Duration of Training

2 Days


  • To have knowledge of data, data analysis, mathematics, statistics, computer science, database, database query.
  • To have basic knowledge of Python.
  • To have basic Linux knowledge.


Suitable for people who want:

  • Software developers, analysts and data scientists who need to apply data science and machine learning in Spark / Hadoop,
  • To collect, analyze and interprete extremely big amounts of data,
  • To use advanced analysis technologies,
  • To use various analysis and reporting tools by collecting and analyzing data, identifying patterns, trends and relationships in data sets, who want to work on large amounts of data.

Training Goals

  • Learning the basics including project life cycle, data collection, data evaluation, data transformation and data analysis,
  • Theoretical learning of machine learning (supervised / unsupervised learning) algorithms,
  • Learning the basics of working on data flowing with Spark used to perform in-memory analysis and analytical studies on big data and the use of machine learning algorithms,
  • Sample application studies.


  • Data Science Fundamentals
  • Machine Learning Methods
  • Spark Machine Learning (ML)
  • Spark ML Lab Study
  • Application Study