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Data Science and Artificial IntelligenceMain Subject Area
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Data Science programme is designed as a conversion master’s to introduce graduates from diverse backgrounds to the field of data science. The programme aims to provide a comprehensive foundation in data analysis, statistical methods, probability models, big data, machine learning and modern data imputation and processing technologies. Students will learn to extract insights from complex data sets, use machine learning algorithms, and apply predictive analytics in various sectors. T he course provides broad knowledge and practical skills needed to develop software systems to generate predictive, descriptive, diagnostic, preventive and prescriptive analytics from huge and complex real-world datasets. The practical skills include programming, analyses of algorithms, statistical & probabilistic techniques, neural networks, large language models, distributed processing and data science. The integral academic writing, research and project management skills and a mandatory independent dissertation/project in the final semester further underpin application of the industry-style professional approaches as well as an appreciation of future directions of technological advances and research. T he balanced academic preparation is aligned with emerging trends in job market and allows graduates to pursue in-demand and lucrative careers in IT industry or assume interdisciplinary roles by effectively combining applied computing with their first degrees. The course also provides foundations and opportunity to progress to and formally pursue specialized computer science research on a Ph.D. programme
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Data Science programme is designed as a conversion master’s to introduce graduates from diverse backgrounds to the field of data science. The programme aims to provide a comprehensive foundation in data analysis, statistical methods, probability models, big data, machine learning and modern data imputation and processing technologies. Students will learn to extract insights from complex data sets, use machine learning algorithms, and apply predictive analytics in various sectors. T he course provides broad knowledge and practical skills needed to develop software systems to generate predictive, descriptive, diagnostic, preventive and prescriptive analytics from huge and complex real-world datasets. The practical skills include programming, analyses of algorithms, statistical & probabilistic techniques, neural networks, large language models, distributed processing and data science. The integral academic writing, research and project management skills and a mandatory independent dissertation/project in the final semester further underpin application of the industry-style professional approaches as well as an appreciation of future directions of technological advances and research. T he balanced academic preparation is aligned with emerging trends in job market and allows graduates to pursue in-demand and lucrative careers in IT industry or assume interdisciplinary roles by effectively combining applied computing with their first degrees. The course also provides foundations and opportunity to progress to and formally pursue specialized computer science research on a Ph.D. programme
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
MSc Data Science (conversion)
Birmingham Newman University, Birmingham, United Kingdom
24 monthsProgram duration
16,000 GBPTuition Fee/year
YesScholarships
Data Science and Artificial IntelligenceMain Subject Area
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Data Science programme is designed as a conversion master’s to introduce graduates from diverse backgrounds to the field of data science. The programme aims to provide a comprehensive foundation in data analysis, statistical methods, probability models, big data, machine learning and modern data imputation and processing technologies. Students will learn to extract insights from complex data sets, use machine learning algorithms, and apply predictive analytics in various sectors. T he course provides broad knowledge and practical skills needed to develop software systems to generate predictive, descriptive, diagnostic, preventive and prescriptive analytics from huge and complex real-world datasets. The practical skills include programming, analyses of algorithms, statistical & probabilistic techniques, neural networks, large language models, distributed processing and data science. The integral academic writing, research and project management skills and a mandatory independent dissertation/project in the final semester further underpin application of the industry-style professional approaches as well as an appreciation of future directions of technological advances and research. T he balanced academic preparation is aligned with emerging trends in job market and allows graduates to pursue in-demand and lucrative careers in IT industry or assume interdisciplinary roles by effectively combining applied computing with their first degrees. The course also provides foundations and opportunity to progress to and formally pursue specialized computer science research on a Ph.D. programme
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Data Science programme is designed as a conversion master’s to introduce graduates from diverse backgrounds to the field of data science. The programme aims to provide a comprehensive foundation in data analysis, statistical methods, probability models, big data, machine learning and modern data imputation and processing technologies. Students will learn to extract insights from complex data sets, use machine learning algorithms, and apply predictive analytics in various sectors. T he course provides broad knowledge and practical skills needed to develop software systems to generate predictive, descriptive, diagnostic, preventive and prescriptive analytics from huge and complex real-world datasets. The practical skills include programming, analyses of algorithms, statistical & probabilistic techniques, neural networks, large language models, distributed processing and data science. The integral academic writing, research and project management skills and a mandatory independent dissertation/project in the final semester further underpin application of the industry-style professional approaches as well as an appreciation of future directions of technological advances and research. T he balanced academic preparation is aligned with emerging trends in job market and allows graduates to pursue in-demand and lucrative careers in IT industry or assume interdisciplinary roles by effectively combining applied computing with their first degrees. The course also provides foundations and opportunity to progress to and formally pursue specialized computer science research on a Ph.D. programme
Admission requirements
Exam Scores
Important Dates
Tuition fee and scholarships
Tuition Fee
Scholarships
Domestic Students
International Students
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
In this guide you will find:
Where to look for scholarship opportunities
How to apply to scholarships relevant to you
A list of available scholarships around the world
A scholarship application checklist
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