ECTS
5 credits
Training Structure
College of Sciences
Description
Optimization
- Linear Optimization
- Nonlinear Optimization (gradient method, optimal-step gradient, Lagrange multipliers)
- Optimization Applied to Robotics (Optimal Control Based on Quadratic Programming Under Linear Constraints)
Embedded Systems
- Harvard and Von Neumann Architectures
- Understanding and implementing the main features of a microcontroller
- Selecting and sizing an embedded programming solution based on a specific need
- Programming a Raspberry Pi Board in C
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Optimization
- Linear Optimization
- Nonlinear optimization (gradient descent, Lagrange multipliers)
- Applying Optimization in Robotics (Optimal Control Based on Quadratic Programming Under Linear Constraints)
Embedded Systems
- Harvard & Von Neumann Architectures
- Understanding and Implementation of the Main Functions of a Microcontroller
- Selection and Implementation of an Embedded Programming Solution Tailored to Specific Design Specifications
- C Programming on a Raspberry Pi
Objectives
Optimization Section: By the end of the course, students will be able to properly formulate an optimization problem and propose the most appropriate tools for solving it.
Embedded Systems Section: By the end of the course, students will be able to select and implement an embedded programming solution tailored to a specific need.
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Optimization: By the end of the course, students will know how to formulate an optimization problem and propose the most appropriate tools for solving it.
Embedded Systems: By the end of the course, students will know how to select and implement an embedded programming solution based on the design specifications.
Contact Hours:
Lectures taught: 15 hours
Laboratory Practicals: 27 hours
Mandatory Prerequisites
C programming, linear algebra, mathematical analysis.
Recommended prerequisites*:
Programming in Python.
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C Programming, Linear Algebra, Calculus.
Recommended prerequisites: Python programming.
Additional Information
CM: 3:00 p.m.
Practical Training: 27 hours
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Lectures taught: 15 hours
Laboratory Practicals: 27 hours