Project in Machine Learning* 10 credits
The course is a project course that, given a realistic problem and settings, considers the entire CDIO (Conceive­Design­-Implement-­Operate) cycle. The students are placed in the role of a small development team within an agile startup that should develop a data-driven product. The students are expected to work using agile processes in teams and are expected to perform all roles except product owner. The startup environment requires fast releases and effective use of available resources focus is put on Lean agile as well as applied machine learning and data processing.

-  How machine learning projects are structured and implemented.
-  Tools, services, and libraries that are used for data analysis and machine learning, e.g., Weka and Tensorflow.
-  The configuration of pipelines for machine learning systems with respect to software and hardware, e.g.,
    accelerators.
-  The practice of working with real data with respect to, e.g., collection, processing, and analysis.
-  Evaluation of performance based on customer requirements.
-  Experiment­driven development with short design, training, and evaluation cycles.
-  The Lean strategy for production and the Toyota production system.
-  How Lean­Agile combines the ideas from Lean with agile processes.
-  What is waste in software development and how can it be reduced?
-  How can just­in­time­production be applied to software development?
-  How can a team learn, for example from reflection after a spring and how can the process highlight the
   development team (and their competences).
-  Software as something complete.
-  Advanced skills in writing reflection reports.

The course will be given during the period: 20 Jan, 2020 - 07 Jun, 2020
Please sign up no later than 10/1 2021

For more information see the course plan: https://kursplan.lnu.se/kursplaner/syllabus-4DV652-1.pdf

If you have any questions please turn to  Welf Löwe, welf.lowe@lnu.se 

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