The document outlines the curriculum and self-study courses developed by EDSA. It includes the following key points: - The curriculum covers foundational topics, storage/processing, analysis, and interpretation/use of data science. It is delivered through video lectures, MOOCs, eBooks, and other online learning formats. - Self-study courses are offered on topics like foundations of big data, distributed computing, and machine learning. MOOCs are also developed on the FutureLearn platform. - The curriculum is regularly updated, with new topics like statistical foundations and data management planned for future iterations. - Courses are tagged with skills and targeted towards different learner groups like statisticians, analysts

1. Curriculum and self-study
coursesChris Phethean
University of Southampton
United Kingdom

2. EDSA activities
• Surveys
• Interviews
• Dashboards
Landscaping
• Modular, media-rich, multiple
languages
• Core, domain-specific, and
technology-specific topics
Curriculum
and
courseware
• Video lectures
• Professional training
• MOOCs
• eBooks
Courses and
learning
analytics

3. Curriculum
Foundations
• Foundations of
Data Science
• Foundations of Big
Data
• Statistical /
Mathematical
Foundations
• Programming /
Computational
Thinking (R and
Python)
Storage and
Processing
• Data Management
and Curation
• Big Data
Architecture
• Distributed
Computing
• Stream Processing
Analysis
• Essentials of Data
Analytics and
Machine Learning
• Big Data Analytics
• Process Mining
Interpretation
and Use
• Data Visualisation
• Visual Analytics
• Finding Stories in
Open Data
• Data Exploitation

4. EDSA Courses
The EDSA Courses Portal: http://courses.edsa-project.eu/

5. EDSA Courses: Self-study options
• Foundations of Big Data
• Big Data Architecture
• Process Mining
• Distributed Computing
• Essentials of Data Analytics
and Machine Learning
• Big Data Analytics
• Foundations of Data Science

6. Big Data Architecture course: http://courses.edsa-project.eu/course/view.php?id=27

7. EDSA Courses: FutureLearn MOOCs
Started 11 April
3 weeks
Starts 11 July
4 weeks

9. Curriculum – Next Iteration (M18)
Foundations
• Foundations of
Data Science
• Foundations of Big
Data
• Statistical /
Mathematical
Foundations
• Programming /
Computational
Thinking (R and
Python)
Storage and
Processing
• Data Management
and Curation
• Big Data
Architecture
• Distributed
Computing
• Stream Processing
Analysis
• Machine
Learning, Data
Mining and Basic
Analytics
• Big Data Analytics
• Process Mining
Interpretation
and Use
• Data Visualisation
• Visual Analytics
• Finding Stories in
Open Data
• Data Exploitation
M18 Curricula modules

10. Course Schedule
the Data Science community.
Table 3: EDSA Core Curriculum Schedule
Topic Schedule
Foundations of Data Science M6
Foundations of Big Data M6
Big Data Architecture M6
Distributed Computing M6
Machine Learning, Data Mining and Basic Analytics M6
Process Mining M6
Statistical / Mathematical Foundations M18
D2.1 Data Science Curricula 1 Page 11 of 37
Data Management and Curation M18
Big Data Analytics M18
Data Visualisation M18
Finding Stories in Open Data M18
Programming / Computational Thinking (R and Python) M30
Stream Processing M30
Visual Analytics M30
Data Exploitation including data markets and licensing M30
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11. Curriculum Dimensions
• Courses to be tagged with pre and post skills
• Learning pathways aimed at:
– Statisticians
– Analysts
– Managers, product owners, CEOs
– Programmers, developers and system engineers
– Data managers (incl. security experts)
• Further dimensions:
– Tools and programming languages
– Type of data
– Industry sector
– Level
• Basic, advanced, expert