TUIASI
Machine Learning, Robotics, and Control (MLRC)
MLRC Courses

Machine Learning, Robotics, and Control (MLRC) Courses

The Machine Learning, Robotics, and Control graduate program has an interdisciplinary curriculum built on engineering branches such as automatic control, applied informatics, computer engineering, robotics, communications, and electronics.

1st Year

Mandatory (DI)

Agile Software Development

  • MLRC.IA.104
  • YEAR: 1
  • SEMESTER: 1
  • ECTS: 6

Course organizer:

Sef lucr. dr. ing. Silviu Florin Ostafi

The main goal of this course is to put the Agile methodology, one of the successful approaches to software development, in the context of systems engineering and robotics in general, and manufacturing systems management and robot software development in particular.

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 2 H

Bond Graph Language in Physical Modeling

  • MLRC.IA.103
  • YEAR: 1
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

Prof. dr. ing. Octavian Pastravanu

Development of a unified methodology for modeling physics systems, based on the bond-graph language (formalism)

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 2 H

Complex Dynamical Systems Analysis and Control

  • MLRC.IA.107
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 4

Course organizer:

Conf. dr. ing. Cristina Budaciu

Developing student’s ability to use numerical and experimental methods to analyze structural dynamic systems. Basic mathematical methods for describing dynamics of elastic bodies. Systems with one degree of freedom and systems with multiple degrees of freedom.

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 1 H

Embedded Systems

  • MLRC.IA.102
  • YEAR: 1
  • SEMESTER: 1
  • ECTS: 6

Course organizer:

Prof. dr. ing. Alexandru Onea

The overall educational objective of this class is to allow students to discover how the computer interacts with its environment. It will provide hands-on experiences of how an embedded system could be used to solve problems

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 1 H

Ethics in Artificial Intelligence and Professional Integrity

  • MLRC.IA.109
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 2

Course organizer:

Conf. dr. ing. Constantin Catalin Dosoftei

The overall educational objective of this course is to allow the master students to learn in an appropriate manner, concepts and norms specific for the ethics and integrity within an organization, with the purpose to be further applied in a professional career characterized by competence and fairness.

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 0 H

Intelligent Systems

  • MLRC.IA.106
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 4

Course organizer:

Conf. dr. ing. Lavinia Eugenia Ferariu

Understand the fundamental concepts of sub-symbolic intelligent techniques, with focus on deep neural networks and evolutionary algorithms.

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 0 H

Machine Learning

  • MLRC.IA.101
  • YEAR: 1
  • SEMESTER: 1
  • ECTS: 6

Course organizer:

Conf. dr. ing. Lavinia Eugenia Ferariu

Understand the basic principles used in the field of machine learning, and the main advantages and limitations of machine learning techniques in classification, clustering and regression.

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 0 H

Mobile Robots Path Planning Project

  • MLRC.IA.108
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 4

Course organizer:

Prof. dr. ing. Marius Kloetzer

Understanding a solution for planning the path of mobile robots and transposing it into an user-friendly Matlab implementation

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 2 H

Research and practice (sem. 1)

  • MLRC.PA.105
  • YEAR: 1
  • SEMESTER: 1
  • ECTS: 7

Course organizer:

To develop research skills and prepare the student for a career in research and development in the fields of Machine Learning, Robotics and Control

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

Research and practice (sem. 2)

  • MLRC.PA.110
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 7

Course organizer:

To develop research skills and prepare the student for a career in research and development in the fields of Machine Learning, Robotics and Control

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

1st Year

Elective (DO)

High Level MATLAB Applications for Systems and Control

  • MLRC.IA.111
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 4

Course organizer:

Prof. dr. ing. Mihaela-Hanako Matcovschi

Development of students’ abilities to model and analyse systems using appropriate MATLAB tools.

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 2 H

Knowledge Representation and Reasoning

  • MLRC.IA.113
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 5

Course organizer:

Prof. dr. ing. Doru Adrian Panescu

Understanding the Artificial Intelligence approach based on symbolic processing

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 0 H

Nonlinear Dynamics

  • MLRC.IA.112
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 4

Course organizer:

*

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 2 H

State Space Control

  • MLRC.IA.114
  • YEAR: 1
  • SEMESTER: 2
  • ECTS: 5

Course organizer:

*

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 0 H

2nd Year

Mandatory (DI)

Advanced Communications in Control Systems – Project

  • MLRC.IA.203
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 4

Course organizer:

Prof. dr. ing. Constantin Florin Caruntu

Provides the basic theoretical and practical features involved in the design of advanced communication techniques for control systems.

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

Intelligent Robotic Systems – Modeling and Control Project

  • MLRC.IA.202
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 4

Course organizer:

Prof. dr. ing. Adrian Burlacu

Design, implementation and evaluation of robotic systems in applications that illustrate fundamental notions of the systems and control specialization. Working in teams to put into practice specific algorithms.

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

Modeling and Predictive Control

  • MLRC.IA.201
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

Prof. dr. ing. Constantin Florin Caruntu

Introduction to fundamental knowledge of model based predictive control. Study of different process models, predictors. The design of predictive control laws and their implementation and testing are studied. Develop student skills in order to analyze and design model based predictive control systems by using MATLAB – SIMULINK software

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 1 H

Practice for Master’s Thesis

  • MLRC.PA.206
  • YEAR: 2
  • SEMESTER: 2
  • ECTS: 15

Course organizer:

To develop research skills and prepare the student for a career in research and development in the fields of Machine Learning, Robotics and Control

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

Research and Practice (sem.3)

  • MLRC.PA.204
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 7

Course organizer:

To develop research skills and prepare the student for a career in research and development in the fields of Machine Learning, Robotics and Control

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

Research and Practice (sem.4)

  • MLRC.PA.205
  • YEAR: 2
  • SEMESTER: 2
  • ECTS: 15

Course organizer:

To develop research skills and prepare the student for a career in research and development in the fields of Machine Learning, Robotics and Control

L (lecture) - 0 H

L (lecture) - 0 H

LB (laboratory works) - 0 H

2nd Year

Elective (DO)

Data Mining: Practical Tools and Techniques

  • MLRC.IA.210
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 2 H

Fault Diagnosis

  • MLRC.IA.207
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

Conf. dr. ing. Letitia Mirea

To provide the students the necessary knowledge about process fault diagnosis theory

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 1 H

Machine Vision

  • MLRC.IA.209
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

Prof. dr. ing. Adrian Burlacu

To provide a broad and solid base of understanding how to add computer vision capabilities to robotics systems and expend their application areas

L (lecture) - 1 H

L (lecture) - 1 H

LB (laboratory works) - 2 H

PLC-based Process Automation

  • MLRC.IA.208
  • YEAR: 2
  • SEMESTER: 1
  • ECTS: 5

Course organizer:

*

L (lecture) - 2 H

L (lecture) - 2 H

LB (laboratory works) - 1 H

Structure of the Academic Year 2023– 2024

Bachelor and Master Studies, Full Time Studies

DATE

PERIOD

ACTIVITY

25.09.2023–01.10.2023

7 days

Accommodation of students

02.10.2023

The Official Opening of the Academic Year

1st SEMESTER

02.10.2023-22.12.2023

12 Weeks

Didactic Activity

23.12.2023-07.01.2024

2 Weeks

Christmas Holiday

08.01.2024- 21.01.2024

2 Weeks

Didactic Activity

22.01.2024-11.02.2024

3 Weeks

Examination Period

12.02.2024-18.02.2024

1 Week

Winter Holiday

2nd SEMESTER

19.02.2024-02.05.2024

11 Weeks

Didactic Activity

03.05.2024-12.05.2024

1 Week

Easter Holiday

07.05.2024

Free Day For Students (to be recovered on Saturday 25.05.2024)

13.05.2024-02.06.2024

3 Weeks

Didactic Activity

03.06.2024-23.06.2024

3 Weeks

Examination Period

02.09.2024-15.09.2024

2 Weeks

Reexamination Period

17 and 18.09.2024

2 Days

Re examinations

2nd SEMESTER for the final year of study (bachelor + master)

19.02.2024-02.06.2024

14 + 1 Weeks

Re Didactic Activity and Easter Holiday According To The Previous Calendar

03.06.2024-16.06.2024

2 Weeks

Examination period

17.06.2024-20.06.2024

4 days

Reexamination period

27.06.2024-07.07.2024

11 days

Period for preparing the final thesis

Legal and Religious Holidays:
30.11.2023, 01.12.2023, 25.12.2023 , 26.12.2023, 01.01.2024. 02.01.2024, 24.01.2024 01.05.2024, 03.05.2024, 06.05.2024, 01.06.2024, 24.06.2024, 15.08 2024.


Practical Activities (3 -6 Weeks)
will be scheduled either during the entire academic Year

Gheorghe Asachi Technical University of Iasi, with the oldest engineering education tradition in Romania, is dedicated to developing technology for the community through research, teaching, and technology transfer.

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