MSc Business Analytics (Online)Imperial College Business School
MSc Business Analytics (Online)
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MSc Business Analytics (Online)
MSc Business Analytics (online delivery, part-time) is a 22 month, part-time programme, delivered via our purpose-built online learning platform, The Hub. Although grounded in highly rigorous technical and quantitative training and the latest academic thinking, you will focus on the practical side of business analytics. This programme will prepare you for a future of evidence-based decision making.
To apply for MSc Business Analytics you should have a First or Upper Second Class Honours undergraduate degree from a recognised university or the international equivalent in a quantitative discipline such as:
- Computer science
- A quantitative economics degree
We may consider candidates applying to MSc Business Analytics (online delivery, part-time) with non-traditional qualifications and backgrounds, on the basis of highly relevant work experience or demonstrated interest. If you come from a less quantitative degree background we advise you to take the GMAT or GRE test to demonstrate your quantitative ability. If you do not meet the requirements listed above please contact the Admissions team to discuss your eligibility.
Prerequisite knowledge requirements
Your quantitative experience should typically include topics such as advanced calculus, probability, statistics and linear algebra.
Complete our online Maths test to determine if you are suitable to apply for the programme.
GMAT is not required for MSc Business Analytics, but a well-balanced GMAT result with 650 or higher overall and a good result in the quantitative reasoning section will add weight to you application.
The most common ways that applicants meet the requirements are:
- IELTS (academic): A minimum score of 7.0 with minimum scores of 6.5 in all elements. The IELTS indicator test will be accepted for admissions to the 2020/21 academic year.
- TOEFL iBT: A minimum score of 100 overall with minimum scores of 22 in all elements. The ETS at Home test will be accepted for admission to the 2020/21 academic year.
- Duolingo English Test: 125 Overall with no less than 115 in any band score.
- Degree studied in and awarded by an English-speaking country and English language assessed to be proficient via Kira Talent video interview.
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Core modules rapidly build the theoretical and programming foundations you need for analytics. They are the backbone of the programme and will provide you with a solid combination of tools and knowledge.
These modules are studied on campus by full-time students, and online for those studying the part-time programme.
Analytics in Business
This module surveys some of the most popular and widely used methodologies for drawing inferences from data, as well as common analytics fallacies (correlation vs. causality, paradoxes of high-dimensional data,etc.). The module also offers an overview of the technical infrastructure required for business analytics (e.g., distributed file systems and DBMS, cloud computing etc.).
Data Structures and Algorithms
This module introduces you to the design of algorithms and data structures for computational problem solving. The design of efficient computational methods for sifting through large data sets lies in the core of modern technological innovation ranging from search engines and social networks to healthcare, energy and finance. The module will familiarise you with key algorithm design paradigms and central concepts of computational complexity and running-time analysis. You will develop a working knowledge of basic algorithms (for problems such as search, sorting, and shortest paths) and data structures, along with the necessary programming constructs. The module will also serve as an introduction to the Python programming language, with the goal of becoming proficient in organizing and writing programs for practical problem-solving.
Fundamentals of Database Technolgies
This module introduces you to practical usage of databases with the main emphasis on SQL and related technologies. As big data problems are more and more prevalent for business, this module introduces basics of their processing with Apache Spark – a versatile, big data processing engine. This module will use PostgreSQL - one of the most popular and powerful object-relational database management systems.
This module will teach you basic analytics skills and methodologies for large-scale data analysis. It will focus on the practical use of these skills and methodologies to solve real world problems. The goal of the module is to enable you to be data-savvy, analytically minded and coding-literate problem solvers.
Maths and Statistics Foundation for Analytics
This rigorous module will teach you concepts of probability, statistics and linear algebra. You will learn to summarise and analyse data using statistical concepts and understand linear algebra to represent and manipulate data. This will ensure that you build a solid foundation of the mathematical concepts necessary to succeed on the programme. This module will also serve as an introduction to R.
Networks arise in many different contexts and a vast amount of networked data is now generated. For instance social networks such as Facebook and Twitter generate immense amount of data that is invaluable to marketers and businesses to obtain product feedback and do targeted marketing. This module covers algorithms, analysis and interpretation of network data and relationships.
Optimisation and Decision Models
Optimisation plays a key role in statistical, machine learning and business operational models. This module trains students on the fundamental optimisation tools available to the modeller and business analyst. You will obtain hands-on experience with the key modelling (AIMMS, GAMS, AMPL) and optimisation (CPLEX, GUROBI) software packages.
Statistics and Econometrics
This module provides an introduction to multiple regression analysis and related methods for analysing data in business applications.
This module covers a range of state-of-the-art methods and tools to visualise high-dimensional data. You will learn how humans process and perceive images, be introduced to the best practices for visualising patterns in large data sets, and get hands-on experience with state-of-the-art visualisation software packages.
Scholarships & funding
Several scholarship options are available. Please visit the institute website for more information.
You will complete your core modules, which provide the mathematical and computational foundations of analytics in the first year of your programme.
There are two on-campus periods in your first year where you will need to be in London for coding bootcamps, revision and exams. For September 2021 entry, there will be a one week visit in December 2021 and a one week visit in July 2022.
In your second year, you will focus on the application of the knowledge and skills learned in year one to real-world verticals such as healthcare, logistics and supply chain, finance or functional areas such as marketing, digital and human resources.
You will be expected to complete 10 to 15 hours of study a week. The number of hours may vary depending on your assignment deadlines, quizzes and exams.
The cost of tuition for this program is £32,500 for all students.
Graduates are typically employed in a variety of sectors in roles such as:
- Data Analytics Consultant
- Associate Analytics Consultant
- Business Analyst
- Technology Consulting Analyst
- Data Analyst
- Mobile Analyst
- Risk and Regulatory Analytics Analyst
About this institute
Imperial College Business School
At Imperial College Business School, we offer a range of programs to inspire intelligent and creative minds from a diverse range of backgrounds to be the world’s future business leaders. As part of Imperial College London, a global leader in...
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