IoT Big Data and Analytics (5 cr)
Code: 5000BL72-3005
General information
- Enrollment
-
01.06.2022 - 11.09.2022
Registration for the implementation has ended.
- Timing
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19.09.2022 - 09.12.2022
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Engineering and Business
- Campus
- Kupittaa Campus
- Teaching languages
- English
- Degree programmes
- Degree Programme in Information and Communications Technology
- Teachers
- Juha Saarinen
- Teacher in charge
- Juha Saarinen
- Groups
-
ICTMODembeddedSemMOD Embedded System (International Semester)
-
PTIVIS21SEmbedded Software and IoT
- Course
- 5000BL72
Evaluation scale
H-5
Content scheduling
Chapter 1 Data and the Internet of Things
Chapter 2 Fundamentals of Data Analysis
Chapter 3 Data Analysis
Chapter 4 Advanced Data Analytics and Machine Learning
Chapter 5 Storytelling with Data
Chapter 6 Architecture for Big Data and Data Engineering
Objective
Student knows Basic tools for data analysis
Student can implement data analytics in edge computing
Student knows Basic solutions for big data analysis in cloud
Content
Data at rest and data in motion
Process for data analysis
Data preparation
Basics of descriptive statistics
Data visualization
Machine learning basics
Big data architectures
Materials
Cisco network academy material www.netacad.com
Teaching methods
Self-study network material
Lectures
7 laboratory sessions
Pedagogic approaches and sustainable development
Lab works
Lectures
Self study
Completion alternatives
-
Student workload
lab works 7x3h = 21h
lectures 6x2h = 12h
exam = 2h
self study = 74h
exam preparation 26h
TOTAL 135h
Arviointimenetelmät ja arvioinnin perusteet
Must pass Final Exam:
60% -> 1
68% -> 2
76% -> 3
84% -> 4
92% -> 5
Mandatory lab works: +/- 2 grades from individual Lab performance
Mandatory lectures, must attend 70%
Hylätty (0)
Failed Final Exam <60%
or
Weak Final exam < 76% + poor lab performance (missing labs, nonprofessional attitude or lack of active problem-solving, missed lectures)
Arviointikriteerit, kiitettävä (5)
Excellent Final Exam >92%
and
expected lab performance (all labs done with average performance)
or
Good Final Exam >76%
and
superb lab performance (all labs done, actively learns new skills outside of the lab scope, is able to help fellow students, attended all lectures)
Qualifications
Basic skills in using both Windows and Linux systems
Basic networking skills (Cisco CCNA1 or similar)
Basic programming skills with some high level programming language (for example Python, Java, C# or similar)
Basic programming skills include (but are not limited to): output formatting, conditional execution, loops, functions/procedures, function parameters and return values, arrays, error handling, testing and good programming policies
Sufficient logical-mathematical thinking skills
Sufficient skills in English language (lectures and all materials are in English)
Further information
-