Bachelor of Science in Robotics EngineeringApply now |
Overview
Robotics Engineering is a multidisciplinary field that combines mechanical, electrical, computer, and systems engineering to design, develop, and implement advanced technological systems. These systems include robots, prostheses, medical devices, electric vehicles, automated production systems, and intelligent machines.
The BSc in Robotics Engineering at Nazarbayev University School of Engineering and Digital Sciences is a four-year undergraduate program designed to prepare engineers who can work with modern robotic and mechatronic systems in industry, research, and technology-driven sectors.
The program has been running since 2011 and is the first undergraduate Robotics degree program in Kazakhstan, as well as one of the first Robotics programs in the world. It provides students with strong theoretical foundations, practical engineering skills, hands-on laboratory experience, and opportunities to work on real-world robotics and mechatronics projects.
Graduates of this program are prepared to contribute to automation, intelligent systems, industrial modernization, research, and the development of local robotics and mechatronics companies.
The BSc in Robotics Engineering at Nazarbayev University School of Engineering and Digital Sciences is a four-year undergraduate program designed to prepare engineers who can work with modern robotic and mechatronic systems in industry, research, and technology-driven sectors.
The program has been running since 2011 and is the first undergraduate Robotics degree program in Kazakhstan, as well as one of the first Robotics programs in the world. It provides students with strong theoretical foundations, practical engineering skills, hands-on laboratory experience, and opportunities to work on real-world robotics and mechatronics projects.
Graduates of this program are prepared to contribute to automation, intelligent systems, industrial modernization, research, and the development of local robotics and mechatronics companies.
Testimonials
Alisher Igizgali
Major: BSc Geology
Graduation Year: 2024
Graduation Year: 2024
Growing up in the West Kazakhstan Region, I witnessed how the thoughtful use of natural resources could uplift entire communities. I also noticed a shortage of local professionals with the expertise needed to make this a reality. This realization inspired me to address the skills gap in my community. After high school, I decided to pursue Geosciences.
NU SMG stood out as the ideal choice for many reasons. It offered diverse coursework, modern facilities, experienced faculty, a research-focused approach, and a strong sense of community. The Geology program covered many core subdisciplines, including petrology, mineralogy, and stratigraphy. It also included interdisciplinary fields like paleontology, geostatistics, and GIS. This variety was important to me as I did not want to narrowly specialize too early.
Also, the low student-to-faculty ratio ensured personalized attention. Fieldwork combined with classroom learning gave me hands-on experience, which is essential for geologists. Students were encouraged to join research projects outside the curriculum, and collaboration projects with leading companies in Kazakhstan and abroad including big oil and mining companies.
My time at SMG enriched me both academically and personally. Contributing to an undergraduate research project helped me sharpen my technical expertise and problem-solving abilities. I also developed a professional network in academia and industry, and honed my soft skills like teamwork and critical thinking.
I encourage anyone interested in this field to consider SMG, as it provides excellent preparation in both academic and practical aspects.
NU SMG stood out as the ideal choice for many reasons. It offered diverse coursework, modern facilities, experienced faculty, a research-focused approach, and a strong sense of community. The Geology program covered many core subdisciplines, including petrology, mineralogy, and stratigraphy. It also included interdisciplinary fields like paleontology, geostatistics, and GIS. This variety was important to me as I did not want to narrowly specialize too early.
Also, the low student-to-faculty ratio ensured personalized attention. Fieldwork combined with classroom learning gave me hands-on experience, which is essential for geologists. Students were encouraged to join research projects outside the curriculum, and collaboration projects with leading companies in Kazakhstan and abroad including big oil and mining companies.
My time at SMG enriched me both academically and personally. Contributing to an undergraduate research project helped me sharpen my technical expertise and problem-solving abilities. I also developed a professional network in academia and industry, and honed my soft skills like teamwork and critical thinking.
I encourage anyone interested in this field to consider SMG, as it provides excellent preparation in both academic and practical aspects.
Geology in Action: Field Trip Adventures in Kazakhstan
Geology at Nazarbayev University
Step into the vast world of geology at Nazarbayev University—where learning goes beyond the books into the great outdoors.
General information
- Campus: Astana, Kazakhstan
- Language: English
- Delivery mode: Full time, on-campus
- Duration: 4 years
- Total ECTS credit: 246
Program Aims
The educational objectives of the BSc in Robotics Engineering program are to prepare graduates who are able to:
- Have a basic understanding of the fundamentals of mechanical, electrical, computer and systems engineering.
- Apply the theoretical and practical skills acquired in the courses to design and implement robotic and mechatronic systems.
- Use their technical and entrepreneurial skills to improve society.
- Contribute to the scientific and economic development of the Republic of Kazakhstan.
- Adhere to the highest ethical behaviour and standards expected of responsible professionals.
Key Advantages
- The first undergraduate Robotics degree program in Kazakhstan1
- Capstone projects focused on real robotics and mechatronics engineering challenges2
- Multidisciplinary curriculum combining mechanical, electrical, computer, and systems engineering3
- Strong preparation for careers in automation, robotics, mechatronics, intelligent systems, and graduate studies4
- Hands-on laboratory experience in circuits, sensors, microcontrollers, control systems, mechanical design, electromechanical systems, and robotics5
- Opportunities for credit-bearing internships in companies in Kazakhstan or abroad, as well as research laboratories of foreign universities6
Learning Outcomes
On successful completion of the program students will be able to:
- An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
- An ability to apply engineering design to producesolutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
- An ability to communicate effectively with a range of audiences.
- An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must considerthe impact of engineering solutions in global, economic, environmental, and societal contexts.
- An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
- An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
- An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
What Will You Learn?
- Mechanical, electrical, computer, and systems engineering fundamentals
- Engineering mathematics, probability, linear algebra, differential equations, and physics
- Programming, data structures, and embedded systems
- Mechanics, statics, dynamics, system modeling, and simulation
- Electrical and electronic circuits, microcontrollers, sensors, and signal processing
- Mechanical design, CAD, machining, rapid prototyping, and finite element analysis
- Linear control theory, electromechanical systems, and motor drives
- Industrial robotics, robot kinematics, robot dynamics, and safety
- Robot control, modeling, motion planning, and learning-based robotics
- ROS-based control architectures and robotics simulation tools such as MATLAB/Simulink, Gazebo, and related software environments
- Robotic and mechatronic system design through project-based learning
- Research methods, technical communication, teamwork, and capstone project development
- Specialized elective areas such as embedded systems, power electronics, industrial automation, image processing, machine learning, and human-robot interaction
Curriculum
Year 1: Fall Semester (30 ECTS)
Year 1: Spring Semester (30 ECTS)
Year 2: Fall Semester (30 ECTS)
Year 2: Spring Semester (34 ECTS)
Year 3: Fall Semester (34 ECTS)
Year 3: Spring Semester (32 ECTS)
Year 4: Fall Semester (32 ECTS)
Year 4: Spring Semester (24 ECTS)
Electives
- Exploration Geology and Geophysics
- Carbonate Systems, Processes and Deposits
- Photography for Geosciences
- Environmental Geochemistry
- Engineering Economics
Handbook
Core modules
The list of core modules
This course covers foundations of probability theory, combinatorial and counting methods, conditional probability, random variables, discrete and continuous distributions, expectation, moment generating functions, multivariate distributions, variable transformations, the Law of Large Numbers and the Central Limit Theorem.
Course learning outcomes
Course learning outcomes
- Use basic counting techniques (multiplication rule, combinations, and permutations) to compute conditional probabilities directly and using Bayes' theorem and check for independence of events.
- Introduce random variables and work with discrete and continuous random variables. In particular, understand the basic properties of Bernoulli, binomial, geometric Poisson distributions, uniform, Gamma and exponential, normal distribution and compute the central limit theorem.
- Be able to compute the expectation, variance, covariance and correlation between jointly distributed variables, Moment generating functions, Transformation of random variables and the computation of order statistics.
- Apply knowledge of probability to solve problems from the field of electronic, electrical and communications of applicable nature, falling in both discrete and continuous domain.
This is a one-semester course intended for mathematics, engineering, and science students. It covers first order differential equations; mathematical models and numerical methods; linear systems and matrices; higher-order linear differential equations; linear systems of differential equations; and Laplace transform methods.
Course learning outcomes
Course learning outcomes
- Classify differential equations and learn basic concept related to ordinary differential equations.
- Solve linear and some simple nonlinear ordinary differential equations using different solution techniques.
- Solve systems of first order linear ordinary differential equations.
- Describe the general behavior of the solutions to differential equations and systems of first order linear ordinary differential equations.
- Modelsimple real-world problems using ordinary differential equations.
- Employ Laplace transform for linear ordinary initialvalue problems.
This one-semester course is intended for mathematics, engineering and science students. It introduces students to the fundamental concepts of linear algebra. The course primarily deals with two mathematical objects: matrix and vector, and covers topics such as solutions of systems of linear equations, properties of invertible matrices, linear transformation, determinant, eigenvalues and eigenvectors, vector spaces and subspaces, linear independence, basis, coordinates, inner product, norm, orthogonal basis, similarity, and quadratic forms.
Course learning outcomes
Course learning outcomes
- Employ row reduction algorithm to solve systems of linear equations.
- Understand basic matrix algebra and construct linear problems in the matrix forms.
- Implement the basic theory of finite dimensional vector spaces and related concepts such as subspaces, basis, and linear transformations; Gram-Schmidt process.
- Solve eigenvalue problems and apply matrix diagonalization procedures.
Elective Courses
This course will introduce the students to the principles behind the geological and geophysical methods applied in exploration for mineral, hydrocarbon, and water resources.
Course learning outcomes
1. Relate each geophysical exploration method to physical properties of minerals and rocks.
2. Evaluate which exploration methods should be used at which exploration stage in either mineral, hydrocarbon, or water resource exploration.
3. Design a simple exploration strategy for hydrocarbon or mineral resources.
4. Interpret and evaluate geophysical data in terms of subsurface geology.
Course learning outcomes
1. Relate each geophysical exploration method to physical properties of minerals and rocks.
2. Evaluate which exploration methods should be used at which exploration stage in either mineral, hydrocarbon, or water resource exploration.
3. Design a simple exploration strategy for hydrocarbon or mineral resources.
4. Interpret and evaluate geophysical data in terms of subsurface geology.
The course will provide the students with a solid background in sedimentology, in particular concerning the formation and evolution of carbonate sedimentary rocks; deep water sediment transport and deposition in the context of sequence stratigraphy and facies models; mechanical stratigraphy with implications to fluid flow; utility of outcrop studies for subsurface reservoir characterization and modeling.
Course learning outcomes
1. Discuss carbonate depositional settings.
2. Identify different carbonate facies and their spatial relationships.
3. Describe sedimentary structures in cores and outcrops and use them to interpret sedimentary processes and depositional environments.
4. Distinguish early sedimentary fractures from tectonic fractures.
5. Discuss geological controls on petroleum reservoir exploration and development.
Course learning outcomes
1. Discuss carbonate depositional settings.
2. Identify different carbonate facies and their spatial relationships.
3. Describe sedimentary structures in cores and outcrops and use them to interpret sedimentary processes and depositional environments.
4. Distinguish early sedimentary fractures from tectonic fractures.
5. Discuss geological controls on petroleum reservoir exploration and development.
This course will cover fundamental aspects of physical chemistry relevant to heavy metal dispersion, radionuclide migration, and oil spill contamination. The processes of adsorption, complexation, solubility, and co-precipitation will be thermodynamically characterized with the aid of a geochemical software. A comprehensive review will be made of environmental pollutants in the atmosphere, the ocean, as well as in continental areas. Remediation techniques will be discussed, and a local case study will be investigated by the students.
Course learning outcomes
1. Discuss the nature and sources of pollutants in the environment.
2. Interpret aqueous geochemical and mineralogical data in terms of their environmental significance, using sound thermodynamic and kinetic reasoning.
3. Expertly model the behavior of contaminants with a geochemical software.
4. Propose remediation techniques for contaminated sites.
Course learning outcomes
1. Discuss the nature and sources of pollutants in the environment.
2. Interpret aqueous geochemical and mineralogical data in terms of their environmental significance, using sound thermodynamic and kinetic reasoning.
3. Expertly model the behavior of contaminants with a geochemical software.
4. Propose remediation techniques for contaminated sites.
Photography is an essential part of Geology. In this digital photography course students will learn to understand what different types of cameras and lenses exist, how to work properly with the camera, including smart phone, understanding and making full use of the various camera settings (iso, shutter speed, aperture etc.). They will learn how to work with natural and with artificial light, learn about colors, composition, making high quality pictures. Notably: images of minerals, fossils, rocks with the macrolense, and under the microscope, and outside in quaries or mountains. Students will learn image processing with Adobe Lightroom (Adobe Adobe Photoshop, Illustrator, InDesign) correcting image quality, and learn e.g. how to stitch images making panoramas, get familiar with different color codes (RGB, CMYK etc.), file formats (GIF, JPEG, TIFF, RAW etc.), loss in quality (e.g. resolution or change in color) when copying images and pasting in word processors, saving them as a PDF, printing on a color printer, or presenting with a beamer. Students will also learn about issues like plagiarism and copyright in photography, tagging, and organising pictures in personal or public database, and preparing pictures for presentation and publication.
Course learning outcomes
1. Propose a conceptual set-up for digital adaptation in accordance to the field of geosciences (C5).
2. Produce digital image processing in accordance with the latest technology in geosciences (P4).
3. Adapt digital photography and image analysis in geosciences (P6).
4. Present their own, new high quality geoscientific photos with explanation to an audience (C6).
Course learning outcomes
1. Propose a conceptual set-up for digital adaptation in accordance to the field of geosciences (C5).
2. Produce digital image processing in accordance with the latest technology in geosciences (P4).
3. Adapt digital photography and image analysis in geosciences (P6).
4. Present their own, new high quality geoscientific photos with explanation to an audience (C6).
Economic analysis presents a structured approach to understanding natural resource industries. The focus of this course is on the market mechanism and its demand-supply model. Students learn both the theory and its applications to analyzing natural resource markets. Specifically, topics include market equilibrium, prices, costs, and government regulation. Students apply economic models to understand how resource markets are impacted by the business cycle, economic growth, emerging technologies, and climate policies.
Course learning outcomes
1. Assess a project using the discounted cash flow model.
2. Analyze alternatives on a before-tax and after-tax basis.
3. Appraise projects considering inflation, exchange rates, and uncertainty.
Course learning outcomes
1. Assess a project using the discounted cash flow model.
2. Analyze alternatives on a before-tax and after-tax basis.
3. Appraise projects considering inflation, exchange rates, and uncertainty.
Where do our graduates work?
- Career opportunities
- Robotics and mechatronics engineering
- Industrial automation
- Manufacturing and smart production
- Control systems engineering
- Embedded systems and electronics
- Robot programming and integration
- Machine learning and intelligent systems
- Computer vision and image processing
- Human-robot interaction
- Medical and rehabilitation robotics
- Electric vehicles and electromechanical systems
- Research and development
- Technology startups
- Graduate studies in robotics, engineering, AI, automation, or related fields
- Where???
Admissions & Apply now
Our Contacts
Feel free to write, call, and visit us.
Regarding consultation on admissions
On academic issues
Address:
Address: 53, Kabanbay batyr Ave., Astana, 010000, Kazakhstan.
Phone numbers
+7 (7172) 64 25 84
+7 747 094 02 30
+7 747 094 02 30
Fees and Funding:
For more detailed information about tuition fees, please contact the Bursar's Office:
For more detailed information about tuition fees, please contact the Bursar's Office:
- Phone: +7 (7172) 70 60 32, 70 91 99
- Email: bursars_office@nu.edu.kz
- Office: 1.248B Block 1
- Address: 53, Kabanbay batyr Ave., Astana, 010000, Kazakhstan