Master of Computer Science by LSMT London

Data Science Foundations

Data science combines powerful computing technology, sophisticated statistical methods, and expert domain knowledge to analyse and gain practical insights from huge amounts of data produced by organisations in the present business environment. The aim of this module is to introduce a range of data science concepts, data administration and governance and big data sources.

Data Mining, Machine Learning and Artificial Intelligence

This module is designed to introduce the science behind machine intelligence and the philosophical debate around the ambitions of simulating human intelligence to solve real-world problems. Students will be guided to appreciate AI types and applications and develop a better understanding of aspects related to intelligent agents. In this module students will master key concepts and gain the practical knowledge to apply machine learning principles to challenging real-world problems.

Data Analysis and Visualisation

The Data Analysis and Visualization module equips students with the skills to analyse complex data sets and present insights in a clear and compelling visual format. The course covers various data analysis techniques, including descriptive and inferential statistics, as well as data cleaning and transformation methods. Students will learn to use software tools such as Excel, Python (with libraries like Pandas, NumPy, and Matplotlib), and Tableau to manipulate, analyse, and visualise data effectively. By the end of the module, students will be able to identify patterns, trends, and anomalies in data, and communicate their findings through impactful visual representations, supporting decision-making processes in business and research contexts.

Probability and Statistics for Data Analysis

The Probability and Statistics for Data Analysis module provides students with foundational knowledge in probability theory and statistical methods, focusing on their application in data analysis. Topics include probability distributions, hypothesis testing, regression analysis, and statistical inference techniques. The module emphasises the practical use of statistical tools to analyse and interpret data, helping students develop the skills necessary for making data-driven decisions. Real-world case studies and hands-on exercises using software such as R or Python will be incorporated to enhance students' ability to perform statistical analysis and draw meaningful conclusions from data.

Advanced Computing Research Methods

The aim of this module is to develop learners' ability to prepare for various types of academically based computing research through the development and design of a research proposal. Learners will develop a critical understanding of the philosophical, practical, and ethical concepts of research within the context of computing discipline.

Internet of Things and Cryptography

This extensive module provides definitions of important terminologies about Internet of Things (IoT) and Cryptography. Students will explore the intricate relationship between the IoT and cryptography, gaining a profound understanding of how cryptography plays a pivotal role in securing the expansive network of interconnected devices that constitute the IoT ecosystem. This module will provide you with a comprehensive theoretical foundation on how cryptographic techniques are applied to IoT environments, ensuring their security and privacy.

Networking and Kali Linux

The Networking and Kali Linux module provides students with a comprehensive understanding of networking fundamentals and hands-on experience with Kali Linux, a powerful platform for penetration testing and cybersecurity. Students will learn about network protocols, IP addressing, subnetting, routing, and switching, as well as how to configure and secure networks. The module will also cover the use of Kali Linux tools for ethical hacking, including information gathering, vulnerability scanning, and exploitation techniques. Through practical exercises, students will develop the skills necessary to assess and secure networks in real-world environments.

Engineering of Hacking

The Engineering of Hacking module focuses on the techniques, tools, and methodologies used in ethical hacking and penetration testing. Students will learn how to identify, exploit, and defend against vulnerabilities in various systems, including networks, web applications, and devices. The module emphasises hands-on practice with tools like Kali Linux to perform real-world hacking simulations and understand cybersecurity concepts. By the end, students will be able to apply ethical hacking principles to assess and improve system security.

Forensic Computing

The Forensic Computing module provides students with the knowledge and skills required to investigate and analyse digital evidence from a variety of sources. It covers topics such as data acquisition, evidence preservation, cybercrime investigation, and legal considerations in digital forensics. The module focuses on the application of forensic tools and techniques to solve real-world cybercrime cases, ensuring students understand both technical and ethical aspects of forensic computing.

Application and Device Audit

The Application and Device Audit module focuses on the methodologies and techniques for auditing software applications and devices within organisational environments. Students will learn how to assess security, compliance, and performance of various applications and devices, identifying vulnerabilities and potential risks. The module emphasises practical tools and real-world scenarios for conducting effective audits, ensuring the integrity and security of IT systems.