BSc Hons Accounting and Management
Queen Mary University of London's BSc-Hons- Accounting and Management program ...
MSc Data Analytics
Mile End
INTAKE: September
Program Overview
The MSc Data Analytics program at Queen Mary University provides students with a comprehensive understanding of data analytics concepts, tools, and techniques.
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Data Analysis Fundamentals: Students gain a solid foundation in data analysis, learning about data types, data cleaning, and exploratory data analysis.
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Statistical Modeling: The program covers statistical techniques for modeling and analyzing data, enabling students to uncover patterns and trends.
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Machine Learning: Students delve into machine learning algorithms and methods, allowing them to develop predictive and classification models.
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Big Data Technologies: The program explores technologies used to handle and process large-scale datasets, including distributed computing and cloud platforms.
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Data Visualization: Students learn how to effectively visualize data and communicate insights through graphs, charts, and interactive dashboards.
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Database Management: The program covers database design and management, essential for storing and retrieving data efficiently.
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Ethics and Privacy: Students explore the ethical considerations and privacy concerns associated with handling and analyzing data.
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Real-World Projects: Practical projects and case studies provide students with hands-on experience in solving data analytics challenges.
Location
Mile End
Score
IELTS 6.5
Tuition Fee
£ 28950
Postgraduate Entry Requirements:
- Applicants should have successfully completed a bachelor's degree or its equivalent from a recognized institution with a minimum overall score of 60% or equivalent.
- English language proficiency is required, and applicants must provide evidence of their English language skills through an approved language test.
- IELTS: A minimum overall score of 6.5 with no individual component below 6.0.
- TOEFL: A minimum overall score of 92, with at least with at least 17 in Listening, 18 in Reading, 20 in Speaking, and 21 in Writing.
- PTE Academic: A minimum overall score of 71 with 65 in Writing, and 59 in Reading, Listening and Speaking..
- Some postgraduate programs may have specific subject prerequisites or additional requirements.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
Work experience: Some postgraduate courses may require relevant work experience in the field.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
Queen Mary University of London offers a range of scholarships and bursaries to its students.
- Queen Mary International Excellence Scholarships: A scholarship program for international undergraduate and postgraduate students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full tuition fees for one year of study.
- Queen Mary Law Scholarships: A scholarship program for undergraduate and postgraduate law students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
- Queen Mary Engineering and Materials Science Scholarships: A scholarship program for undergraduate and postgraduate students studying engineering or materials science who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
The MSc Data Analytics program opens up a multitude of rewarding career opportunities in today's data-driven world. Graduates are equipped with the skills to excel in various industries and roles.
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Data Analyst: Graduates can work as data analysts, extracting valuable insights from data to inform business strategies and decision-making.
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Data Scientist: Graduates may pursue roles as data scientists, utilizing advanced analytical techniques to solve complex problems and create predictive models.
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Business Intelligence Analyst: Graduates can become experts in business intelligence, helping organizations make informed choices based on data-driven insights.
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Machine Learning Engineer: Graduates with a focus on machine learning can work on designing, building, and deploying machine learning models for automation and prediction.
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Data Engineer: Graduates may pursue careers as data engineers, responsible for the design and maintenance of data pipelines and infrastructure.
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Quantitative Analyst: Graduates interested in finance can become quantitative analysts, using data analytics to assess financial risks and opportunities.
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Marketing Analyst: Graduates can work in marketing analysis, using data to understand consumer behavior and optimize marketing campaigns.
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Healthcare Data Analyst: Graduates may find opportunities in healthcare, analyzing patient data to improve medical treatments and outcomes.
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Consultant: Graduates can become data analytics consultants, providing expertise to organizations seeking to harness the power of data.
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Academic Researcher: Graduates may pursue further studies or research positions in academia, contributing to advancements in data analytics.
