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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
- StartingApplication deadline not specified.
Language
English
TOEFL® IBT 90
IELTS 6.5
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Credits
7 ECTS
Delivered
On Campus
Campus Location
- Stockholm, Sweden
Disciplines
Data AnalyticsWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
TOEFL® IBT 90
IELTS 6.5
Prepare for Your English Test
Cathoven AI IELTS Preparation AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
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
Student Insurance via Studyportals Partner
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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.
Tuition Fees
Living costs
Stockholm
Sweden
9668 - 17248 SEK / month
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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