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Data Analyst

Shape field (scope)

The Data Analyst TÜV HELLAS scheme involves a qualified professional who is the link between the capabilities offered by information technology and business objectives. Among other things, this position involves collecting, processing and analysing data in relation to business objectives, solving business problems using appropriate templates, performing audits as well as project management using specific methodologies.

Cognitive framework (syllabus)

Basic level:
1. MS Excel, R language and Knime program

  • Control structures in MS
  • Descriptive statistics in MS Excel
  • Descriptive Statistics with R
  • Clustering in Statistical Analysis in MS (MS Excel)
  • Regression
  • Data Import & Analysis Creation
  • Data processing & organization
  • Displaying information in reports

2.

  • Databases with SQL
  • Storing Information in Databases

Advanced level:
1,2 and above:
3. R language

  • R Studio
  • Data types
  • Basic operators
  • Apply command
  • Error Detection and Correction
  • Code development

4. Statistics in R

  • Descriptive Statistics with R
  • Clustering
  • Regression
  • Advanced Graphics
  • Graph construction


For specialisation.

1,2 and additional:

5. Business Statistics and Statistical Analysis.

  • Probability, Normal Distribution and Case-Control.
  • Computational tools
  • Regression
  • Forecasting

6. Web Analytics

  • Key Performance Indicators of Web Analytics
  • Quantified Web Analytics Techniques

Web Testing

For specialization: R and Knime

1,2 and additional:

7. R and KNIME

  • Descriptive Statistics
  • Dimension reduction
  • Feature selection
  • Clustering
  • Regression

8. Presentation of results

  • Techniques for presenting results
  • Storytelling with data

For specialization.

1,2 and additional:

9. Basic Python concepts.

  • Python programming language
  • Data Science with Python

10. Data Science with Python

  • Statistics and Probability
  • NumPy
  • Pandas
  • Visualization with Matplotlib

11. Machine Learning

  • Artificial Intelligence, Machine Learning, Deep Learning
  • Machine Learning Algorithms

Data science and Machine Learning

Exam methodology

Multiple-choice theoretical examination.

Certification Requirements

Minimum Compulsory education and technical training

Contact Information