gr

Big Data Analysis and Communication II


Teaching Staff: Ampeliotis Dimitris
Code: DMC303
Code: 303Υ
Course Category: Specific Background
Type: Compulsory
Course Level: Undergraduate
Course Language: Greek
Semester: 3rd
ECTS: 5
Lecture Hours: 4
Total Hours: 4
Short Description:

The purpose of the course includes the basic principles of visualizing and displaying data by creating graphs, as well as the use tools like as Google and Stack Overflow, to solve programming problems. Final goal of the course, is to familiarize participants with processing big data and therefore will be used: Python, basic statistical analysis, HTML, CSVs, APIs, SQL, APIs, CSVs, regular expressions, PDF processing, pandas, BeautifulSoup, Jupyter/IPython Notebooks, git/GitHub, StackOverflow, data cleaning, command line tools and more.

Part of the course includes the following sections:

  • Database management
  • Database processing
  • Data mining
  • Document libraries, regular expressions
  • Creating visualizations

Upon successful completion of the course, students will be able to:

  • Find and store Big Data
  • Know the basic principles of Big Data processing
  • Be familiar with Big Data visualization
  • Analyze data trends

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