Data Analytics - MSc

Program Overview

The Data Analytics MSc program at London Metropolitan University equips graduates with the skills to succeed in today's data-driven world. The program focuses on data science, big data analytics, and business intelligence, preparing students for careers as data analysts in various industries. Graduates gain expertise in industry-standard software tools and apply their skills to real-world business problems through case studies and projects. The program is accredited by BCS, The Chartered Institute for IT, and the Engineering Council, ensuring high academic standards and industry relevance.

Program Outline

Degree Overview

The Data Analytics MSc program at London Metropolitan University equips graduates with the theoretical, technical, and practical skills required to succeed in today's data-driven world. This program focuses on providing students with a strong foundation in data science, big data analytics, and business intelligence, preparing them for rewarding careers in various industries and sectors that require skilled data analysts.

Objectives:

• Equip graduates with advanced knowledge and skills in data analysis, mining, visualization, and interpretation.
• Develop expertise in using industry-standard software tools, including R, Python, SQL, and SAS.
• Enable graduates to apply their skills to real-world business problems through case studies and projects.

Modules:

• Data Analysis and Visualization: Covers fundamental concepts and practical techniques for data exploration, analysis, and visualization.
• Data Mining and Machine Learning: Introduces students to data mining algorithms, machine learning models, and their application in various scenarios.
• Financial Mathematics: Explores mathematical methods used in financial calculations and project valuation, including Discounted Cash Flow and Real Options methods.
• Statistical Modelling and Forecasting: Introduces advanced statistical techniques for prediction and forecasting, utilizing R statistical software and relevant libraries.
• MSc Project: Culminating experience where students conduct independent research and apply their skills to a chosen project, demonstrating their critical and analytical abilities.

Assessment

The Data Analytics MSc program utilizes multiple assessment methods to evaluate students' learning outcomes. Here's a breakdown:

Assessment Methods:

• Written reports and research assignments: Assess students' ability to analyze data, interpret findings, and communicate their insights effectively.
• Demonstrations and presentations: Evaluate students' presentation skills, communication abilities, and understanding of data analysis concepts.
• Group projects and assignments: Assess collaboration skills, teamwork, and the application of data analysis skills in group settings.
• Practical exercises and lab work: Evaluate students' practical skills in using data analysis tools and techniques.
• Examinations: Assess students' theoretical knowledge and understanding of key concepts in data analysis, data mining, and statistical modeling.

Teaching

Teaching Methods:

• Interactive lectures: Facilitate knowledge acquisition and understanding of key concepts.
• Practical workshops and labs: Provide hands-on experience with real-world data and tools, promoting practical skill development.
• Case studies and project work: Apply theoretical concepts to real-world scenarios, fostering problem-solving and analytical abilities.
• Group discussions and seminars: Encourage active learning, critical thinking, and participation in collaborative settings.
• Individual and group supervision: Offer personalized support and guidance on project work and research assignments.

Faculty:

• Experienced and knowledgeable faculty with expertise in data analysis, machine learning, statistics, finance, and programming.
• Active research involvement and strong industry connections, ensuring the program aligns with current industry trends and practices.

Unique Approach:

• The program utilizes real-world data resources, case studies, and industry partnerships to provide students with practical experience and prepare them for real-world challenges.
• Access to industry-standard software and tools, including R, Python, SQL, SAS, Oracle, and Hadoop, enhances employability and equips students for the current job market demands.
• The program emphasizes critical thinking, problem-solving, and communication skills, preparing students to excel in various professional settings.

Careers

Career Opportunities:

• Data Analyst
• Data Scientist
• Big Data Analyst
• Business Intelligence Analyst
• Data Engineer
• Data Visualization Specialist
• Research Analyst

Potential Industries:

• Financial Services
• Technology
• Healthcare
• Manufacturing
• Retail
• Public Sector
• Research and development

Other

• The program is accredited by BCS, The Chartered Institute for IT, and the Engineering Council, signifying its adherence to high academic standards and industry-relevant skills development.
• Graduates are prepared for additional professional certifications, such as the Oracle Professional Certification.
• Opportunities for international students to gain real-world experience through internships or placements with local companies.