Why Study this course?
MSc IT programme with a specialisation in Data Analytics offers the opportunity to develop theoretical, technical, and practical competencies in this rapidly growing field. In today's data-driven era, organisations across industries are increasingly relying on data analytics to gain valuable insights and make informed decisions. By focusing on data analytics, you can acquire the skills needed to collect, analyse, and interpret data, providing actionable information for businesses.
This programme emphasises a combination of academic learning, practical experience, and staying up-to-date with current developments in the field. By studying data analytics, you position yourself in a very high-demand field, where you can contribute to the success of organisations by leveraging the power of data.
* The full course has been developed and delivered by Islington College and has been evaluated and deemed by London Metropolitan University to be of an equivalent standard and quality to that of its own provision, and therefore suitable to lead to one of its own awards.
Entry Requirement
A second lower-class Honours IT-related degree from any recognised university or IT-related degree graduates from Tribhuvan, Kathmandu, and Pokhara University with a Minimum GPA 3.0. All other qualifications are evaluated on a case-to-case basis and subjected to approval by London Metropolitan University.
A related undergraduate degrees plus related employment, or consultancy within the field can be considered alongside the portfolio and statement.
Course Content
Semester 1
The module develops an understanding of project management issues in the context of software development – including the consideration of a standard method, software development frameworks, financial evaluation, planning, monitoring, control and team management – together with the ability to apply these as appropriate to a business case study.
This module aims to provide students with an appreciation of the benefits of Cybersecurity Management within a business environment and over cyber space. This includes the choice and application of appropriate risk assessment and risk control techniques, the understanding of security standards & procedures, coupled with the application of cybersecurity technology & security measures in a business setting.
Semester 2
This module enables students to gain understanding of programming principles, develop students’ knowledge and skills in programming design and coding, expertise in data manipulation and presentation for data analysis, and enhance students’ skills for integrative reasoning, problem-solving and critical thinking.
The module will primarily provide students with a good understanding of database concepts and management system in reference to modern enterprise-level database development. Most importantly, this module will deliver students a broad understanding of Big Data technologies including Hadoop based architectures, data ingestion, data transformation, data management, analytics and predictive analytics for manipulating and discovering insight. Topics include Hadoop, HDFS, MapReduce, Spark, Sqoop, Hive, Pig and MLlib.
Semester 3
The module aims to provide students with the opportunity to gain work experience and explore career opportunities. It focuses on work related projects and helps to enhance their learning experience by implementing their academic skills to tackle real life problems in workplace.
The aims of this module are to enable students to gain understanding of fundamental concepts in data analysis and visualisation, develop student expertise in descriptive statistics, correlation analysis, and linear regression model.
Semester 4
The module aims to widen opportunities to stimulate the knowledge students gain in their course and extend knowledge to new area of application. It directs student to determine framework of the project according to a set of specifications relevant to the subject of study.
How this course will help
the students?
Career Prospects
Big Data Specialists | Project Managers | IT Systems Analysts | Data Scientists | AI and Machine Learning Specialists
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