Fuel Your Passion with High-Tech Specialisations

Course Overview

Embedded System Specialist

Specialisation courses enable engineers to quickly advance their knowledge and skill set with specific technologies. The modules are typically offered along with project-based training to candidates who have successfully completed Embedded System Professional. This helps candidates bring unique value when attending interviews where companies are in search of niche skills for their development projects.

Skill Matrix

VHDL
FPGA Design
Timing Analysis
APSoC
RF Engineering
SDR
AI & ML
Deep Learning
Edge AI
Computer Vision
Python
DSP
FIR and IIR
FFT
PID Control
Smart Objects
IIoT
MQTT
CoAP
Modbus
RTOS
RISC-V

Specialisations

  • Overview of VHDL
  • Basic Concepts
  • RTL Design Methodology
  • Finite State Machines (FSM)
  • Testbenches
  • VHDL Coding Guidelines
  • Synthesis & simulation guidelines
  • FPGA Architecture
  • Basic Components of FPGA (LUT, CLB, Switch Matrix, IOB),
  • Resources available
  • FPGA Design Flow
  • Xilinx tool Flow
  • Reading Reports
  • IP core usage
  • Pin Planning
  • Global Timing Constraints
  • Debugging methodologies
  • Static Timing Analysis
  • Introduction to static timing analysis & CDC
  • Implementing reset Techniques
  • Clock Domain Crossing
  • Dual Synchronization
  • Optimal FPGA Design
  • HDL Coding Techniques
  • FPGA Design Techniques
  • Synthesis Techniques
  • Implementation Options - Overview
  • Achieving Timing Closure
  • Path Specific Constraints
  • Introduction to Advanced IO Timing
  • Project-Based Learning
  • Introduction to APSoC
  • APSoC vs. Traditional SoC
  • APSoC Design Flow
  • APSoC Architecture - Core Components
  • Peripheral Interfaces - I/O ports, ADC/DAC, UART, SPI, I2C, USB, Ethernet
  • Hardware Description Languages (VHDL / Verilog)
  • Design Entry and Synthesis
  • Timing Analysis and Optimization
  • Software Design for APSoC
  • Operating Systems for APSoC
  • Driver Development
  • Interfacing - GPIO, ADC/DAC, PWM, UART, SPI, I2C, CAN, Ethernet
  • High-Speed Interfaces - PCIe, USB, SATA, HDMI, MIPI
  • Design Verification and Validation
  • Integrated Development Environments (IDEs)
  • Project-Based Learning
  • Introduction to RF Engineering
  • Basic Concepts
  • Transmission Lines
  • Passive Components
  • Active Components
  • RF Circuit Design
  • Antenna Basics
  • Antenna Design
  • Radio Wave Propagation
  • RF System Components
  • RF System Design Considerations
  • RF Simulation and Modeling
  • Microwave Transmission Lines
  • Microwave Components
  • Microwave Network Analysis
  • Overview of Wireless Systems
  • RF Front-End Design
  • Software-defined radio (SDR)
  • Project-Based Learning
  • Overview of Edge AI
  • Fundamentals of Deep Learning
  • Introduction to Edge Computing
  • Edge Computing vs. Cloud Computing
  • Edge Devices and Platforms
  • Machine Learning Frameworks - TensorFlow Lite, PyTorch Mobile
  • Lightweight Machine Learning Models
  • Model Selection for Edge Deployment
  • Data Collection and Preprocessing
  • Data Storage and Management
  • Model Deployment Techniques
  • Inference Optimization
  • Monitoring and Updating Models
  • Computer vision
  • Overview of hardware accelerators: GPUs, TPUs, FPGAs, ASICs
  • Software stacks for edge AI
  • Popular libraries and frameworks: TensorFlow, PyTorch
  • Project-Based Learning
  • Overview of DSP and Control Systems
  • Overview of STM32 Microcontrollers
  • Development Environment Setup
  • Hands-On Lab: Getting Started
  • DSP Concepts - convolution, correlation, FFT
  • STM32 DSP Libraries
  • Signal generation and visualization on STM32
  • Introduction to FIR and IIR filters and designing using GNU Octave/ Scilab
  • FIR and IIR filters implementation using CMSIS-DSP on STM32
  • Open-loop and closed-loop control systems
  • STM32 peripherals for control applications (timers, PWM, ADC, DAC)
  • PID Control Theory
  • Using CMSIS-DSP for PID control implementation
  • Implementing a PID controller on STM32
  • Testing and tuning the PID controller
  • Project-Based Learning
  • What is IIoT
  • IoT Network Architecture and Design
  • Smart Objects - The "Things" in IoT
  • Connecting Smart Objects
  • IP as the IoT Network Layer
  • IIoT system components
  • Communication Technologies
  • Wired and wireless communication protocols
  • Industrial Ethernet, Wi-Fi, Bluetooth, Zigbee
  • LPWAN technologies
  • Application Protocols for IIoT Protocols - MQTT and CoAP
  • Industrial protocols: Modbus, Profinet, BACnet
  • IIoT Gateways and Middleware
  • Role of gateways in IIoT
  • Securing IIoT
  • Data and Analytics for IIoT
  • Project-Based Learning
  • Operating System Basics
  • Toolchain & Cross-Compilation
  • Concurrent Programming and Scheduling Algorithms
  • Scheduling and Interrupt Handling
  • Task Management with POSIX API
  • Inter-Task Synchronization and Communication (IPC)
  • IPC Based on Shared memory & Message queue
  • Network Communication in RTEMS
  • POSIX Sockets API
  • Multicores in Embedded Systems
  • Multicore Concurrency: Issues and Solutions
  • Introduction to RISC-V
  • RISC-V memory map & memory access
  • Development Environment Setup
  • General Purpose Input/Output (GPIO)
  • Clocking and power control
  • Analog-to-Digital Conversion
  • Interrupt Driven applications
  • Timers & PWM
  • Serial Communication Protocols: I2C, SPI & UART
  • Overview of VHDL
  • Basic Concepts
  • VHDL Syntax and Semantics
  • Entity and Architecture
  • Data Types and Operators
  • Signal and Variable
  • Concurrent and Sequential Statements
  • Loops- for loop, while loop
  • Behavioral Modeling
  • Dataflow Modeling
  • Structural Modeling
  • Generics and Configurations
  • Attributes and Attributes Declaration
  • Functions and Procedures
  • Synthesizable VHDL Constructs
  • RTL Design Methodology
  • Finite State Machines (FSM)
  • Testbenches
  • VHDL Coding Guidelines
  • Project-Based Learning
  • Introduction to APSoC
  • APSoC vs. Traditional SoC
  • APSoC Design Flow
  • APSoC Architecture - Core Components
  • Peripheral Interfaces - I/O ports, ADC/DAC, UART, SPI, I2C, USB, Ethernet
  • Hardware Description Languages (VHDL / Verilog)
  • Design Entry and Synthesis
  • Timing Analysis and Optimization
  • Software Design for APSoC
  • Operating Systems for APSoC
  • Driver Development
  • Interfacing - GPIO, ADC/DAC, PWM, UART, SPI, I2C, CAN, Ethernet
  • High-Speed Interfaces - PCIe, USB, SATA, HDMI, MIPI
  • Design Verification and Validation
  • Integrated Development Environments (IDEs)
  • Project-Based Learning
  • Introduction to RF Engineering
  • Basic Concepts
  • Transmission Lines
  • Passive Components
  • Active Components
  • RF Circuit Design
  • Antenna Basics
  • Antenna Design
  • Radio Wave Propagation
  • RF System Components
  • RF System Design Considerations
  • RF Simulation and Modeling
  • Microwave Transmission Lines
  • Microwave Components
  • Microwave Network Analysis
  • Overview of Wireless Systems
  • RF Front-End Design
  • Software-defined radio (SDR)
  • Project-Based Learning
  • Overview of Edge AI
  • Fundamentals of Deep Learning
  • Introduction to Edge Computing
  • Edge Computing vs. Cloud Computing
  • Edge Devices and Platforms
  • Machine Learning Frameworks - TensorFlow Lite, PyTorch Mobile
  • Lightweight Machine Learning Models
  • Model Selection for Edge Deployment
  • Data Collection and Preprocessing
  • Data Storage and Management
  • Model Deployment Techniques
  • Inference Optimization
  • Monitoring and Updating Models
  • Computer vision
  • Overview of hardware accelerators: GPUs, TPUs, FPGAs, ASICs
  • Software stacks for edge AI
  • Popular libraries and frameworks: TensorFlow, PyTorch
  • Project-Based Learning
  • Overview of DSP and Control Systems
  • Overview of STM32 Microcontrollers
  • Development Environment Setup
  • Hands-On Lab: Getting Started
  • DSP Concepts - convolution, correlation, FFT
  • STM32 DSP Libraries
  • Signal generation and visualization on STM32
  • Introduction to FIR and IIR filters and designing using GNU Octave/ Scilab
  • FIR and IIR filters implementation using CMSIS-DSP on STM32
  • Open-loop and closed-loop control systems
  • STM32 peripherals for control applications (timers, PWM, ADC, DAC)
  • PID Control Theory
  • Using CMSIS-DSP for PID control implementation
  • Implementing a PID controller on STM32
  • Testing and tuning the PID controller
  • Project-Based Learning
  • What is IIoT
  • IoT Network Architecture and Design
  • Smart Objects - The "Things" in IoT
  • Connecting Smart Objects
  • IP as the IoT Network Layer
  • IIoT system components
  • Communication Technologies
  • Wired and wireless communication protocols
  • Industrial Ethernet, Wi-Fi, Bluetooth, Zigbee
  • LPWAN technologies
  • Application Protocols for IIoT Protocols - MQTT and CoAP
  • Industrial protocols: Modbus, Profinet, BACnet
  • IIoT Gateways and Middleware
  • Role of gateways in IIoT
  • Securing IIoT
  • Data and Analytics for IIoT
  • Project-Based Learning
  • Operating System Basics
  • Toolchain & Cross-Compilation
  • Concurrent Programming and Scheduling Algorithms
  • Scheduling and Interrupt Handling
  • Task Management with POSIX API
  • Inter-Task Synchronization and Communication (IPC)
  • IPC Based on Shared memory & Message queue
  • Network Communication in RTEMS
  • POSIX Sockets API
  • Multicores in Embedded Systems
  • Multicore Concurrency: Issues and Solutions
  • Introduction to RISC-V
  • RISC-V memory map & memory access
  • Development Environment Setup
  • General Purpose Input/Output (GPIO)
  • Clocking and power control
  • Analog-to-Digital Conversion
  • Interrupt Driven applications
  • Timers & PWM
  • Serial Communication Protocols: I2C, SPI & UART

Platforms & Tools Covered

Xilinx Artix 7
Zynq APSoC
Vivado
Lattice Diamond
TensorFlow
Jupyter Notebook
PyTorch
STM32
DSPIC
STMCube IDE
MPLAB
3 Months (40 hours / week)
Earn Certification

Who should join?

The modules are typically offered to candidates along with project-based training, who have successfully completed Embedded System Professional.

Prerequisite: Embedded System Professional / Embedded System Expert

Frequently Asked Questions

An embedded system is a piece of electronic hardware that typically carries out a specific task with the help of software running on it. Whether it's the attractive dashboard in a modern car, a satellite navigation system, the autopilot of an aircraft, a smart TV, or your smartphone, all these technological advancements are powered by meticulously crafted software supported by electronic hardware. With the increasing demand for smart and connected devices, the role of embedded systems continues to expand, driving technological advancements.

Yes, Embedded Systems is a great career choice for graduates in Computer Science (CS), Information Technology (IT), etc., in addition to those from Electrical and Electronics Engineering (EEE) or Electronics and Communication Engineering (ECE). Adequate training in basic electronics will bridge any knowledge gaps. Coding skills are complementary, making the learning curve ideal.

We provide comprehensive placement assistance for up to one year after course completion. This includes resume preparation, conducting mock tests and interviews, and arranging interviews with reputed organizations offering opportunities in the core embedded domain. Over our decade-long stint, 98% of our students have successfully secured placements upon completing the course.

Embedded System Professional is designed for BE/BTech graduates (ECE, EEE, CSE, IT, etc.) who have a passion for electronics and programming. However, Embedded System Professional is also suitable for BSc/MSc graduates (Electronics or Computer), though it requires more effort and dedication to build the necessary skills. Ultimately, success depends on the capability and passion of the student, regardless of their academic background.

Nearly 80% of OS-based embedded systems are powered by Linux, and this trend continues to grow. Its open-source nature and extensive hardware compatibility make it ideal for embedded and multimedia applications. The dominance of Linux in embedded systems is increasing, and even Android kernel is based on an upstream Linux kernel.

This training will build the skills necessary to take on the role of an embedded software engineer in diverse domains such as automotive, aerospace, defense, space, consumer electronics, healthcare, and industrial sectors. Embedded systems play a crucial role in these industries, driving innovation and technological advancement.

We offer both online and classroom options for our training programmes, but we recommend a hybrid model with 80% classroom-based and 20% online learning. For embedded systems training, we believe that a purely online approach may not be optimal, especially for beginners.

Yes, typically students can enroll in the programmes without paying the fee upfront. They are free to attend classes for a period of two weeks and make the payment if they decide to continue with the training. Moreover, our course structure is modular enough for students to choose modules they're interested in and make payments in installments accordingly.

Yes, the curriculum is entirely designed by industry experts with over 15 years of experience. Nearly 80% of the course consists of hands-on sessions, promoting a 'learning by doing' approach. Industry-standard tools and software are used in all our training programmes to equip students with the most in-demand skills.

We provide a course completion or merit certificate upon finishing the training programmes. Our skill-building programmes are industry-relevant; companies across India trust us to bridge the gap between academia and industry. With a global presence of alumni and over a decade of expertise, we help you gain a competitive advantage.

Embedded System Professional provides foundational knowledge and skills essential for an embedded system engineer. Once placed, you will specialize and adapt to domain-specific technologies. However, our Specialist and Expert training programs offer in-depth coverage of technologies that are domain-agnostic.

Yes, our Embedded System Professional training covers Git. Understanding and using Git is essential for managing code, collaborating with teams, and maintaining projects. We follow the Software Development Life Cycle (SDLC) in our project-based training, where you will have opportunities to work on modules aligned with recommended industry practices.

It's possible if unavoidable. However, it's not preferred since learning embedded systems requires dedication and hard work during the program. It's recommended to spend 2 to 3 hours per day on self-study and assignments, in addition to 4 hours of classroom and practical sessions.

Yes, but courses on IoT, AI, and ML are part of our specialisations and are typically offered to students who successfully complete Embedded System Professional. This helps them secure jobs more easily, as we integrate these specialisations into our project-based assignments.

We conduct specialisations or expert programmes for professionals who are seeking to advance their careers or update their skill set in line with their assignments. These programs are not beginner-friendly and are offered to students who successfully complete Embedded System Professional. These trainings are not frequent, and their scheduling may depend on total enrollments.

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