secure communication—equipping them to deliver AI-powered solutions for real-world challenges.
Duration: 20 Hours
3. 5G technology: Programing and usecases development
Module 1 - Deep dive into 5G technologies and infrastructure setup for 5G public and private networks (Level 1: Foundational Labs)
Hands on experience with setting up and managing 5G core network components, configuring network functions using tools like Open5GS, managing Linux services, work with REST APIs based on 5G specifications to enable service communication and hands-on tasks with SIM card features – providing a clear understanding of 5G core functions.
Duration: 10 Hours
Module 2 - Configuration and Programming of 5G End Devices (Level 1: Foundational Labs)
Understand different modem types and hardware interfaces such as PCIe, M.2, USB, and Ethernet; learn serial communication and use AT commands for modem configuration; gain practical experience with real modems and emulators like UERANSIM to simulate 5G device setup and network registration.
Duration: 10 Hours
Module 3 - 5G Network Signaling and KPI Analysis (Level 2: Applied Labs)
Hands-on experience with 5G signaling protocols using tools like Wireshark and CMX500. Learn to measure key performance indicators and visualize network coverage and performance metrics on maps using GNSS data and Folium.
Duration: 10 Hours
Module 4 - Data Communication and Protocols in 5G (Level 2: Applied Labs)
Understand data communication protocols like UDP and TCP, practical client-server programming, packet analysis using tools like Scapy, deployment of HTTP servers using Docker containers, and an introduction to 5G user plane protocols (GTP-U) with hands-on data session configuration and network communication troubleshooting.
Duration: 10 Hours
Module 5 - 5G Network Interfaces and Configuration in Linux (Level 2: Applied Labs)
Understand modem driver management and kernel event monitoring, advanced Linux networking tools including virtual interfaces and network namespaces, network performance testing with tools like ping and iperf3, and Python-based implementation for network testing, data logging, and visualization.
Duration: 10 Hours
Module 6 - NetScope 5G: Exploring and Analyzing 5G cell deployments (Level 3: Hands on Project Execution)
Students build a diagnostic tool that uses a public SIM + 5G modem to scan available networks, their configuration and performance. Using tools like AT commands, ping, iperf3, python, databases and grafana, learners will implement a network assessment tool to characterize 5G networks. Results are stored in databases, visualized on maps and dashboards to assess the network environment. This hands-on experience builds expertise in modem configuration, network and data analysis and builds strength in network planning.
What You’ll Walk Away With
By the end of the program, participants will be able to:
- Set up and operate embedded, AIoT, and 5G/6G virtual and hardware-based environments using professional-grade tools and platforms.
- Program and configure microcontrollers, wireless IoT, Embedded AI devices, and integrate sensor systems across diverse protocols (I2C, SPI, UART).
- Implement and evaluate wireless communication technologies, including 5G, MIOTY, and LoRaWAN modems for real-world IoT applications.
- Design, train, and deploy AI/ML models for edge devices using platforms like Edge Impulse and TensorFlow Lite.
- Build intelligent systems that collect, process, and visualize real-time data from distributed sensor networks to IoT Dashboards.
- Troubleshoot and optimize wireless networks through 5G signaling analysis, KPI evaluation, and Linux-based diagnostic tools.
- Develop and test full-stack applications with secure communication, data persistence, and cloud/edge interfacing.
- Execute and present complete industry-aligned projects suitable for academic thesis, research showcases, and entry level industrial jobs and working internships globally with expert mentoring.
Where This Can Take You?
When you finish, you can apply for roles like:
- IoT Systems Developer
- IoT Protocol Stack Developer/Tester
- Wireless Communication Engineer
- Embedded Software Engineer
- 5G Network Engineer and Planner
- Telecom Test and Measurement Engineer
- 5G and Wireless IoT System Engineer
- Cloud Integration Specialist (IoT/ Telco Cloud)
- Technical Sales Engineer (5G/IoT/ Embedded AI)
Top companies hiring Full Stack Developers!
and many more.
Salary Expectations
In India
- Freshers can expect between ₹3 to ₹8 lakhs per year, depending on skills and company
Experienced professionals can earn ₹12+ lakhs/year and more.
In Germany and Europe
Entry-level salaries start from EUR 48,000 per year and can grow quickly to EUR 60,000+ with experience.
Ready to Build Your Dream Career?
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