Becoming a Professional Data Scientist
| Code | School | Level | Credits | Semesters |
| DATA3001 | Computer Science | 3 | N/A | Full Year UK |
- Code
- DATA3001
- School
- Computer Science
- Level
- 3
- Credits
- N/A
- Semesters
- Full Year UK
Summary
This teaching block allows apprentices to prepare for work as a professional data scientist.
Apprentices will be introduced to relevant literature and professional networks so that they may prepare for further study, research and lifelong learning opportunities as they progress their career. They will build a portfolio of projects representing the development of their individual knowledge, skills and behaviours as well as reflecting and adapting their current CV so that apprentices may identify gaps and consequently prioritise and plan personal development targets for successful ongoing achievement. This portfolio will be necessary for learners to proceed through the Gateway and will be used as a basis for the professional discussion part of the end-point assessment.
Learners will be expected to reflect on their current role and future direction (considering the on-the-job activities within this reflection)
Target Students
Only available to those studying towards the Data Scientist Degree apprenticeship programme
Classes
6 week teaching block 1 hour of e-learning and reflective study (1 hour per week for 5 weeks = 5 hours) 1 hour of online workshops (1 hour per week for 5 weeks = 5 hours) 1 block release x 5 hours Total of 15 hours allocated in the delivery plan.
Assessment
- 100% Assignment
Assessed by end of designated period
Educational Aims
This teaching block allows apprentices to prepare for work as a professional data scientist by supporting apprentices in their development of professional skills, attitudes and behaviours necessary for employment in a diverse and changing environment.Learning Outcomes
Teaching Goal 1
Demonstrate an awareness of professional skills relevant to that of a data scientist as well as attitudes and behaviours necessary for employment in a diverse and changing environment.
Teaching Goal 2
Demonstrate an awareness of development and employability skills by keeping an up to date portfolio and CV.
Teaching Goal 3
Demonstrate a comprehensive understanding of current and developing data science approaches and apply them where appropriate.
KSBs
K1. The context of Data Science and the Data Science community in relation to computer science, statistics and software engineering. How differing schools of thought in these disciplines have driven new approaches to data systems.
B6. A commitment to keeping up to date with current thinking and maintaining personal development. Including collaborating with the data science community.