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The Pilot Course for Data Scientist, designed as result of the huge research activities of the Da.Re. Project, will be a 150 hours course dedicated to about 450 participants from five countries (Italy, Portugal, Serbia, Slovenia, United Kingdom, possibly involving international students already participating in the Erasmus Programme) and will be held in English.
The Pilot Course will consist of a part of distance learning shaped as a MOOC (Massive Open Online Course) and a part of face-to-face learning and practical experience organized in Italy. Participants involved in this second stage will be 75, 10 of which will access the EU grants, covering travel and individual support costs.
The Pilot Course participants will be awarded a joint attendance certificate that will include clear references to the European Qualification Framework levels 7.
The total course workload has been planned to count around 21 ECTS credit points.
The Pilot Course Concept
Our research identified a gap in the provision of data science education that is not satisfied by the universities or boot camps, namely for what we have called the bridge person, someone who combines knowledge of an organisation’s business with sufficient knowledge and understanding of data science to ‘bridge’ between nontechnical people in the business with highly skilled data scientists able to add value to the business.
We believe that the roles of the Bridge Person and Chief Data Analytics Office identified by the Da.Re. project can make a significant impact to improving the application of data science to European businesses and organisations.
Our solution is to enable a proper additional education in the data science domain for:
- Employees from business who have expert knowledge about business and know little about data science.
Career path They can become Chief Data Analytics Officer (or similar) in the company (after a while)
- Graduate students who want to work as a data scientist in business and are motivated to learn new technical topics of the value for their future position.
Career path They can become Chief Data Scientist (after a while)
- Senior business people who have little time but want to know how data science can add value to their business, and how to take the first steps towards it.
An Outline of the Da.Re. Programme
The Da.Re. programme has two parts: 80 hours online education followed by 70 hours face-to-face education.
The idea is that the online education provides students with the technical knowledge and skills needed to do the hands-on training at the two-weeks 70-hours face-to-face residential school. By combining online and face-to-face education, Da.Re. can combine the best of MOOCs and the boot camp approach to provide new, useful and sustainable data science education in Europe.
The logic of this programme design is that the content of the 80-hours online education will be determined by what students need to know in order to address the case studies in the 70 hour residential part of the programme. Case study areas can include topics such as:
- Business Modelling and forecasting, modelling production and supply chains
- Marketing Designing campaigns, analysing data on sales, footfall, web clicks etc.
- Education Analysing data on web clicks, study times, marks gained, study paths
- Scientific Analysing large quantities of multidimensional numerical data
- Medicine Classification for diagnosis and treatments, statistical analysis
- City planning Modelling & mapping to forecast land use, transport, housing, services
The detailed content of the online course is part of the activities that are going to be performed in the second year of the project (Sept. 2017-Aug. 2018), but are likely to be the following:
- Common notion of data lifecycle / pipeline / methodology/ mind map
- Technical issues, e.g. setting up virtual machines in the cloud with generic tools
- Databases and query languages: SQL, noSQL
- Modelling: types of model, e.g. network models, systems models
- Statistics: statistical theory and packages, e.g. SPSS, R
- Web design: user interface design, HTML, CSS, front and back end programming
- Visualisation: using visualisation tools, graphics, maps GIS
Prerequisite Knowledge and Background
- Level 6 education or higher, e.g. a bachelors degree in any subject
- Numerate and able to read simple equations, graphs and charts
- Literate and able to write reports with illustrative graphics
- Good search skills, finding and synthesising information
- Interest in patterns of data as they impact on business
- Good self-study and time-management skills
- Good teamwork skills
Thus our typical students are seeking a job in industry, or are already employed people in companies (typically SMEs) who have the knowledge of their business domain and will acquire the data science competences of the bridge person.
The Design of Online Course Modules
It is proposed that Da.Re. will use the FutureLearn platform for its MOOCs. This e-learning system involves innovative use of multimedia forms including text, voice, images, animations, videos with moving images demonstrating what is being taught, narrative videos that ‘tell the story’, interactive graphics, interactive computer software, databases, downloadable texts such as pdf documents, and so on.
The design of online course modules is a task led by The Open University, member of the UNESCO UniTwin Complex Systems Digital Campus (CS-DC), a consortium of 120 universities worldwide with a mission to provide free technical education in Europe, Africa, Latin America and worldwide.
The Design of Face-to-Face Residential Course Module
Students and business personnel who attend the course will be separated into groups, each solving a real problem from industry in the form of a use case.
Use cases will be gathered from the industry partners of the consortium or by stakeholders dealing with Data Science in activities.
Lecturers will support the groups at solving the problems, including how to use specific tools/algorithms/methodologies specifically prepared for each use-case.
The Learning Outcomes
The general learning outcomes of the face-to-face course will be:
- A clear knowledge of the data lifecycle
- Data Preparation
- Data Analysis
- Data Visualisation
- Practice and ability to solve real problems that companies face
- The capacity to go beyond the data lifecycle by creating added value to the organisation
- Ability to organise and revise a data lifecycle in an organisation. More precisely, to identify and select existing and not existing competences in the organisation, create a team and structure the work for going through an established pipeline:
- Problem Identification
- Data Preparation
- Data Analysis
- Data Visualisation