An Overview of Data Science



Overview

Data is of huge significance as it forms the quintessential building block of the Information age. In some circles Data is already becoming an alternative global currency. Data Science is an increasingly important skill. A recent study by the McKinsey Global Institute concludes, "a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge”.

Data science is an interdisciplinary field. It enables one to analyse, communicate and reformulate raw Data in order to extract conclusions about that information. Data Science ultimately allows us to use and work with Data in creative ways to generate value and give us a better and more profound understanding of the underlying context.

Data Science is already used in all sectors of industry and society to allow government and organisations to make better and more informed decisions and to verify or disprove existing models, processes and theories.

The course aims to introduce students to a blend of Data Science concepts and technologies in order to enable them to understand the everyday Data related issues, covering the Data Science Supply Chain from Data collection, to processing, analysis and visualisation.

Programme details

Course starts: 21 Sept 2022

Week 0:  Course orientation

Week 1:   Nature of Data, Big Data Phenomena

Week 2:   Web, Internet, Cloud Computing, Data Bases

Week 3:   Data Science Pipeline

Week 4:   Introduction to Data Science Tools

Week 5:   Data Cleaning/Data Publishing  

Week 6:   Practical Session Data Wrangling

Week 7:   Data Visualisation Theory

Week 8:   Relation Data Visualisation

Week 9:   Practical Session on Data Visualisation Tools 

Week 10:  Assessment

Certification

Students who register for CATS points will receive a Record of CATS points on successful completion of their course assessment.

To earn credit (CATS points) you will need to register and pay an additional £10 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online.

Coursework is an integral part of all weekly classes and everyone enrolled will be expected to do coursework in order to benefit fully from the course. Only those who have registered for credit will be awarded CATS points for completing work at the required standard.

Students who do not register for CATS points during the enrolment process can either register for CATS points prior to the start of their course or retrospectively from the January 1st after the current full academic year has been completed. If you are enrolled on the Certificate of Higher Education you need to indicate this on the enrolment form but there is no additional registration fee.

Fees

Description Costs
Course Fee £260.00
Take this course for CATS points £10.00

Tutor

Dr Sepi Chakaveh

Dr Sepi Chakaveh is a Departmental Lecturer in Data Science and Course Director for the Undergraduate Advanced Diploma in IT Systems Analysis and Design (ADITSAD) at the Department for Continuing Education, University of Oxford. She has a degree in Electronic Engineering and a PhD in Experimental Astrophysics & Space Sciences. Sepi has been teaching and researching Dynamic Objects and Data convergence. She is co-founder and former director of the Southampton Data Science Academy.  Sepi is the winner of Everywoman Innovator Award 2020, Technology GameChanger  2021 & the Winner of The Innovation Excellence Streaming Platform of the Year 2022.

Course aims

The course will include a mix of lectures, and hands-on exercises which  will allow students to gain experience using the theory and techniques delivered in the lectures in the field of Data Science at large.

Course Objectives

• Learning about the Nature of Data & Data Science enabling technologies.

• Introduction to the Applied Data Science Pipeline Process.

• Exploring Data Visualisation & its application.

Teaching methods

The course will be mostly theory based, with a few hands-on introductory practical sessions in Data Wrangling & Data visualisation tools.

Learning outcomes

To provide an introduction to various topics such as Big Data, data visualisation, advanced databases and cloud computing, along with a toolkit to use with data.

Assessment methods

The students will need to complete a written assessment on the last session of the course. 

Students must submit a completed Declaration of Authorship form at the end of term when submitting your final piece of work. CATS points cannot be awarded without the aforementioned form - Declaration of Authorship form

Application

We will close for enrolments 7 days prior to the start date to allow us to complete the course set up. We will email you at that time (7 days before the course begins) with further information and joining instructions. As always, students will want to check spam and junk folders during this period to ensure that these emails are received.

To earn credit (CATS points) for your course you will need to register and pay an additional £10 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online.

Please use the 'Book' or 'Apply' button on this page. Alternatively, please complete an application form.

Level and demands

No, or very little, background knowledge or experience is required for this course.

Most of the Department's weekly classes have 10 or 20 CATS points assigned to them. 10 CATS points at FHEQ Level 4 usually consist of ten 2-hour sessions. 20 CATS points at FHEQ Level 4 usually consist of twenty 2-hour sessions. It is expected that, for every 2 hours of tuition you are given, you will engage in eight hours of private study.

Credit Accumulation and Transfer Scheme (CATS)

Terms & conditions for applicants and students

Information on financial support