edsa curriculum and courses

Curriculum and self-study coursesChris Phethean

University of SouthamptonUnited Kingdom

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

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

EDSA Courses

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

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

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

EDSA Courses: FutureLearn MOOCs

Started 11 April3 weeks

Starts 11 July4 weeks

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

Course Schedule✔✔✔✔✔✔

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