The curriculum was constantly updated throughout the duration of the project, based on the process model adopted for the production of learning resources (see figure below). This model is driven by a participatory approach that defines a series of iterations in the production of learning materials, with multiple revisions from internal and external stakeholders, in order to ensure high quality in the produced materials.
Final curriculum (July 2017)
Module
Topic
Stage
Status as of July 2017
1
Foundations of Data Science
Foundations
Released and revised
2
Foundations of Big Data
Foundations
Released
3
Statistical / Mathematical Foundations
Foundations
Released
4
Programming / Computational Thinking (R and Python)
Foundations
Newly released
5
Data Management and Curation
Storage and Processing
Released
6
Big Data Architecture
Storage and Processing
Released
7
Distributed Computing
Storage and Processing
Released and revised
8
Data Intensive Computing
Storage and Processing
Newly released
9
Linked Data and the Semantic Web
Storage and Processing
Released as FutureLearn MOOC in April 2016
10
Machine Learning, Data Mining and Basic Analytics
Analysis
Released and revised
11
Big Data Analytics
Analysis
Released
12
Process Mining
Analysis
Released
13
Social Media Analytics
Analysis
Newly released
14
Data Visualisation and Storytelling
Interpretation and Use
Released
15
Data Exploitation including data markets and licensing
Interpretation and Use
Newly released
Revised curriculum (July 2016)
Module
Topic
Stage
Status as of July 2016
1
Foundations of Data Science
Foundations
Released and revised
2
Foundations of Big Data
Foundations
Released
3
Statistical / Mathematical Foundations
Foundations
Newly released
4
Programming / Computational Thinking (R and Python)
Foundations
To be released in July 2017
5
Data Management and Curation
Storage and Processing
Newly released
6
Big Data Architecture
Storage and Processing
Released
7
Distributed Computing
Storage and Processing
Released and revised
8
Stream Processing
Storage and Processing
To be released in July 2017
9
Linked Data and the Semantic Web
Storage and Processing
Released as FutureLearn MOOC in April 2016
10
Machine Learning, Data Mining and Basic Analytics
Analysis
Released and Revised
11
Big Data Analytics
Analysis
Newly released
12
Process Mining
Analysis
Released
13
Social Media Analytics
Analysis
To be released in July 2017
14
Data Visualisation and Storytelling
Interpretation and Use
Newly released
15
Data Exploitation including data markets and licensing
Interpretation and Use
To be released in July 2017
Initial curriculum (July 2015)
Module
Topic
1
Foundations of Data Science
2
Foundations of Big Data
3
Statistical / Mathematical Foundations
4
Programming / Computational Thinking (R and Python)
5
Data Management and Curation
6
Big Data Architecture
7
Distributed Computing
8
Stream Processing
9
Machine Learning, Data Mining and Basic Analytics
10
Big Data Analytics
11
Process Mining
12
Data Visualisation
13
Visual Analytics
14
Finding Stories in Open Data
15
Data Exploitation including data markets and licensing
What do you think about our curriculum? Are there any modules you are particularly interested in? Please leave your feedback in the comments section below.
Hi dears at EDSA,
You people are doing a great work.
My query is related to the existing curriculum that is published on your site(http://edsa-project.eu/resources/curriculum/). Is it correct to say that the learning sequence of the new entrant in this field should be the same as the order of Modules (1 to 15)?
I am an experienced telecom engineer(15 plus years in wireless GSM/UMTS operators and vendor) and now am gearing toward learning Data Sciences as this is the future of technical maintenance and support related activities.
Cheers, Asad
Thank you for sharing useful information for all the candidates of Datascience Training who want to kick start these career in this field
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.OkRead more
5 Comments
Hi dears at EDSA,
You people are doing a great work.
My query is related to the existing curriculum that is published on your site(http://edsa-project.eu/resources/curriculum/). Is it correct to say that the learning sequence of the new entrant in this field should be the same as the order of Modules (1 to 15)?
I am an experienced telecom engineer(15 plus years in wireless GSM/UMTS operators and vendor) and now am gearing toward learning Data Sciences as this is the future of technical maintenance and support related activities.
Cheers, Asad
Hi,
where can i find the course material please?
Paul
Hi Paul, you can access course materials through http://courses.edsa-project.eu
Hi, Great job! Please include some deep learning.
Thank you for sharing useful information for all the candidates of Datascience Training who want to kick start these career in this field