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Overview
What you will study
Using methods from statistical learning, students taking the Network Analytics and Data-Driven Engineering course offered by KTH Royal Institute of Technology will develop and evaluate, for instance, models for prediction and forecasting of Key Performance Indicators (KPIs) and for anomaly detection. The models will be fitted and evaluated using testbed measurements or traces from operational systems. The functions built from these models are designed for real-time execution. To develop the models, tools and packages from data science will be used, e.g., Jupyter notebook, scikit-learn, TensorFlow. The course is structured as two consecutive project blocks. Each block starts with introductory lectures that give background and discuss concepts for the specific project, followed by project execution, writing of a report, and interview.
After passing the course, the student should be able to:
- model an assignment for network analysis
- pre-process data and design models for prediction based on machine learning techniques and tools
- evaluate, interpret and apply the results when possible
- write report that describes and explains project result.
Programme Structure
The program focuses on:
- initial lessons about selected machine learning techniques that are used in the projects
- the tools that should be used
- projects completed by the students based on message boards and project meetings
- preparations before the students' project reports.
Key information
Duration
- Full-time
- 3 months
Start dates & application deadlines
- Starting
- Apply before
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Language
English
TOEFL® IBT 90
Credits
7 ECTS
Delivered
On Campus
Disciplines
Data AnalyticsAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
TOEFL® IBT 90
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
Get your student insurance nowStarting from €0.53/day, free cancellation any time.
Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at KTH Royal Institute of Technology and/or in Sweden, please visit Student Insurance Portal.
Other requirements
General requirements
- In total 180 higher education credits of which at least 90 higher education credits in computer science, electrical engineering or an equivalent discipline
- Knowledge in statistics, 6 higher education credits.
- Knowledge in machine learning, 6 higher education credits.
- Knowledge in networks and computer systems, 6 higher education credits.
- Knowledge in Python programming, 6 higher education credits.
- The upper secondary course English B/6
Tuition Fee
To always see correct tuition fees
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EU/EEA
FreeTuition FeeBased on the tuition of 0 SEK for the full programme during 3 months.
If you are an EU, EEA or Swiss citizen or hold a residence permit in Sweden for something other than studies you generally do not have to pay tuition fees.
Living costs for Stockholm
9668 - 17248 SEK /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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