Python course and data analysis

Course content:

1. Python programming language
   Introduction to Python. Basic syntax. Flow control. Data structures in python. Functions. Working with files. Error and excepton managment. Modules and packages. Object-oriented Python.Data bases manipulation.
2. Python libraries for data analysis
   Basic usage of Python for data manipulation and data analysis. Basics of machine learning and using Python and Pythong packages in data analysis and machine learning. Usage of packages: NumPy, Pandas, Bokeh, Agate, SciPy.
3. PySpark
   Big data analytics in real time. Data streaming. Apache Spark. Development and managment of Spark applications. Machine learning in Apache Spark. PySpark. Data visualisation.  

Course is free of charge for all participants. Theoretical and practical teaching will be organized in cabinet 304 at Faculty of Organizational Sciences. All the participants are obliged to take a project related to the areas within the course.

Each participant who attends the classes and successfully completes the final project receives a certificate at the end of the course. For students or future students of Faculty of Organizational Sciences, the part of pre-exam obligations on one of the Elab subjects (depends on level of study) will be considered as completed, based on received certificate:

• Internet technologies – undergraduate studies
• Internet technologies and systems – master studies
• Internet technologies and systems – selected chapters – particular postgraduate studies
• Internet technologies – selected chapters – PhD studies