ECON62020
Programming and other Skills for Data Scientists
30
Full year
Postgraduate Taught
Level 7
Chad Brown
Unit coordinator
Ralf Becker
Unit coordinator
Arthur Sinko
Unit coordinator
Economics
1
FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 '
European Credit Transfer & Accumulation System Rating : 15.0
<p>This unit will help students on the MSc Economics and Data Science in the development of vital study, employability and programming skills. Students will be supported in their development of the vital programming skills (R in Semester 1, Python in Semester 2) that are needed to implement the advanced methods taught in the Data Science & Machine Learning units. </p><p>As part of this unit students will also work (in groups) on substantial empirical projects. Through this group work students will learn to deal with issues of data acquisition, handling, wrangling and security as well as ethical issues surrounding the curation of data-sets. </p><p>Throughout the unit und through the work described above students will be supported in developing vital employability skills, such as working in a group and communicating results to a variety of audiences. </p>
<p>develop vital study, employability and programming skills</p><p>develop vital programming skills (R in Semester 1, Python in Semester 2) that are needed to implement the advanced methods taught in the Data Science & Machine Learning units. </p><p>provide experience in team work on substantial empirical projects.</p><p>develop an understanding of issues surrounding data acquisition, data handling, data wrangling and data security</p><p>develop an understanding of the ethical issues surrounding the curation of datasets.</p><p>gain experience communicating statistical results to a variety of audiences.</p><p>This unit will help students on the MSc Economics and Data Science in the development of vital study, employability and programming skills. Students will be supported in their development of the vital programming skills (R in Semester 1, Python in Semester 2) that are needed to implement the advanced methods taught in the Data Science & Machine Learning units. As part of this unit students will also work (in groups) on substantial empirical projects. Through this group work students will learn to deal with issues of data acquisition, handling, wrangling and security as well as ethical issues surrounding the curation of data-sets. Throughout the unit, and through the work described above, students will be supported in developing vital employability skills, such as working in a group and communicating results to a variety of audiences. </p>
<p>In order to be able to take up positions in government, central banks or private sector organisations as a data analyst/economist students will have to be able to demonstrate strong skills in the areas supported by this unit:</p><p>Programming </p><p>Data handling</p><p>Group working </p><p>Communication (oral and written) </p>
<p>Semester 1</p><p>Data </p><p>Availability and sources <br/>Security <br/>Ethical issues</p><p>Databases/SQL</p><p><br/>Programming in R</p><p>Setup</p><p>Data Wrangling <br/>Data Science techniques <br/>Data Visualisation </p><p><br/>Collaborative working</p><p>Use of Github <br/>Communication in Teams <br/>Work sharing</p><p><br/>Employability</p><p>Career options <br/>Skills and Portfolio presentation (CV, LinkedIn, GitHub pages)</p><p> </p><p>Semester 2 </p><p>Data </p><p>Databases/SQL <br/> </p><p>Programming in Python</p><p>Setup</p><p>Data Wrangling <br/>Data Science techniques <br/>Data Visualisation <br/> </p><p>Communicating</p><p>Communicating in a group <br/>Communicating with non-technical audiences</p>
<p>Student work will be organised around problem sets and empirical group-work projects communicated through the unit’s Blackboard site. </p><p>Students will meet in weekly three-hour workshops in which they will finalise or continue work prepared asynchronously. Any learning materials required will be delivered through the unit’s Blackboard site. </p><p> </p><p>Workshop attendance: 72h (2 semesters x 12 weeks x 3h)</p><p>Prep work on problem sets: 10h (10 x 1h)</p><p>Guided programming training: 100h</p><p>Group project work: 100h (Semester 2 only)</p><p>Employability skill work: 18h</p><p> </p><p>Sum: 300h </p>
0
Other
100%
<p><br/>Programming Tests (PT) (Sem 1: R, Sem 2: Python), 20%</p><p>Group replication Project (REP) 1,000 words, 30%</p><p>Group project (written project + presentation) (PRO) 1,500 words, 50% <br/> </p>
ECON61351
Data Science and Machine Learning 1
Co-Requisite
Compulsory
ECON62012
Data Science and Machine Learning 2
Co-Requisite
Compulsory
ECON61351 AND ECON62012 are co-requisites for ECON62020
Available to MSC Economics & Data Science only
N
0
0
0