3807711: CF_Big Data Analytics

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Semester:WS 14/15
Type:Seminar
Language:English
Scheduled in semester:1-6
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h

Module coordination/Lecturers

Curricula

Bachelor's degree programme in Business Administration (01.09.2012)
Master's degree programme in Architecture (01.09.2014)
Bachelor's degree programme in Architecture (01.09.2014)

Description

  • Introduction into "Big Data Analytics"
  • Gathering Data with Python
  • Cleaning Up Data with Python
  • Interpreting Data with R
  • Visualizing Data with R
  • Predictive Models with R

Learning Outcomes

  • Repeat the fundamental concepts and definitions in the area of big data analytics
  • Understand the benefits of using and interpreting large data sets derived from various data sources.
  • Solve assignments, especially case studies in the area of smart cities
  • Identify relationships between different types of data.
  • Describe data an build prediction models.
  • Compare solutions with regard to their prediction accuracy.
  • Evaluation and select suitable prediction models.

Qualifications

Lectures Method

  • Lecture with interactive elements
  • Team project work

Admission Requirements

  • Basic programming skills
  • Basic skills of descriptive statistics

Literature

Field, A. P., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage.
Chang, W. (2013). R graphics cookbook. Beijing: O'Reilly.
Downey, A. (2013): Think Python - How to Think Like a Computer Scientist. Green Tea Press.

Materials

Will be provided in class

Comments

Cross-faculty elective subject:
Notice the special Multi-stage allocation process.

Dates

DatumZeitRaum
17.09.201411:45 - 13:15S3
24.09.201411:45 - 13:15S3
01.10.201411:45 - 13:15S3
08.10.201411:45 - 13:15S3
15.10.201411:45 - 13:15abgesagt/cancelled
22.10.201411:45 - 13:15S3
29.10.201411:45 - 13:15S3
05.11.201411:45 - 13:15S3
12.11.201411:45 - 13:15S3
19.11.201411:45 - 13:15S3
26.11.201411:45 - 13:15S3
03.12.201411:45 - 13:15S3
10.12.201411:45 - 13:15S3
17.12.201411:45 - 13:15S3