Master's

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

The skills of collecting, storing, transforming, mining and analysing data are essential for a professional working in the modern labour market of technology and innovation. This programme’s goal is to educate the engineers and scientists who will lead the ever growing and evolving industry, in which new job openings in the data fields (i.e. data engineers, data scientists, ML engineers, AI engineers, ETL developers, Business Intelligence experts, Big data experts, data analysts and others) are constantly available.

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

WHY CHOOSE THIS COURSE

Because the degree received is issued by the university of Sheffield, a university that is α listed among the 15 best in the UK.

Because this is the ideal course for software engineers and developers who wish to gain from emerging technologies and succeed in creating strategic growth, competitiveness, profit and value for the companies they work for.

Because it focuses on creating and developing engineers, scientists, experts and professionals who are ready to deal with hands-on cases and actual issues companies face in the complicated field of data

Because it provides a variety of employment options due to the great demand for graduates who combine ICT knowledge and skills. Graduates can start their own business or work in various fields or even begin an academic career

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

GOALS OF THIS COURSE
  • To teach the necessary techniques and skills on how to process a large amount of data and turn it into valuable information that will lead to the accomplishment of business objectives.
  • To provide specialisation for sectors that are in constant need of professionals with skills in big data engineering and data sciences.
  • To educate on the principles of software engineering, a science that has different applications in our everyday life. Students will be taught how to create effective and updated software systems that keep up with the tech trends and the need of the actual labour market.
  • To focus on industrial models approved and needed by businesses so that students will be efficiently prepared for a career in every field relating to IT.
  • To cοnduct research and compose a thesis under the supervision of the faculty.
  • To create the leaders of the business world.
  • To train students to conceive, develop and create complex software systems.
  • To employ scientific personnel of experienced lecturers and researchers. The professors of Sheffield university have been long teaching in academic environments and have been involved in research groups and studies. Frequent seminars with guest speakers from the tech industry and the academic world complete the learning process.

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

CURRICULUM

Advanced Software Development Techniques

This unit presents advanced software development techniques within the context of a real world business environment. It focuses on: software engineering principles; agile development processes; object oriented analysis and design techniques (using the UML notation); object-oriented principles; and well-known design practices as design patterns.

Continuous and Agile Software Engineering

The aim of this unit is to present contemporary topics in Software Engineering. It starts with a brief overview of software engineering principles and then focuses on modern approaches to software development and management, software architecture, and advanced techniques as formal methods. Students will actively contribute to the lectures, by reviewing and presenting material on contemporary software engineering topics.

Industrial Group Project

The purpose of this unit is to provide students with the opportunity to integrate and apply the skills and the knowledge they have acquired so far in their studies to a realistic problem. Students are exposed to the processes involved in the team-based development of software through real projects that are provided by companies from the software industry.

Research Skills and Dissertation Preparation

This unit intends to introduce students to the research topics and techniques that are commonly employed in software engineering and telecommunication science. Students will be exposed to the principles of report writing, literature reviewing, and research designs and approaches. These research approaches will include the design of data collection and analysis methods, as well as representation and interpretation of the results. An introduction to tools facilitating quantitative and qualitative analysis will also be provided. The unit is enriched with a number of exercises, case studies and discussions and concludes with practical guidelines of how to write a successful dissertation.

Business Intelligence

Business intelligence (BI) systems are applications and technologies for gathering, storing, analyzing, and accessing information for better business decision-making. The application areas of such systems include measuring and monitoring key performance indicators, benchmarking and forecasting sales, performing data mining and analysis of customer information.
This course provides a comprehensive introduction to the concepts, components, techniques and applications of BI and related areas. Students will gain awareness, in a gradual manner, of the complete life cycle of implementing and managing BI systems.

Big Data Engineering

This unit explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments. Main aspects and challenges of Big Data will be addressed by introducing relevant algorithms, among others, in the areas of MapReduce, data stream mining and recommendation systems.
Additionally, this course provides a detailed description and hands-on experience to the cutting-edge open-source software Apache Hadoop and Apache Kafka.
Students will be introduced and gain awareness, in a granual manner, to the concepts, algorithms and techniques that cover key Big Data topics.

Data Mining and Machine Learning

This unit addresses the contemporary aspects, algorithms and challenges of mining big data by introducing data mining and machine learning algorithms. The unit aims to provide students with the necessary skills, knowledge and hands-on experience regarding data exploration, data preprocessing, visualization, unsupervised machine learning algorithms, clustering and other contemporary topics like dimensionality reduction, anomaly detection, pattern recognition, association rules and recommendation systems.

Advanced Artificial Intelligence Techniques

This unit starts with an in-depth introduction to Artificial Intelligence problem solving techniques and covers contemporary and advanced AI algorithms and application area. Main aspects and challenges that will be addressed by introducing relevant theory and hands-on practical sessions include search algorithms (brute-force, heuristic), supervised Learning Algorithms, Neural Networks, Deep Learning, Natural Language Processing and image classification.

DevOps Engineering

This unit explores a range of the most relevant topics that pertain to devops engineering scope. Main aspects and challenges of the contemporary DevOps Engineering field will be addressed by introducing relevant theory and practices in the areas of infrastructure and configuration management (on-premises and cloud), continuous pipelines, containers and orchestration. Additionally, this course provides a detailed description and hands-on experience to the cutting-edge open-source platforms that are used for the aforementioned purposes.

Dissertation

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

INFORMATION + PREREQUISITES
STARTING DATES

1st semester (October)
2st semester (February)

DURATION

2 Years (Part Time)

LANGUAGE OF INSTRUCTION

English

SCHEDULE

Block teaching: Two weekday evenings per week and two Saturdays per semester

PREREQUISITES FOR ENROLLING

Candidates should hold an undergraduate degree in Computer Science, Computer Engineering, or any other related ICT discipline.

Proof of fluency in English is provided by showing:

  • CAE: Grade A or B or
  • IELTS: Grade 6.5 or above or
  • TOEFL (paper based 575 / internet based 89-90) or
  • Equivalent or Higher Qualification

Candidates who have completed their Bachelor’s studies or their higher secondary education entirely through the medium of the English Language are not required to hold an English language qualification.

MSc in Advanced Software Engineering – Big Data Engineering & Data Sciences

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