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Study programme, year:
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| Study programme syllabus for |
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| MPDSC - DATA SCIENCE AND AI, MSC PROGR |
Academic year: 2020/2021 |
| DATA SCIENCE OCH AI, MASTERPROGRAM | | Associated to: TKITE |
| The Study programme syllabus is adopted 2019-02-21 by Dean of Education
and is valid for students starting the programme the academic year 2020/2021 |
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| Entry requirements: |
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General entry requirements:
Basic eligibility for advanced level
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Specific entry requirements:
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English proficiency:
An applicant to a programme or course with English as language of instruction must prove a sufficient level of English language proficiency. The requirement is the Swedish upper secondary school English course 6 or B, or equivalent. For information on other ways of fulfilling the English language requirement please visit Chalmers web site.
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Undergraduate profile:
Engineering, Technology, Science or Mathematics.
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Prerequisities:
Mathematics (at least 30cr., including Multivariable Analysis, Linear Algebra, and Mathematical Statistics), Programming in a General-Purpose Language (e.g. C/C++/Java/Haskell or similar (at least 7,5 cr.)), and Algorithms and/or Data Structures (at least 7,5 cr.).
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| General organization: |
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Aim:
The Data Science and AI master programme aims at providing the students with a good theoretical knowledge and practical skills regarding mathematical, statistical and computer science methods to manage, analyze and extract information from large scale data sets, as well as develop tools and algorithms in complex, computer intense and AI related applications.
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Learning outcome:
Knowledge and understanding
On successful completion of the programme the student will be able to
- describe what data science and machine learning is and can be in terms of question
formulations, models and methods and their pros and cons,
- master necessary tools and concepts, such as within probability theory, statistics,
optimization, algorithms and software architecture, at a level where they can
modify and develop them in the desired direction,
- apply their practical experiences of modelling through implementation, simulation,
analysis and testing of the models, - give a detailed account of the most up-to-date question formulations, the most
recent technology and the most recent research results within a subdomain.
Skills and abilities
On successful completion of the programme the student will be able to
- participate in the development of intelligent and automated digital
systems, thereby improving, accelerating, and amplifying the
digitalisation of society - create models of concrete problems and balance the model complexity against the amount
and quality of data, as well as against time and computational power,
- deduce and apply the methods in optimization and statistics, required for a correct
analysis of the model behavior and experimental results,
- create and implement efficient algorithms for analysis and simulation,
- master field relevant programming languages and tools as well as be able to deal with
different data formats,
- quickly absorb and implement new knowledge in a changeable field,
- communicate their results and conclusions verbally, in writing and visually to both experts
and non-experts.
Judgement and approach
On successful completion of the programme the student will be able to
- critically analyze models and algorithms with regards to efficiency and reliability,
- give an account of the possibilities and limitations of the technology, and be
responsible for its ethical, societal and environmental sustainability, and
thereby contribute to a discussion of its role in the society.
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Extent:
120.0 c
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Thesis:
The programme includes a degree project (Master's thesis) corresponding to 30 credits. The rules for starting and carrying out the the degree project are described in the corresponding course syllabi for the second year of the study programme.
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Courses valid the academic year 2020/2021:
See study programme
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Accredited to the following programmes the accademic year 2020/2021:
Degree of Master of Science in Engineering
TKATK - ARCHITECTURE AND ENGINEERING
TKAUT - AUTOMATION AND MECHATRONICS ENGINEERING
TKMED - BIOMEDICAL ENGINEERING
TKDAT - COMPUTER SCIENCE AND ENGINEERING
TKELT - ELECTRICAL ENGINEERING
TKTEM - ENGINEERING MATHEMATICS
TKTFY - ENGINEERING PHYSICS
TKGBS - GLOBAL SYSTEMS ENGINEERING
TKDES - INDUSTRIAL DESIGN ENGINEERING
TKIEK - INDUSTRIAL ENGINEERING AND MANAGEMENT
TKITE - SOFTWARE ENGINEERING
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| Degree: |
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Degree of master of science (120 credits):
Passed courses comprising 120 credits
Passed advanced level courses (including degree project) comprising at least 90 credits
Degree project 30 credits
Advanced level courses passed at Chalmers comprising at least 45 credits
Courses (including degree project) within a major main subject 60 credits
Fulfilled course requirements according to the study programme
The prior award of a Bachelors degree, Bachelors degree in fine arts, professional or vocational qualification of at least 180 credits or a corresponding qualification from abroad.
See also the Local Qualifications Framework - first and second cycle qualifications
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Title of degree:
Master of Science (120 credits). The name of the Master's programme and the major subject Information Technology are stated in the degree certificate. Specializations and tracks are not stated.
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Major subject:
Software Engineering
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| Other information: |
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More information about the programme (url):
https://www.chalmers.se/en/education/programmes/masters-info/Pages/Data-Science.aspx
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