Deep Learning, 7.5 credits
This course introduces the basics of artificial neural network (ANN) and deep neural network (DNN). The course also deals with proper applicability of different ANN/DNN algorithms in some of the practical appication (like computer vision). The student shall also learn about some of the modern DNN architectures. Practical exercises are provided to give hands-on experience.
FACTS
CYCLE
Second cycle
ENTRY REQUIREMENTS
General entry requirements and approved result from the following course/courses:
IAI600-Introduction to Artificial Intelligence and Machine Learning and
BSD600-Big Data Processing and Analysis and
PFA600-Programming for Automation and
STB600-Sensor Technology and Image Analysis or the equivalent.
PACE OF STUDY
Part-time
TYPE OF INSTRUCTION
On Campus
PROGRAMME/COURSE DATE
TEACHING HOURS
Daytime
APPLICATION DEADLINE
16 October 2023
APPLICATION CODE
HV-E1774
START/END
From v.03 2024 to v.12 2024
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