Date post: | 12-Apr-2017 |
Category: |
Data & Analytics |
Upload: | edsa-project |
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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