Today, the demand for data scientists outstrips supply. Many global industries continuously demand for qualified and talented graduates in this field. In 2019, LinkedIn ranked “data scientist” the number one most prominent job in the U.S. based on job openings, salary, and career advancement opportunities. With this qualification, students will be equipped with the skills set and technical knowledge relevant for the data science job market. More importantly, they will gain skills of a data storyteller which adds value to a data scientist’s job.
This course combines mathematics, statistics, computer applications for data science, economics, finance, accounting, management, and communication in English. 50% of the time is allocated to practical work. Students will be introduced to business organisations and industries from the beginning. They will understand how these organisations function, the type of data they have, the type of data analyses that they need. Then they will work with these industries to analyse their data and show them solutions to their problems. In doing so, students will go through the full cycle of data science through practical tasks.
By the end of the course, students will be ready to join the industry without any additional training. They will be the best data-analysts that the industry can have.
This novel interdisciplinary course has been designed with the help of academics in reputed UK universities and industry experts.
Local students
G.C.E. (Advanced Level) –Three Simple Passes (S) in Mathematics, Bio Science, Technology or Commerce streams, pass in the Common General Test and at least a Credit pass for English and Mathematics in the G.C.E. (O/L) examination
Those who have taken Statistics and/or Economics as a subject/subjects in the Arts stream can also apply.
OR
Equivalent qualifications.
Foreign nationals
Equivalent qualifications (E.g. Cambridge or Edexcel).
*A bridging programme will be conducted to those who do not come from an A/L mathematics background.
**There will be a selection test in English for all applicants.
Year 1
Fundamentals of mathematics
Fundamentals of programming with R
Business economics
Effective presentation skills
Fundamentals of statistics
SQL for data science
Essence of management and organizational behaviour
Citizen science and communication
Year 2
Fundamentals of data mining
Programming with Python
Accounting and finance
Effective writing skills
Applied machine learning
Advanced SQL and Cloud Databases
Operations management
Research methods and research presentations
Year 3
Data science applications and artificial intelligence
Data visualization and storytelling
Policy analysis
Corpus analysis and data presentation
Industry sponsored dissertation
Industrial training
Module Details
Fundamentals of mathematics
This module provides students with a foundation in fundamentals of mathematics necessary to understand calculus and algebra for data science.
After completion of this module, students will be able to:
- apply core calculus for data science.
- apply matrix algebra for data science.
- apply implementation of matrix and calculus in R programming language.
Fundamentals of programming with R
In this module, we aim to provide fundamental skills in using the latest version of R programming language for data science.
After completion of this module, students will be able to:
- express fundamental programming concepts.
- write clean and concise code with R.
- explore data with R.
- process data with R.
Business economics
The aim of this module is to provide a thorough introduction to the discipline of Economics. The module is divided into two parts and in the first part, the course will cover microeconomic analysis, including the theory of demand, costs and pricing under various forms of industrial organisation, and welfare economics. The second part focuses on macroeconomic analysis and will include national income analysis, monetary theory, business cycles, inflation, unemployment, and the great macroeconomic debates.
After completion of this module, students will be able to:
- express theory of demand, costs and pricing under various forms of industrial organisation, and welfare economics.
- follow national income analysis, monetary theory, business cycles, inflation, unemployment, and great macroeconomic debates.
Effective presentation skills
The aim of this module is to provide students with understanding of presentation skills needed for data storytelling. It focuses not only on verbal communication, but also on non-verbal communication, cultural aspects related to communication and how data visualization can make a significant change into communication.
After completion of this module, students will be able to:
- use diverse presentation tools.
- do effective presentation applying the presentation skills learned.
- analyse features of data stories in different disciplines.
- analyse barriers to data communication in a range of contexts and propose solutions.
Fundamentals of statistics
This module provides students with a foundation in basic statistics and probability. The module lays foundations for data analysis.
After completion of this module, students will be able to:
- apply data summarization techniques.
- apply probability concepts.
- apply probability distribution functions.
- assess relationship between variables.
- apply hypothesis testing.
SQL for data science
The aim of this module is to provide students the foundational concepts of databases and SQL (Structured Query Language).
After completion of this module, students will be able to:
- design a database.
- create databases and schemas in SQL Server and query records using T-SQL.
- explore various techniques to retrieve data from multiple tables.
- create tables, views and stored procedures and query multiple tables by using joins.
- add, update, and delete data in the SQL server databases and join, filter, group, and sort results.
Essence of management and organizational behaviour
The aim of this module is to provide an understanding of the essential components of how organisations behave and how to manage them. The four essential components of management, i.e. planning, organizing, leading and controlling are covered in the content.
After completion of this module, students will be able to:
- identify main features of an organization, and how organisations behave and organsations’ relationships with external bodies.
- identify the factors that govern organisations and the behaviour of managers.
- examine how decision making happens within an organization.
- examine how organizational problems are identified and the process of conflict resolution and negotiation.
- identify the learnership styles.
Citizen science and communication
The aim of this module is to introduce the concept of citizen science and the importance of effective communication in citizen science projects. This explores the possibility of how people who are not data scientist can use data science tools and techniques to improve the use of information in their respective fields. The module will discuss aspects such as open science, participatory science, citizen science in the digital age etc. Students will also learn the basics of designing citizen science projects and how effective communication is crucial in citizen science projects.
After completion of this module, students will be able to:
- apply the basic principles of citizen science in evaluating citizen science projects.
- use effective communication techniques to communicate with diverse audiences.
- accurately communicate rules and regulations involved in ethics and data protection.
- plan and execute a citizen science project.
Fundamentals of data mining
This module provides students with data mining and predictive modelling concepts including clustering, classification and association rule mining techniques.
After completion of this module, students will be able to:
- examine core data mining concepts.
- examine data mining process and standards.
- learn key differences between supervised and unsupervised learning techniques.
- apply data mining concepts in real-world problems.
- create prediction models.
- perform data mining in practical terms, using a wide variety of R libraries and techniques.
Programming with Python
Python programming is one of the most demanded skill sets in today’s job market. In this module, we aim to provide fundamental skills in Python language.
After completion of this module, students will be able to:
- implement basic Python code.
- input and output data from a variety of data types.
- load data from files or from internet sources.
- implement data engineering techniques.
- combine, manipulate and visualize complex dataset.
- automate essential tasks with Python scripts.
Accounting and finance
This is an introductory course in accounting and finance. The first part of the course will provide an introduction to financial accounting concepts and financial reporting, with the focus being on how decision makers analyse, interpret, and use accounting information. Emphasis is given to how accounting measures, records, and reports economic activities for corporations and on the relationship between accrual and cash flow measures in interpreting accounting information.
In the second part, students learn how to value assets and businesses given forecasts of future cash flows. The course also concentrates on the risk characteristics of different asset classes. The course focuses on stocks, bonds and interest rates in addition to measuring and pricing risk. Further, the course introduces students to valuation and derivative instruments. This course will combine the theoretical underpinnings of finance with real-world examples.
After completion of this module, students will be able to:
- examine financial accounting concepts and financial reporting, with the focus being on how decision makers analyse, interpret, and use accounting information.
- examine how accounting measures, records, and reports economic activities for corporations and on the relationship between accrual and cash flow measures and interpreting accounting information.
- analyse value of assets and businesses given forecasts of future cash flows. Further, they will be able to examine the dynamics of stocks, bonds and interest rates in addition to measuring and pricing risk.
Effective writing skills
The aim of this module is to provide students with understanding of essential writing skills for business and organisations. It also makes students be able to use communication effectively for data storytelling in writing.
After completion of this module, students will be able to:
- apply the features of technical business writing in drafting business documents.
- evaluate features of various types of documentations used in the government and non-government sector.
- use appropriate terminology in written communication in diverse fields.
- write data stories.
Applied machine learning
This module provides students with a foundation of machine learning techniques and its application. Machine learning techniques are the key skills that data scientists need to process and filter the data, to detect new patterns or anomalies within the data, and gain deeper insight from the data.
After completion of this module, students will be able to:
- examine core machine learning concepts
- apply machine learning concepts in real-world problems
- prepare data for machine learning
- evaluate models and improve their performance
Advanced SQL and Cloud Databases
The aim of this module is to provide students the exposure to advanced SQL concepts (Structured Query Language) using T-SQL and introduction to cloud databases.
After completion of this module, students will be able to:
- experiment with data analytics using advanced queries.
- import and export data from multiple difference sources using SQL queries.
- discover how to work with and manipulate large datasets using advanced SQL quarries.
- speed up data analysis workflow by automating tasks and optimising queries.
- evaluate cloud database concepts.
- assess how to backup, restore, secure, and scale cloud databases.
Operations management
The aim of this course is to provide an overview on operations management and make students aware of the systems and process perspectives. Students will be exposed to various operations management tools such as lean management.
After completion of this module, students will be able to:
- identify the basic principles behind operations management.
- assess how operation systems are planned.
- identify operations management tools.
- identify key features in operations strategy, analysis, design, planning and control.
Research methods and research presentations
The aim of this module is to provide students with understanding of research methods needed to engage in an independent research study in the field. This includes both quantitative and qualitative methods with especial emphasis on quantitative methods.
After completion of this module, students will be able to:
- evaluate the fundamentals of qualitative and quantitative research methods.
- apply research methods in designing, executing and presenting an independent research study.
- present qualitative and quantitative data in research.
Data science applications and artificial intelligence
During this semester, students will be able to apply the knowledge they have gained in previous semesters by working on real data science cases together with leading organizations. Also, this module aims to provide students with a broad overview of Artificial Intelligence. AI has the potential to replicate humans in every field. This module serves as a starting point for students to understand how AI is built, with the help of intriguing and exciting examples. This module makes students adaptive thinkers and help them apply Data Science and Artificial Intelligence concepts to real-world scenarios.
After completion of this module, students will be able to:
- apply neural networks to a varied set of applications.
- demonstrate knowledge on how Data Science and Artificial Intelligence are applied in real world scenarios.
- develop decision-making abilities with a variety of Data Science and Artificial Intelligence techniques.
Data visualization and storytelling
This module aims to provide students with a broad overview of the general field of data visualization and visual analytics.
After completion of this module, students will be able to:
- evaluate fundamental concepts and conventions of data visualisation techniques.
- implement different plotting techniques to produce compelling data visualisations.
- learn to create complex visualisation using R and Power BI.
- apply the basics of R and QGIS to work with GIS and remote sensing data.
- manage, manipulate, and analyse spatial data using R and QGIS.
Policy analysis
The course aims at enhancing the students’ ability for logical and structured problem analysis, their ability to present technical subjects clearly, and their ability to assess real-life economic issues relating them to their studies.
After completion of this module, students will be able to:
- appraise how the current competition and environmental policies relate with the findings of academic research in Economics.
- critically assess their impact in terms of efficiency and feasibility.
Corpus analysis and data presentation
The aim of this module is to provide students with an introduction to corpus linguistics and presenting data extracted from different corpora. It focuses on corpus tools and on using corpora in diverse fields.
After completion of this module, students will be able to:
- interpret the basic features of corpus tools and corpus analysis.
- use corpus tools to analyse language features.
- effectively present the data extracted from corpora
Industry sponsored dissertation
Dissertation will be given 4 credits. This includes a piece of original research based on data taken from the industry. Students are expected to submit a report in a research paper format.
Industrial training
Students will be given internships in different organisations.
Full course fee
Degree programme | Fee | Installments |
ADSC | 1,200,000. 00 | 1st installment: 480,000.00 |
| | 2nd installment: 360,000.00 |
| | 3rd installment: 360,000.00 |
Payment options
Payments can be made in instalments.
Student loans
Student loans are available via Local Banks.
