Why Graduate Diploma
The qualification of the University of London will allow you to get more specialized knowledge and will be a plus when continuing your studies abroad or when applying for a job!
In this program, you will study based on the materials of the London School of Economics and take external exams, which will also be checked by the London School of Economics
A Graduate Diploma is an academic and professional qualification that aims to provide students with specialized knowledge and skills for a specific industry. Unlike a degree, it is usually completed in a shorter period of time and is intended to enhance employment opportunities by offering additional expertise. It is typically pursued after a bachelor's degree and can also serve as a stepping stone towards a relevant master's degree.
A Graduate Diploma is a specialized academic qualification that enhances employment opportunities. It's completed in less time than a degree and provides industry-specific knowledge and skills.
Often pursued after a bachelor's degree, it can also serve as a stepping stone to a relevant master's degree.
Programs
Graduate Diploma in
Data
Science
Data
Science
Graduate Diploma in Business Analytics
This diploma prepares graduates for a quantitative career in data science. Developed by LSE, it will enable you to become a competent and confident data modeller and interpreter, assisting management to make data-driven decisions.
This diploma equips graduates with the analytical and commercial know-how to turn data into actionable solutions to real-world problems.
Developed by LSE, it prepares you for a quantitative career in business analytics. It can also prepare you for postgraduate study in the field.
Developed by LSE, it prepares you for a quantitative career in business analytics. It can also prepare you for postgraduate study in the field.
Business Analytics
- Information system management
- Machine learning
- Programming for data science
- Business analytics and applied modeling
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Data Science
- Business analytics and applied modeling
- Statistical methods for market research
- Entrepreneurship
- Information system management
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The duration of the programme is 1 year, will be held in English, within the walls of KBTU
Graduate Diploma Business Analytics Programm
For those undertaking market research in practice, an ability to handle data is an essential skill. This course concentrates on transforming students into competent and confident users of statistical software to enable them to conduct independent data analysis by taking a more applied approach to conventional statistics. The first half of the course focuses on aspects of market research, and in the second half the emphasis is on the practical application of a variety of multivariate statistical techniques to supplied datasets.
- ST3188 Statistical methods for market research
Two compulsory courses
- ST2187 Business analytics, applied modelling and prediction
People in business, economics and the social sciences are increasingly aware of the need to be able to handle a range of mathematical and statistical models. It must be admitted that many good managers are not very mathematically adept. However, they would be even more inquisitive, more precise, more accurate in their statements, more selective in their use of data, more critical of advice given to them etc. if they had a better grasp of quantitative subjects. Modelling is an important tool which all good managers should appreciate. The course extends and reinforces existing knowledge and introduces new areas of interest and applications of modelling in the ever-widening field of management
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Graduate Diploma Business Analytics Programm
This course studies the management of information systems in organisations. It identifies the main managerial factors affecting the design and implementation of ICTs in organisations. It also introduces basic principles of project management and governance. The course also overviews the most common strategies associated with ICT management and the tools used to manage these strategies. These are contrasted with organisational issues such as structure, planning and control and deployment framework. Finally, the course provides a holistic view of benefit management and information systems strategy alignment.
Two elective courses
- IS2184 Information systems management
- MN3194 Entrepreneurship
This course is about entrepreneurship both from an economics and practitioners angle and shows how economics can contribute to our understanding of entrepreneurship. The course also sheds light on the societal impact of entrepreneurship and its utility for economic development. It further provides practical elements such as developing business models, designing market research frameworks, product development cycles, and raising seed capital.
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Graduate Diploma Data Science Programm
This course studies the management of information systems in organisations. It identifies the main managerial factors affecting the design and implementation of ICTs in organisations. It also introduces basic principles of project management and governance. The course also overviews the most common strategies associated with ICT management and the tools used to manage these strategies. These are contrasted with organisational issues such as structure, planning and control and deployment framework. Finally, the course provides a holistic view of benefit management and information systems strategy alignment.
Two compulsory courses
- IS2184 Information systems management
- ST3189 Machine learning
In the last decade there has been a remarkable growth in machine learning with image and speech recognition, recommendation systems and artificial intelligence being only some the big success stories. Following recent advances in gathering, storing and managing vast amounts of observations, the ability to process high dimensional data and deal with uncertainty becomes increasingly important. This course covers a wider range of such model based and algorithmic machine learning methods, illustrated in various real-world applications and datasets. At the same time, the theoretical foundation of the methodology is presented.
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Graduate Diploma Data Science Programm
In the last decade the demand for programming skills related to managing and visualizing data has grown remarkably. Python, R and SQL feature consistently in the top skills listed in data science and data analyst jobs. Knowing how to write efficient software code to handle and visualise data is an essential skill for any modern data scientist. This course will cover the main principles of computer programming with a focus on data science applications by following the entire pathway from raw data to databases, data wrangling and visualisation, machine learning frameworks up to software development.
Two elective courses
- ST2195 Programming for data science
- ST2187 Business analytics, applied modelling and prediction
People in business, economics and the social sciences are increasingly aware of the need to be able to handle a range of mathematical and statistical models. It must be admitted that many good managers are not very mathematically adept. However, they would be even more inquisitive, more precise, more accurate in their statements, more selective in their use of data, more critical of advice given to them etc. if they had a better grasp of quantitative subjects. Modelling is an important tool which all good managers should appreciate. The course extends and reinforces existing knowledge and introduces new areas of interest and applications of modelling in the ever-widening field of management.
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Professors
Requirements
English Proficiency tests
- APTIS: must achieve an overall CEFR score of at least B2 equivalent with at least B2 equivalent in each sub category.
- Duolingo: must achieve an overall score of at least 105.
- IELTS: 6 overall, with 5.5 in each sub-test.
- TOEFL : 87 overall, with 21+ in Reading and Writing sub-tests and 19+ in Speaking and Listening sub-tests.
- An acceptable Bachelor's degree,
Either in a quantitative subject or where you have passed at least 2 courses in satisfactory mathematical subjects.
List of documents :
The fees below relate to new students registering for the 2023-2024 session, and are effective from 25 January 2023. These may be increased by up to 7% per annum.
Fees
2023-2024
University of London
Continuing registration fee
£2958
£581
Initial registration fee
Examination entry fee per (half course)
Examination entry fee per (full course)
Online examination fee*
Application fee (non-refundable)
£107
£1275
£192
£384
£10
Academic year
Indicative total
The fee below relates to students who are not in enrolled in Master’s degrees
2023-2024
KBTU
Total ECTS
20 ECTS
Academic year
700 000 KZT
Indicative total
*When applying for a master's degree at KBTU, you can register for this program and study for free, paying only for exams at the University of London. At the end of the master's program, you receive two diplomas - KBTU and University of London.
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