Program Overview
This part-time, online program equips students with in-demand data analytics skills through real-world dataset analysis. It covers both practical applications and theoretical underpinnings, enabling graduates to apply their knowledge effectively in careers such as Data Analyst, Data Engineer, and Data Scientist. The program is accessible to individuals without prior computing knowledge and offers flexible study options to fit work and personal commitments.
Program Outline
Degree Overview:
Objectives:
- Equip graduates with the skills and knowledge needed for real-world careers in data analytics.
Description:
This 100% online and part-time program aims to develop in-demand data analysis skills through the analysis of real-world datasets to help businesses make informed decisions. Students who lack prerequisite computing knowledge can still successfully participate in the program. The curriculum focuses on both the practical application and theoretical underpinnings of data analysis, enabling graduates to apply their skills effectively.
Outline:
Program Content:
The program focuses on developing a strong foundation in computer science, including the theoretical, engineering, and scientific aspects of the discipline. Students acquire essential skills and knowledge to understand and apply various programming languages and paradigms.
Data analytics:
Students develop expertise in data analytics and the ability to solve computational problems through coding.
Software development and engineering:
They gain proficiency in software development and engineering, as well as an appreciation for computer systems that implement these software solutions.
Electives:
Students have the opportunity to specialize further by choosing electives in programming, software engineering, artificial intelligence, or cybersecurity.
Course Schedule:
No specific course schedule is mentioned. However, the program is offered online and is flexible to fit students' work and other commitments. There are no formal start dates, allowing individuals to begin their studies any time during the year after being admitted.
Modules:
Programming and Algorithms: This foundation module introduces students to procedural programming, data structures, and algorithms and equips them with problem-solving skills using computer programs.
Web Technologies: Students gain theoretical and practical understanding of web technologies, learn to create web applications, and explore a range of technologies to understand the current web landscape.
Object Oriented Programming: Building upon foundations from module 1, this module delves into object-oriented programming concepts and encourages practical application through an object-oriented programming language.
Databases: Students explore and learn to build relational databases, the most common type.
The module also covers non-relational databases and their contrasts to relational databases.
Big Data Analytics and Visualisation: Students learn key concepts of big data analytics, its data sources, data mining, and the various applications of data analysis within various contexts, such as business.
They also explore data visualization techniques and tools.
Artificial Intelligence: Students delve into Artificial Intelligence (AI) principles and learn which problems are well-suited for AI solutions.
They explore different forms of knowledge representation, manipulation, and search, as well as artificial neural networks for learning from patterns in data sets.
Cloud Computing: Students gain insights into cloud computing concepts, explore the technologies that build cloud systems, and learn how these technologies enable on-demand computing for various applications.
Additionally, they learn to develop cloud applications using common technologies.
Statistical Data Analytics: This module builds on knowledge gained in the Big Data Analytics and Visualisation module.
Students explore the statistical principles applied in data analytics and learn to apply these using a suitable statistical programming language. They cover graphical and numerical methods for understanding data and later transition to data handling and inferential statistics.
Individual Project: Students undertake an investigation into a chosen topic of their choice, conducting independent work that demonstrates their acquired knowledge and skills.
This project can focus on developing a significant software product, gaining deeper knowledge in a specific area of the program, or researching other areas of interest.
Electives: Students can select two elective modules from the following:
- Human Computer Interaction: Learn both theoretical and practical knowledge and skills in human-computer interaction (HCI). This module equips students with essential skills to understand users of interactive systems and design user-friendly systems using a user-centered approach. Students learn and apply design and evaluation techniques used in the industry.
- Software Engineering: Learn key software engineering process concepts within a practical framework. This module introduces the wide spectrum of issues related to software system design and builds upon object-oriented programming concepts by studying another programming language commonly used in large enterprises. Students further develop their object-oriented programming abilities and learn to apply common software engineering principles to build applications.
- Computer Systems and Networks: Gain understanding of computer systems and networking principles through explorations of computer architectures, operating systems, and networks. Learn the purpose of operating systems and how they support resource sharing and concurrency. The module also teaches how to qualitatively and quantitatively assess issues affecting computer systems performance and programs running on them.
- Cybersecurity: Understand the different techniques for protecting information systems against cybercrime in the modern internet.
Careers:
Potential Career Opportunities for Graduates of the Program:
- Data Analyst
- Data Engineer
- Business Intelligence Analyst
- Quantitative Analyst
- Data Scientist
Other:
Entry Requirements:
The program welcomes both recent graduates and mid-career professionals looking to upskill and enter the digital sector, even without a related background.
English Language Requirements:
Applicants may need to demonstrate English language proficiency through tests like IELTS Academic (6.0) or TOEFL IBT (80).
Program Duration:
Study Mode:
Part-time, 100% online
Flexible payment : Pay per module Next start date : Start immediately Fee per 15-credit module : £650 Total Credits : 180
