The curriculum will be constantly updated based on the process model that is adopted by the project 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.
Current curriculum
| 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
| 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.
4 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.