Applied Data Science: Python & TensorFlow in Practice



Overview

Data science is a new emerging multidisciplinary domain that is focused on applying Data for understanding and drawing specific conclusions in many sectors such as business, medical, financial, manufacturing, etc. The key skills required in this field are the ability to hypothesise, and improve business outcomes based on initial analysis with continued proof points, through continuously testing those base conclusions and the iterative improvements to ensure the conclusions reached continue to be correct and true.

The Applied Data Science course aims to introduce students to a blend of Data Science concepts and technologies in order to enable them to work with everyday Data related issues analytically. Students will gain experience of the entire Data Science supply chain, namely Data collection, processing, analysis and visualisation, using an innovative hands-on practical Data Science Group project.

This course could be taken after the companion course "An Overview of Data Science".

Programme details

Course begins: 19 Apr 2023

Week 0:  Course orientation

Week 1:   Introduction to Applied Data Science

Week 2:   Data Science Programming Languages 

Week 3:   Applied Data Science Using Python

Week 4:  Usability in Data Science Projects  

Week 5:  Data Analytics using Python & SciKit

Week 6:  Course Project

Week 7:   Course Project

Week 8:   Course Project

Week 9:   Course Project

Week 10:  Course Project

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

To introduce the learner to Applied Data Science, focusing more on the hands-on techniques and methods for data analytics purposes.

Course Objectives

1. Data Analytics using Python.

2. Application Machine Learning & AI.

3. Data Science Project.

Teaching methods

The course will include a mix of pre-recorded lectures, interactive classes, hands-on exercises and invited talks from expert data science practitioners.

Learning outcomes

By the end of this course, students will be expected to:

1. explain how data is collected, managed and stored for data science;

2. demonstrate an understanding of statistics and machine learning concepts that are vital for data science;

3. implement Python code to statistically analyse a dataset to be used in the group project.

Assessment methods

The students will need to complete a project which include understanding & applying all the above knowledge & techniques and submit a report of around 2000 words to reflect this.

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

The students should have some previous exposure to Data Science, as provided, e.g., by the Department’s “Overview of Data Science” 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