Postgraduate Certificate in Applied Data Science
The PGCert in Applied Data Science is a one year programme. It is an intensive course in applied data science for information professionals who wish to enhance their digital skills, including professionals across the cultural heritage, finance, banking, engineering, business, education, law, IT and management sectors. The programme will exhibit flexibility by providing students with skills related to their particular work-based environment. The coursework and exercises of the modules will be directly related to the information professionals' area, making the programme applicable to different sectors.
Key aspects of the programme
Study applied data science without having any prior experience and become a data scientist in just a year.
- Learn Python and machine learning tools to support your professional career by focusing on the applied data science aspects.
- Study an intensive programme in class for three months and develop your personal skills in the area of programming with Python and machine learning.
- Develop your personal project in applied data science with the guidance of a personal tutor.
The programme will provide professionals an understanding of basic programming and use of analytic tools to support them in their daily work. The work-based project module will allow professionals to apply their knowledge on a topic jointly agreed by the professional and/or their line manager in the area of applied data science. This module will provide an opportunity for the learner to demonstrate and apply their newly acquired knowledge of computational thinking for the benefit of the organisation. The resulting output of the project will be a data science project and a use case detailing the project requirements, realistic time frames together with the final deployment of the solution.
Students will gain broad knowledge of computer science, data science and software engineering, and acquire practical problem-solving and analytical skills, while also having the opportunity to investigate certain areas of current research more deeply. For students who are new to the subject, the programme provides a foundation for a career in the IT industry as a data scientist or analyst; for those already working in IT, it provides an opportunity to strengthen and update their knowledge and skills in the areas of data analytics while obtaining a formal qualification.
The Postgraduate Certificate in applied data science will address the widening digital skills gap in data intensive organisations resulting from the fast pace development of new technologies, which increasingly leaves employees without the required skills in computational thinking needed to support their evolving role within the organisation.
Our standard postgraduate entry requirement is a second-class honours degree (2:2 or above) in a subject other than computer science from a UK university, or an equivalent international qualification. We will review every postgraduate application to Birkbeck on its individual merits and your professional qualifications and/or relevant work experience will be taken into consideration positively. We actively support and encourage applications from mature learners. On your application form, please list all your relevant qualifications and experience, including those you expect to achieve. Apply now to secure your place and allow enough time for the application and enrolment process. You do not need to have completed your current qualification to start your application.
Two evenings per week in the Autumn term, October to December. Several lectures will be held in the Spring term to support students with the work-based project.
- Our Department of Computer Science and Information Systems is one of the longest established in the world - we celebrated our sixtieth anniversary in 2017. Our research dates back to the late 1940s, when one of the first electronic computers was developed at Birkbeck by Dr Andrew Booth. We now house the Computational Intelligence Research Group and the Information Management and Web Technologies Research Group, both of which collaborate with other research groups and with industry, in the UK and abroad, and undertake interdisciplinary research in the life, natural and social sciences, and the humanities.
- We provide a stimulating teaching and research environment, with academic specialists in all fields, including information and knowledge management, web and pervasive technologies, computational intelligence, and information systems development, among others.
- You will have access to laboratories of networked PCs with a range of language compilers, database and other application software. We are connected, via the SuperJANET network, to the computers of other academic institutions in London, elsewhere in the UK and abroad.
- The Birkbeck Knowledge Lab draws on multi- and interdisciplinary perspectives and methodologies from across the sciences, social sciences and the arts, to investigate how digital technologies and digital information are transforming our culture and how we learn and work.
- In the 2014 Research Excellence Framework (REF), more than 75% of our research outputs in Computer Science were ranked world-leading or internationally excellent.
Formal lectures are the principal teaching method, but these frequently incorporate practical sessions, for example in programming, and also group exercises carried out in class. There is a large element of practical coursework which students carry out in their own time; some of these coursework assignments are carried out in groups. Each student also undertakes an individual work-based project which is jointly supervised by a member of staff and someone from the student’s employer. The project provides an opportunity for students to investigate in depth an aspect of data analysis that particularly interests them and provide an opportunity for the learner to demonstrate and apply their newly acquired knowledge of computational thinking through a project that will align with their interests and business objectives of the organisation.
The programme consists of two compulsory modules and a project module.
Demystifying Computing with Python: This module covers the fundamental concepts and techniques of programming with Python and how to apply them to perform simple data science methods. Students develop the core skills and expertise needed by information professionals, for example using Python to implement programs and to interface with different data sources. Students will also develop data science skills as the course will introduce basic algorithms such as those needed for searching and sorting data sets. During the labs, students will work with case studies to realise the potential of Python for data analytics. The module will show students how to use Python to solve practical problems based on use cases extracted from real domains.
Analytic Tools for Information Professionals: This module covers the fundamental concepts and techniques of data science with Python, demonstrating how to apply these in order to process and visualise datasets. The module will cover tools such as database systems (SQL), data analytics techniques using machine learning models and key Python libraries for applied data science. During the labs, students will work on case studies to apply data analytics to real-world problems.
Work-Based Project for Information Professionals: The work-based module provides students with an opportunity to work in an area of data science in depth and to develop a piece of software to address a work-based project need. The module will bring together the different skills developed from the other modules and will serve as a basis for bridging the academic contexts taught and work-based requirements for implementing a project.