Explore the programs and courses offered by Electronics of Embedded Systems
Browse Programs Admission InformationThe Master's program in Electronics of Embedded Systems trains high-level specialists capable of designing, programming, and integrating intelligent embedded systems across various fields.
The curriculum covers four intensive semesters:
Semester 1:
4 Fundamental Units: Microprocessor Systems, Advanced Digital Electronics (FPGA and VHDL), Advanced Signal Processing, Digital Control Systems.
4 Methodological Units: Practical Work on Microprocessor Systems, Practical Work on Advanced Digital Electronics (FPGA and VHDL), Practical Work on Advanced Signal Processing / Digital Control Systems, Practical Work on Embedded C++ Programming.
2 Discovery Units: Wireless Communication, Linux Systems for Embedded Applications.
1 Transversal Unit: Documentary Research and Thesis Design.
Semester 2:
4 Fundamental Units: Processor Architectures for Embedded Systems, Digital Signal Processors (DSPs), Artificial Intelligence in Embedded Systems, Industrial Programmable Logic Controllers (PLCs).
4 Methodological Units: Practical Work on Processor Architectures for Embedded Systems, Practical Work on Digital Signal Processors (DSPs), Practical Work on Artificial Intelligence in Embedded Systems / Industrial PLCs, Practical Work on Python Programming.
2 Discovery Units: Autonomous Energy Systems, Renewable Energy: Photovoltaic Solar Energy.
1 Transversal Unit: Compliance with Standards, Ethics, and Integrity Rules.
Semester 3:
4 Fundamental Units: Real-Time Systems, Embedded Systems, Artificial Vision, Industrial Networks and Communications.
4 Methodological Units: Practical Work on Artificial Vision, Practical Work on Embedded Systems, Practical Work on Industrial Networks and Communications, Studies and Project Implementation.
2 Discovery Units: Information Coding and Security, JAVA 1: UML Design and JAVA (Fundamentals of Object-Oriented Programming)
1 Transversal Unit:Documentary Research and Thesis Design
Semester 4:
Master's Thesis and public defense
Advanced features of microcontrollers and high-level structured programming
VHDL programming and application on FPGA circuits
Advanced design with finite state machines
Random signals and stochastic processes
Spectral analysis by metric methods and adaptive digital filtering
Time-frequency and time-scale analysis
Analysis of sampled systems in the state-space domain
Exploitation of ARM Cortex processors and advanced applications of ARM Cortex processors
Architecture of DSP TMS320C6x, signal processing algorithms on DSP, and advanced DSP memory management techniques
Artificial intelligence and embedded systems
Methods and applications of machine learning and deep learning
Implementation of machine learning and deep learning in embedded systems
Industrial process materialization using PLCs
PLC programming and process visualization
Safety-dedicated programmable logic controllers
Python programming: basic concepts, conditional structures, loops, functions, dictionaries, objects, classes, and file management
Scheduling in classical and real-time operating systems
Real-time multiprocessor scheduling
Memory management and real-time communication
Artificial vision systems: acquisition, filtering, segmentation, detection, and learning
Architecture and programming of embedded systems
Operating systems for embedded and multitasking applications
Development of embedded applications
Digital data transmission: field buses, RS-485 ModBus bus, CAN bus, Profibus, and wireless industrial networks
Project implementation: hardware part (electronics), software part (programming), simulation, and technical report.
Prototyping and Development Platforms:
Use of Raspberry Pi, Arduino, STM32, ESP32, FPGA
Development environments: Arduino IDE, STM32 CubeIDE, Vivado
Hardware and software integration
Signal Processing and AI:
Implementation of AI models on programmable boards, audio and video processing on embedded systems, advanced signal processing on DSP, embedded voice recognition and artificial vision
Energy Management:
Energy consumption management, energy storage and conversion, autonomous and intelligent energy systems
Communicating Systems:
Connected medical devices, sensor-based monitoring systems and IoT, secure communications
Embedded and Real-Time Systems:
Development of real-time and IoT applications, design of embedded systems on FPGA, system-on-chip (SoC) design, advanced ARM architectures, synchronization and multitasking, real-time analysis and scheduling
Industry:
PLC programming, design of industrial sensor networks based on PLCs, monitoring in industrial loops, remote motor control systems
This training is aimed, in order of priority, at holders of a license in:
Electronics (coefficient 1)
Telecommunications (coefficient 0.8)
Biomedical Engineering (coefficient 0.7)
Electromechanical Engineering (coefficient 0.65)
Other Bachelor's degrees in the field of Science and Technology. (coefficient 0.6)
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