Bsc. (Hons) Computing
Our computing degree is designed to produce graduates with a high level of knowledge across a variety of computing technologies.
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Msc.
Data Science and Computational Intelligence
Duration
2 Years - Full Time
Credits
160 Points
Intake
Spring/
Autumn
This course aims to respond the demand for data scientists with the skill to develop innovative computational intelligence applications, capable of analyzing large amounts of complex data to inform business decisions and market strategies.
Admission Eligibility
Students must have obtained at least 50% or equivalent marks in the undergraduate level
English Requirement
GETS English test (65 or above in all individual bands) Or IELTS 6.0.
Msc.
Data Science and Computational Intelligence
Duration
2 Years - Full Time
Credits
160 Points
Intake
Spring/
Autumn
Overview
MSc Data Science and Computational Intelligence programme is to fulfill the demand for data scientists with the skills to develop innovative computational intelligence applications. A graduate with MSc Data Science in Nepal can analyse complex data in bulk and help make important business decisions. One with MSc in Data Science degree is capable of building market strategies. The MSc data science and computational intelligence course covers machine learning, big data analysis, neural networks, information retrieval, and evolutionary computation. It provides you with opportunities to undertake practical projects and apply them to solve real-life problems in almost every field including business, marketing, finance, transportation, pharmaceutics, medicine, and management
Affiliated with Coventry University, this MSc data science programme helps you learn alongside active researchers in pervasive computing, distributed computing, and innovative applications for interactive virtual worlds.
Throughout the program, you learn automatic big data processing and information retrieval through cutting-edge machine learning techniques and become capable of analysing big datasets and performing advanced data mining tasks. You will be introduced to important frameworks including Hadoop Map Reduce, Spark, and NoSQL databases in combination with powerful development tools such as Python, Scala, Matlab and R.
The overall aim of the MSc Data Science and Computational Intelligence is to:
- Deliver advanced theoretical and practical subjects across a range of specialist areas in data science and computational the intelligence which is greatly demanded in a wide range of research and industrial applications.
- Enable students to enhance their analytical, problem solving, critical communication, and presentation skills in the context of their taught modules and develop the ability to analyze, evaluate and model complex problems involving large amounts of data.
- Advance the skills and knowledge acquired through previous study and experience in cutting-edge research and technologies and enhance students’ transferable and professional skills and, thereby, their employment prospects.
- Provide specialist skills and in-depth knowledge essential for graduates to develop and adapt to the challenges in the field of data science.
- Enable students to analyze and critique the central and current research problems in MSc data science and computational intelligence.
- Enable students to operate as effective independent researchers and/or consultants in their chosen specialized aspect of the course.
- Enhance the awareness of the professional, legal, ethical, and social issues along with commercial risk and management in the role of a data science professional.
- Enable students to adapt to future changes in technology in data science and computational intelligence areas.
Career Opportunities
- Data analysis and analytics
- Statistical analysis
- Machine learning algorithms
- Artificial neural networks
- Deep learning
- Big data management systems
- Research skills for advanced data science and computational intelligence
Modules
Applications of machine learning, Supervised / Unsupervised learning, Linear regression, Logistic regression, Regularisation, Support vector machine, Decision trees, Reinforcement learning, etc.
Database modelling, Relational models, Big-data, NoSQL databases, Database programming, Distributed databases, Transaction management, etc.
Search engines, Web crawlers, Query processors, Boolean model, Text classification, Document clustering, Link analysis, Multimedia information retrieval, etc.
Use of range of statistical distributions like binomial, Poisson, uniform, normal, exponential, gamma, etc. Multivariate distributions, Central limit theorem, Hypothesis testing, Bayesian inference, Regression models, etc.
Analytical review of database system and big data, Traditional database concepts for structured data, Big data methodologies for structured and unstructured data sets,
Big data analysis using examples from real life case studies and datasets. Big data processing and predictive frameworks. Data visualisation tools to support decision-making.
Supervised and unsupervised neural networks, Static and temporal neural networks, Deep neural networks, Hybrid and modular neural networks, Various neural networks, and their applications.
Gaussian processes, Dirichlet processes, Graphical models, Fuzzy sets, Adaptive and hybrid fuzzy systems, Evolutionary algorithms
Research skills, Research methodology, Reporting, Legal, Ethical and Social context
The project can be a solution to a practical industry requirement or focus on a research topic. It will require investigation and research as core activities, leading to analysis, final summations and insightful recommendations. The project will culminate in a comprehensive, thorough and professional report, documenting the approach, conduct and outcomes of the project, further supported with a critical review of the project conduct and management. It is intended that students will be given an opportunity to specialise in an area of interest, relevant and useful for future career prospects.
The project can be a solution to a practical industry requirement or focus on a research topic. It will require investigation and research as core activities, leading to analysis, final summations and insightful recommendations. The project will culminate in a comprehensive, thorough and professional report, documenting the approach, conduct and outcomes of the project, further supported with a critical review of the project conduct and management. It is intended that students will be given an opportunity to specialise in an area of interest, relevant and useful for future career prospects.
Why Coventry University?
An award-winning university, we are committed to providing our students with the best possible experience. We continue to invest in both our facilities and our innovative approach to education. Our students benefit from industry-relevant teaching, and resources and support designed to help them succeed. These range from our modern library and computing facilities to dedicated careers advice and our impressive Students’ Union activities.
Disclaimer: We regularly review our course content, to make it relevant and up-to-date for the benefit of our students. For these reasons, course modules may be updated, please contact us for the latest information
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Admission Eligibility
Students must have obtained at least 50% or equivalent marks in the undergraduate level
English Requirement
GETS English test (65 or above in all individual bands) Or IELTS 6.0.
