Robotics and Artificial Intelligence

General education knowledge: 58 CREDITS

Course	Credits
1. Marxist - Leninist Philosophy	3
Marxist - Leninist Philosophy module provides students with the most general knowledge of development and movement as a scientific basis for evaluating and solving problems arising in life. The module includes the basic contents: dialectical materialism, materialistic dialectism and historical materialism. Dialectic materialism provides learners with a scientific worldview as the basis for a positive and creative attitude to life. Dialectic materialism provides learners with a method of dialectic thinking to correctly recognize and solve problems in life. Historical materialism provides learners with a correct understanding of the existence and social development as well as the scientific methodology to recognize and solve social problems.
2. Marxist - Leninist Political Economics	2
The Marxist - Leninist Political Economy course is used for non-specialized political theory, studying the basic principles of Marxism-Leninism about the production of goods, the market and the role of actors in the economy. market economy. Research produces surplus value in a market economy, associated with it is the problem of capital accumulation and reproduction, along with manifestations of surplus value. The subject also studies competition and monopoly in the market economy. Study of the socialist-oriented market economy and economic interest relations in Vietnam. Study the strategy of industrialization, modernization and international economic integration of Vietnam.
3. Scientific Socialism	2
It is one of three constituent parts of Marxism-Leninism, a compulsory subject in the training program of universities and colleges in the country. The scientific socialism subject (social science) for the undergraduate degree without majoring in political theory equips students with the core content of the following specific issues: The process of formation and development of socialism; Working-class history mission; Socialism and the transition to socialism; Socialist democracy and a socialist state; The social-class structure and class alliances, class in the period of transition to socialism; Ethnic and religious issues in the transition to socialism; The family problem in the transition to socialism. On that basis, it helps students form their thinking, analytical skills, evaluate and identify the nature of socialism and the transition period to socialism in Vietnam, forming a school, Marxist-Leninist ideology, building appropriate social responsibility in employment and post-graduate life.
4. History of Vietnamese Communist Party	2
Equip students with the knowledge of objects, purposes, tasks, research methods, study of Party History and the basic, core, systematic knowledge about the birth of the Party (1920 - 1930), the process of the Party leading the struggle for power (1930 - 1945), leading two resistance wars against French colonialism and the American imperialist invasion, completing national liberation, reunification (1945) - 1975), led the country transitionally to socialism and carried out the reform (1975 - 2018). Thereby affirming the successes, raising the limitations, summarizing the experiences of the revolutionary leadership of the Party to help learners raise awareness, belief in the Party and the ability to apply the learned knowledge. into practical work, contributing to building and defending the Socialist Vietnam Fatherland.
5. Ho Chi Minh’s Ideology	2
The Ho Chi Minh Thought module consists of 6 chapters, providing students with basic knowledge of: Objects, research methods, meaning of learning subjects. ; on the basis, process of formation and development of Ho Chi Minh's thought; Ho Chi Minh's basic ideas about national independence and socialism, the Communist Party of Vietnam, about national solidarity and international solidarity, culture, morality and people.
6. General Business English	4
General Business English helps students: - Develop English language skills on the topics and contexts of work and business environments. - Have general knowledge of many fields such as careers, companies, selling, great ideas and stress. - Equip knowledge and skills to take the test for the international certificate of business communication English (TOEIC), contributing to achieving English output standards at level B1 (according to the European Framework of Reference, CFER).
7. English for Technology, Communication and Design 1	3
This module aims to enhance students' comprehension of academic language and literacy practices within the field of Technology, Communication and Design. The design of the module facilitates the integration of language learning with key content areas, enabling students to develop a profound understanding of how language functions in communicating subject matter. Consequently, students will be able to acquire essential language skills relevant to the field of Technology, Communication and Design. Students actively foster their learning experience through engaging in diverse learning activities such as case studies, role-plays, simulations, presentations, and group discussions.
8. English for Technology, Communication and Design 2	3
The principal aim of this module is to enhance students' cognitive mastery of the intricate interplay between academic language and the specialized discourse conventions within the field of Technology, Communication and Design. The structural framework of the module strategically facilitates the integration of linguistic acquisition with the foundational subject matter, thereby endowing students with the capacity to cultivate a profound comprehension of the nuanced role of language in the dissemination of specialized knowledge. Consequently, students will acquire and develop essential language competencies that are intrinsically pertinent to the field of Technology, Communication and Design. Students will be involved in various interesting activities like studying real cases, acting out scenarios, doing simulations, giving presentations, and having group discussions to make their learning experience exciting and valuable.
9. Introduction to Psychology	2
The objective of the field of psychology is to understand how the mind and brain interact with the external world to shape behavior. This course is designed to be an introduction to the science of psychology, which focuses mainly on the study of mind, emotion and behavior in humans. The course will provide basic knowledge that helps students build foundations in psychology. Furthermore, students will also understand how the knowledge of psychology is applied in management, economics, marketing, consumer behavior, technology management, and other fields. The contents of this course will include 3 modules: (1) Module 1: Introduction to psychology, (2) Module 2: psychological processes and behaviors, (3) Module 3: Correcting individual and social behaviors.
10. Sustainable Development	2
The course "Sustainable Development" introduces students to the key principles, concepts, and challenges of sustainable development with a focus on the context of Vietnam. As a rapidly developing nation, Vietnam faces complex social, economic, and environmental issues that require sustainable solutions. This undergraduate-level course aims to equip students with a comprehensive understanding of sustainable development theory, its application, and the role of various stakeholders in achieving sustainable outcomes. Studying "Sustainable Development" is essential for students to develop a holistic understanding of the challenges facing the world and to equip themselves with the knowledge and skills needed to contribute positively to a sustainable and equitable future. The course fosters critical thinking, global awareness, and responsible citizenship while providing a pathway to meaningful and impactful careers in a world that increasingly values sustainability.
11. Design Thinking	2
Design thinking is a problem-solving method that puts the user at the center of the process. It provides a dynamic framework for approaching idea formation, creative exploration, and divergent thinking. The Design Thinking course provides knowledge of principles, tools, and methods that promote creative thinking, such as Empathy Map, Persona/ User profile, Journey Mapping, How might we …?, Value Chain Analysis, Brainstorming, Mind Mapping, Story Telling, Problem Statement, Concept Development, Assumption Testing, Rapid Prototyping, Customer Co-Creation, Prototype to test, Experience Testing, Learning Launch….. Students will learn purposeful use of tools and alignment with process to solve real-world situations. They will develop skills in teamwork, critical thinking, presenting and expressing ideas. Students will learn how to communicate effectively, give and receive feedback, respect the ideas and perspectives of others.
12. Entrepreneurship	1
The course will build on cross-curricular academic skills, by integrating inquiry-based learning and business tools that will enable students to analyze, create, develop and pilot small businesses. Concepts and skills are reinforced by a strong emphasis on hands-on experiences. Applications to society, individuals, and the utilization of technology are included.
13. Soft Skills	2
Soft skills course generates the foundation knowledge of soft skills, applicable to the workplace environment. The goal of learning is to combine the major knowledge with content and implementation of core soft skills techniques, giving students more effective access to the work environment after graduation. The core soft skills include Critical thinking; Problem-solving skills; Adaptability to the working environment; Effective communication and presentation skills; Service Oriented, Self-positioning skills, Feedback and Coaching.
14. Mathematical Statistics	3
Statistics for Economics and Business course provides in a systematic way statistical methods including gathering data on economic; business phenomena and processing collected data into useful information which are used as facts for making decisions for the management of the economy and society. These methods include descriptive statistics, statistical inference, index-number, forecasting ... To introduce students to popular and easy to use packages as a tool to support statistical treatments to save time, effort and increase the accuracy of the results, helping students familiar with outputs from the packages.
15. Advanced Mathematics 1	3
Advanced Mathematics provides basic knowledge about limits, continuity, and calculus of functions of one variable, series of numbers, series of functions, calculus of multivariable functions including multiple integrals of 2 (double integral), triple integral, line integral, surface integral, and the basics of differential equations.
16. Advanced Mathematics 2	3
This course covers the knowledge of matrices, determinants, systems of linear equations, vector spaces, Euclidean spaces, matrix diagonalization, quadratic form and differential calculus of multivariable functions, and vector fields.
17. Physics 1	3
This module provides students with the basics of physics, including parts of mechanics and thermodynamics, as a basis for accessing specialized university-level subjects in the sciences, engineering, and engineering. turmeric. Students will be equipped with the knowledge of physics to investigate motion, energy, and physical phenomena related to objects in nature ranging in size from molecules to planets. After completing the course, students will be able to apply the knowledge they have learned in scientific research as well as in the development of modern engineering and technology.
18. Physics 2	3
This module provides students with the basic content of physics including electromagnetics and optics as the basis for access to specialized university-level subjects in the sciences, engineering, and technology. Students will be equipped with knowledge about phenomena in the natural world and apply that knowledge in scientific research, technical development, and modern technology.
19. Physics Lab	1
Physics lab 1 consists of a unit with 9 experiments on kinematics, particle dynamics, solid body dynamics and thermodynamics. This is a supplementary course for students of college and university technology majors with knowledge about the nature of physical phenomena occurring in nature, to re-examine the physical theories learned in this chapter. The program aims to train future engineers skills in observing, conducting experiments, measuring and calculating, analyzing and processing data.
20. Mathematics for Engineers (EN)	3
The course provides students with an introductory theory of Numerical Calculus and Laplace transforms, and Fourier transforms, recognizing the optimal problem type and providing suitable methods. In addition, the module provides students with skills to apply advanced math knowledge in computational practice in their major.
21. Industrial Fine Art	2
The module equips students of Robotics and Artificial Intelligence with basic knowledge about two- and three-dimensional shaping in industrial art design. The core content of the course is the visual language on the plane and on the block. Provides knowledge of the properties of shapes and methods of construction of shapes as well as the nature of the design and product of industrial design. On that scientific basis, it helps students to apply knowledge in designing industrial products, products that are useful and are the result of the creative process, mass production and have aesthetic value. In addition, students are trained in hand-drawing and model-making skills.
22. Science, Technology and Intellectual Property Law	1
In the knowledge economy, scientific and technological activities, innovation and intellectual products play a key role in national development. According to statistics in 2020, intellectual property accounts for more than 80% of the total value of businesses in the S&P 500 portfolio. The Law on Science and Technology and the Law on Intellectual Property comprehensively institutionalize the policies of the Party and State policies on developing science and technology and innovation to serve the cause of industrialization, modernization of the socialist-oriented market economy and international integration. Therefore, this module focuses on providing students with basic concepts and knowledge about science, technology and innovation activities, regulations on promotion, application and commercialization of products. S&T products serve life and national development; types of intellectual property and intellectual property rights; regulations on copyright, rights related to copyright, industrial property rights, plant variety rights and the protection of those rights; Thereby, students clearly understand legal knowledge about science and technology activities and intellectual property and know how to apply them to the operation, management and development of science and technology activities as well as protection. and effectively exploit intellectual property.
23. Engineering Economics	3
The course aims to provide basic concepts related to economics and analysis and evaluation techniques for engineering options, including Concept and role of technical economics; Time value of money formulas for calculating interest rates and equivalents The basis for comparison and selection of alternatives Accounting concepts and cash flow analysis
24. Technology Project Management	3
Technology project management is a module that examines the introduction of new technologies and technological changes in the production of goods and services for the market. This course integrates technology into business and contrasts commercialization with its benefits/disadvantages for business and society. The course design consists of three main parts; The first is knowledge of technology, technology trends in industries, management of technology deployment, and importantly, the combination of people and technology in the development of competitive solutions at enterprises. The second part is the project of applying a new technology solution as well as optimally exploiting the technologies of an enterprise. This section is studied in a project-based way and applied in a business context. Finally, there are individual skills for students in accessing technology, analyzing which technologies bring new value to businesses, and skills working in digital transformation/technology solutions enhancement projects for Business.

Subjects of Major: 39 CREDITS

Course	Credits
25. Introduction to Robotics and Artificial Intelligence (EN)	3
The course equips students of Robotics and Artificial Intelligence with basic knowledge about: - Occupations and training directions in Robotics and Artificial Intelligence; - Organization of the University of Economics Ho Chi Minh City. College of Technology and Design, and other training resources of the school; - Basic knowledge of techniques, technologies, advanced technologies, Industry 4.0; - Knowledge of communication techniques, teamwork, active and creative learning methods related to technology; - Understanding of academic ethics, and scientific ethics; awareness of the history and future of engineering, the connection between engineering and the outside world, and its relevance to contemporary issues.
26. Computer Science 1 (EN)	3
This course provides learners with basic knowledge of computer programming and the Python programming language. Provide learners with basic knowledge and skills in computer programming: determine the requirements of the problem, build algorithm flowcharts, build programs and compile programs. The course helps learners to have theoretical background and skills to be able to grasp and use programming software to apply to building control programs for real systems.
27. Electrical - Electronics Engineering (EN)	3
This course provides students with basic knowledge of materials for manufacturing electronic components. Present the structure, characteristics, and applications of basic electronic components such as Diode, Transistor, SCR, TRIAC, DIAC, OP-AMP, and 4-layer semiconductor devices, optoelectronic components. Teach students how to analyze, calculate parameters and design basic electronic circuits such as rectifier circuits, clipper circuits, DC power circuits, small signal amplifier circuits, power amplifier circuits, transistor circuit breakers, oscillator circuits, and control circuits using SCR, TRIAC, DIAC, photoresistor, Opto and electronic circuits applied in reality.
28. Engineering Drawings (EN)	3
The course equips students with basic knowledge of technical drawings including 1- Standards for drawing presentation; 2- Construction tools used to solve common geometric problems in the design and construction of technical drawings; 3- Projection & method of perpendicular projections used in technical drawing; 4- Standards and regulations on the representation of objects used in the presentation of technical drawings, including detailed drawings & assembly drawings. The subject helps students develop reading comprehension skills & building technical drawings for machine parts and assemblies as well as practice scientific working style, carefulness, sense of organization, and discipline of workers. technical work.
29. Engineering Mechanics 1 (EN)	3
This course provides students with basic knowledge of statics, kinematics, and dynamics of absolute solids. Which: statics provides knowledge related to the static equilibrium conditions of the point, of the solid under the action of force; kinematics is the study of geometrical parameters of the parallel plane motion of a solid, of a point belonging to a solid; Kinetics is the study of the motion of a rigid body under the action of a force. On the basis of the knowledge learned above, students will determine the binding reactions in the mechanical system. From the kinematics knowledge, students can calculate the design of the structure satisfying the geometrical requirements of the given motion. Finally, knowledge of dynamics allows students to determine the properties of motion of a rigid body under the action of a force.
30. Engineering Mechanics 2 (EN)	3
The course provides basic knowledge on deformed solid mechanics, basic concepts of deformation, internal force, stress, displacement, stress state & durability theories used in machine design calculations. & machine details. The course equips students with methods to determine internal forces, stresses, and displacements for structures and rod-shaped details working in the linear elastic domain subjected to tensile/compression, torsion, and bending loads, thereby solving Basic problems in calculating and designing machine parts based on durability, rigidity and stability conditions.
31. Theory of Automatic Control (EN)	3
This course provides students with the basic knowledge and basic knowledge of the theory of automatic control of continuous linear systems. Provide learners with knowledge and skills in modeling physical systems, knowledge, and skills in applying mathematical tools to survey the dynamic properties of the system, evaluate the kinetic quality of the system. control system design and calibration. This is an industry foundation course, helping students to have the background knowledge to quickly access specific and specialized applications in the field of Robotics.
32. Digital Technique (EN)	3
The course provides for learners with basic knowledge about digital systems, operating principles, and structures of digital systems, providing a simple method of designing and reducing the system, designing the system according to a given requirement, and the practical application of the number system.
33. Microcontroller (EN)	3
The course equips learners with basic knowledge about microcontrollers, methods of designing digital systems using microcontrollers, basic peripherals, and their applications in digital systems.
34. Actuators and Sensors (EN)	3
This course provides students with basic knowledge of the principle, operation, operation, and application of sensors such as color, proximity, capacitive, inductive, magnetic, and temperature sensors, optical, pressure, force, rotation angle, and velocity. Besides, the course also provides basic knowledge about DC, AC, servo, and linear actuators.
35. Manufacturing Processes	3
This course provides the basic technical knowledge of mechanical engineering from the beginning to the end of the part manufacturing process. The course equips technical students but not specialized in machine manufacturing technology to have the ability to calculate, select materials, workpieces, machining and mechanical manufacturing methods to meet technical and business requirements. economic. The course includes the following topics: + material selection + method of creating embryos + processing method + check product reviews + rapid prototyping The subject helps learners to have the knowledge and skills to choose the appropriate materials, workpiece fabrication and machining methods when entering the actual mechanical production.
36. Mechanical Design (EN)	3
This subject is the basic subject of the engineering block, including two contents of Machine Principles and Machine Details. The content of machine principles equips learners with the necessary knowledge about the principles of structure structure, methods of determining the dynamic factors, the dynamics of the structure, the dynamics of the mechanism and the machine. The detailed content of the machine equips the theoretical basis and calculation methods to design the machine parts and machine parts present in most modern machines, providing the basic knowledge of the working principles and results. structuring machine parts, fostering the ability to independently solve problems of calculating and designing machine parts and mechanical drive systems, very important contents in machine design in general. This subject helps students to be able to solve technical problems in machine kinematics computation, design sequence of machine parts. From there, students will apply the knowledge in the subject to solve machine design problems when implementing subject projects and graduation projects.
37. Robotics 1 (EN)	3
This course provides students with the basic knowledge and foundation of robotics engineering. Students will build on the foundation of previous subjects such as: engineering mechanics, mechanical design, automatic control to build, design and evaluate robotic systems. The content in this module includes: conversion of coordinate system; robot kinematics analysis; determine the problems of forward kinematics, inverse kinematics of robots; set the motion trajectory of the robot; Jacobi problem and velocity; forward and reverse dynamics; programming simulation and robot control.

Subjects of Minor: 48 CREDITS

Course	Credits
38. Robotics 2 (EN)	3
This course provides students with the basic knowledge and foundation of robotics engineering. Students will build on the foundation of previous subjects such as: engineering mechanics, mechanical design, automatic control to build, design and evaluate robotic systems. The content in this module includes: conversion of coordinate system; robot kinematics analysis; determine the problems of forward kinematics, inverse kinematics of robots; set the motion trajectory of the robot; Jacobi problem and velocity; forward and reverse dynamics; programming simulation and robot control.
39. Computer Sciences 2 (EN)	3
This course aims to provide learners with the basic knowledge of interface programming and the C# programming language. Provide learners with basic knowledge and skills in interface programming: defining problem requirements, designing interfaces and building interface programs. The course helps learners to have a theoretical background and skills to be able to grasp and use programming software to apply to building control programs for real systems.
40. Robotic Lab	2
• Working principle of industrial automation systems such as sensors, PLCs, CN communication networks, industrial robots • Components in industrial automation systems and industrial robots • Basic principles to simulate Industrial Robots with kinematics, dynamics, and control problems • Basic operating principles for programming and operating Industrial Robots, • Principles of application of industrial robots in practice.
41. Artificial Intelligence (EN)	3
Upon completion of the course, students have a basic understanding of the key ideas for implementing artificial intelligence (AI) applications in mechatronic systems. Students will have a good background and understanding of search algorithms, limit satisfaction, genetic algorithms, logic-based inference, planning and machine learning. The objective of this course is designed to expose students to the frontiers of information systems and intensive computing, while providing a strong enough foundation to encourage further study.
42. Embedded System	3
The course provides students with knowledge of embedded systems and its applications. Help students understand ARM, Broadcom processor architecture. Write code to communicate, control hardware directly with C language. Develop embedded systems on RTOS and Linux real-time operating systems.
43. Computer Vision	3
This module equips students of Robotics and AI Technology with the knowledge of still and moving image processing techniques, including basic processing skills (manipulating images and cameras with programs, blur, denoise, edge highlight, color space conversion) and enhancement (color recognition, contour, motion detection...). At the same time, applying image processing techniques to create intelligent sensor systems for machines (machine vision for machines) used in production lines and daily life.
44. Automation System	3
The course provides initial knowledge of industrial automatic control systems, sensor engineering, actuators and PLC control systems. This is an in-depth subject on the industrial production process automation line, helping learners to become aware of the components in a production system, working principles and methods of designing a system. industrial production management automation.
45. Internet of Things	3
The course provides students with basic and advanced knowledge about IoT systems, components and applications of IoT. Students will experience the steps of implementing an IoT system on the Raspberry platform. In addition, students will be introduced and guided to use cloud computing services in data processing.
46. Human Machine Interaction	3
This course will focus on the field of Human-Robot Interaction (HRI) as well as the issue of virtual reality interaction. This course combines a wide range of knowledge and areas for robotics and artificial intelligence with the support of cognitive psychology. The main goal of this subject is to enable robots to successfully interact with humans. As robots increasingly enter functional roles in everyday human environments (like homes, schools, and hospitals), we need them to be able to interact with ordinary people.
47. Automatic Control Lab	1
System dynamics survey Real-time PID control Digital PID control Controlling objects with delay properties State feedback control Tuning the nonlinear system around the equilibrium point
48. AI Lab	1
• Working principle of AI systems in life and industry • Recalling the basic network configurations of AI • Basic principles for programming AI programs • Basic platforms for data collection and processing. • Principles of application of AI in practice.
49. Project of Robot Design	1
This course introduces students to advanced concepts, principles, and algorithms in robotics and embedded systems. This is a project course that tackles a big challenge: creating a robotic system. Solving challenging big problems requires designing and programming robots or embedded systems that interact effectively and autonomously with the real world. Students will learn about modern technology in robotics and integrate and put to use theoretical knowledge from this course or earlier in the curriculum. Topics include: control, motion planning; state estimation; dynamics and reversible dynamics, computer vision, visual control, mesh networking and network control of multi-robot systems. The course will be structured with a lecture and lab. Lectures will be used to present concepts and algorithms for the course topics. Students will also present design reviews during lectures. Labs will be used to develop and implement the course challenge project. Students will work in groups to design an integrated solution for a robotic gardening system. Students will be introduced to the course platforms and system infrastructure in the lab first. In subsequent labs, students will work in small lab groups to develop, implement and evaluate a robust solution for a component of a project. The final module of the course will integrate all components and evaluate performance.
50. Project of Artificial Intelligence	1
This project requires students in the field of Robotics and AI to carry out a project to help learners consolidate their basic knowledge of the application of artificial intelligence in a real-life field. Understand artificial intelligence networks, and process and collect data for training AI models. Simultaneously improve the ability to program, calculate, and select suitable models for each application field.
- Elective: Select 3 out of 7	9

51. Big data and Applications	3
The course introduces an overview of the concept, characteristics as well as challenges of Big data (Ability to analyze and predict to extract a greater value from data). Introduce some popular methods and tools for mining and managing Big data (Hadoop, MapReduce, and Spark).
52. Natural Language Processing	3
Natural Language Processing (NLP) is one of the most important technologies of the information age. Understanding complex linguistic expressions is also an important part of artificial intelligence. Applications of NLP are everywhere because people communicate almost anything in language: web searches, advertising, email, customer service, language translation, radiology reports, and more. There are many fundamental tasks and machine learning models behind NLP applications. Recently, deep learning methods have achieved very high performance on various NLP tasks. They can tackle tasks with unique end-to-end models and do not require traditional, task-specific feature engineering. In this course, students will learn to deploy, train, debug, visualize, and invent their own neural network models. The course provides a thorough introduction to cutting-edge research in the field of deep learning applied to NLP. In terms of modeling, we will cover word vector representations, window-based neural networks, recurrent neural networks, long-term short-term memory models, recursive neural networks, networks. convolutional neurons as well as some recent models related to memory composition. Through lectures and programming exercises, students will learn the technical tricks needed to make neural networks work on real-world problems.
53. Optimizations	3
This module introduces optimization problems and types of optimization problems; basic theory of linear programming and duality problems; monomorphic method and dual monomorphic method; some typical problems in economics and engineering lead to linear programming problems; optimal conditions for nonlinear programming problems; Some basic methods for solving nonlinear programming problems.
54. Machine Learning	3
This course provides students with the basic and fundamental knowledge of machine learning such as classification algorithms, grouping, neural networks, deep learning, supervised learning, reinforcement learning and the application of algorithms to solve problems. practical problems and especially in the field of Robots and AI.
55. Deep Learning	3
Computer vision has become ubiquitous in our society, with applications in search, image comprehension, applications, mapping, medicine, drones, and self-driving cars. At the core of many of these applications are image recognition tasks such as image classification, localization, and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly enhanced the performance of these modern image recognition systems. This course dives into the details of deep learning architecture, focusing on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn how to deploy and train their own neural networks, and gain insight into cutting-edge research in the field of computer vision. Additionally, the final mission will give them the opportunity to train and apply multi-million-parameter networks to real-world vision problems of their choice. Through a variety of hands-on exercises and end-of-course projects, students will gain a toolkit for setting up deep learning tasks and practical engineering tricks to train and refine deep neural networks.
56. Nonlinear and Multi-Variable Control	3
This course provides students with basic knowledge about nonlinear and multivariable control such as the theory of stability of nonlinear control, optimization in control of nonlinear feedback systems, and robust control for the system. nonlinear and multivariable.
57. Software Architectures for Robotics and AI	3
A robot is a versatile, multi-form and multi-functional machine. It exhibits completely new and unique characteristics regarding what it is made of, how it is structured and what it can do. To accommodate this diversity of form and function, software architectures for robotics must be grounded in a flexible and efficient execution model that goes beyond those developed in applications. use another domain. Students will be able to identify stability requirements in different scenarios, common design problems and similar approaches to recurring software development problems while designing Robotics applications. new. Another goal of the course is to familiarize students with robotic middleware that is very commonly used in robotic applications, such as ROS (Robot Operating System).
- Elective: Select 3 out of 6	9

58. Walking and Humanoid Robots	3
This course presents the fundamentals of controlling the human figure for locomotion and manipulation. The students will learn the most common solutions used for the synthesis and control of steady motion.
59. Cooperative Robotics, Distributive Robotics, Modular Robotics	3
Distributing devices, sensors and actuators, among several mobile robots increases flexibility while reducing overall costs compared to solutions based purely on a single general purpose robot. However, for effective cooperation between a group of robots, the challenges of effective management of devices and the communication between them must be addressed. This also represents a test for the allocation and planning of actual tasks. Applications range from effective exploration and/or monitoring environments, to rescue work. This solution is widely recognized that it will bring many benefits in the production process in SME companies. Thus, intuitive use, easy to adapt to many different tasks, flexible dynamic structure can be changed easily. In view of this, it is also recognized that a substantial answer to the mentioned needs should forward the development of modular configurable robotic structures which also shall exhibit motion self-organizing properties, once assembled in the desired configuration. With the angles mentioned, this course will provide students with basic mechatronic concepts and related techniques that allow the reconstruction of modular robots; as well as internally distributed self-organizing control methods and related algorithms
60. BioMimetics and BioRobotics	3
This course will cover the foundations of delivery room systems and biological robots. This course will analyze the migratory properties of biological systems, how they move, and biosensors. It will show the relationship between the biological motion introduced into the robotic system. The aim of this course is to expose students to creativity in designing biologically based robotic devices. Roles and positions of the module: This module equips students with the knowledge of biomimicry systems and biological robots. With this knowledge, students have the ability to research, design and manufacture biomimetic systems and biological robots. This is a fairly typical subject of Robotics and Artificial Intelligence, which plays a fundamental role for the study of future robotic systems.
61. Advanced Robot Programming	3
This course presents various theoretical and computational aspects of a wide range of optimization methods to solve a wide variety of problems in engineering and robotics.
62. Digital Signal Processing	3
This course equips students of Robotics and AI Engineering Technology with fundamental concepts and knowledge in the field of digital signal processing such as analog signals, digital signals, their frequency ranges and their relationship between them. The z transform and its application. Discrete Fourier transform (DFT). Fast Fourier transform algorithm FFT. Frequency and impulse response characteristics of ideal discrete filter circuits. The specifications of the actual filter circuit. Synthesized FIR filter by window method. Introducing the optimal FIR filter synthesis according to Chebyshev's theorem and Remez's algorithm, introducing the frequency sampling method. Introduction to the synthesis of IIR filtering by pulse invariant and bilinear methods.
63. Optimal Design of Robots	3
This course provides the methodologies and tools for designing robots with serial and parallel configurations as well as other types of configurations of today's robots. Students will learn the method of optimal mechanical design of today's robots. Common mechanisms such as series and parallel mechanisms, especially combined mechanisms. Mechanical efficiency analysis in mechanical systems considers mechanical resistance (friction) and efficiency limitations of steering systems and actuators. Drive system in robot, required motor power characteristics when considering robot system design, mechanical efficiency and its working condition, design process using materials science (selection of materials with material strength analysis) and including automatic movement system, actuator, power supply.

General education knowledge: 58 CREDITS

Subjects of Major: 39 CREDITS

Subjects of Minor: 48 CREDITS

Graduation Internship: 10 CREDITS

Total credits: 155 CREDITS

UEH Standard programs in English (20% English)

General education knowledge: 58 CREDITS

Subjects of Major: 39 CREDITS

Subjects of Minor: 48 CREDITS

Graduation Internship: 10 CREDITS

Total credits: 155 CREDITS