Python and SQL Programming and Data Analysis

Die Grundlagen der Python-Programmierung und Datenanalyse werden durch die Vermittlung von Konzepten wie Variablen, Datentypen und Funktionen erläutert. Weiterführend werden fortgeschrittene Programmierkonzepte wie objektorientierte und funktionale Programmierung in Python behandelt. Die Modellierung von Datenbanken, einschließlich relationaler Datenbanken und NoSQL-Systemen, werden untersucht, gefolgt von der praktischen Anwendung dieser Kenntnisse zur Erstellung eines Data Marts in SQL. Schließlich werden die Qualität von Daten und deren Aufbereitung sowie die explorative Datenanalyse und Visualisierung behandelt.

Die Weiterbildungsinhalte sind auf Englisch.
Introduction to Programming with Python

• Python as a programming language for data science
• Variables and built-in datatypes
• Statements and functions
• Error and exception handling
• Important Python data science modules

Project: Object Oriented and Functional Programming with Python

• This course introduces the students to the advanced programming concepts of object orientation and functional programming and how they are realized in the Python programming language.

Database Modeling and Database Systems

• Fundamentals of relational databases
• Simple database queries
• Entity/Relationship (E/R) Diagrams
• database development
• Complex database queries across multiple tables
• Changing data in databases
• NoSQL database systems

Build a Data Mart in SQL

• This course is about the implementation of a practical database use case employing previously-acquired knowledge on pertaining approaches and methods. The core aim is to apply the hitherto theoretical knowledge of database methods and approaches to solve a real-world application scenario. This entails reasoning about possible design and architectural choices in a rational way, as well as implementing them in a functioning database system.

Data Quality and Data Wrangling

• Data quality and associated management techniques
• Data acquisition from public sources
• Working with relevant data formats
• Techniques for shaping and tidying data for analysis

Exploratory Data Analysis and Visualization

• Exploratory data analysis
• Principles of data visualization
• Established visualization types and apposite use cases
• Commonly-used Python modules for visualization
• Principles of effective visual communication