Data Science Foundation

You will learn the basics of Python programming and how to use Python code online over 18 days in a productive enterprise environment for Data Science applications. With a special focus on the areas of data management, machine learning and projects, this course first teaches the basics of the Python programming language. The contents are introduced and demonstrated live on the source code in practical examples and with the help of sample data. Subsequent exercises provide an opportunity to try out and further develop what has been learned.

In the area of data management, the course pays special attention to the popular Python Pandas library and its Series and DataFrame data types. Another focus area is machine learning, which is divided thematically into classification and regression problems. You will learn how to solve the different problem classes using the most important machine learning methods. In addition, theoretical basics as well as basic principles of data visualization will be worked through and then implemented in a practical way with the Power BI visualization tool. The last topic block covers how Python is used in “state-of-the-art” operative scenarios. You will learn which components enable you to design source code securely and clearly and how they can be used in project structures. You will implement your first small projects in Python.

Learning objectives:

Understanding and using Python syntax
Data management in Python
Creating and managing projects in Python
Learning best practice for professional Python code
Learning the basic methodology of machine learning
Implementing machine learning techniques with Python
Implementing data visualizations with Python
Understanding and using Python in the operative environment

Contents

Introduction to Data Science with Python (5 days)

Theoretical introduction to data science
Theoretical principles of Python
Overview of Python editors
Python projects
Syntactic basics: basic data types, operators, control structures, functions, loops
Basics of object-oriented programming in Python: classes, methods and attributes

Data management in Python (2 days)

Introduction to numpy
Introduction to pandas
Brief overview of the os module
Introduction to SQL

Machine Learning (6 days)

Theoretical introduction to machine learning
Data management, data manipulation & data preparation
Classification algorithms
Regression algorithms
Cluster analysis
Time series analysis
Data Visualization (2 days)
Theoretical introduction to data visualization
Principles of data visualization
Introduction to Power BI
Basic functions in Power BI
Data visualization in Power BI
Python in an Operative Environment (3 days)
Theoretical introduction to frontend, backend, API, OS and databases
Python access to frontend, backend, API, OS and databases
Projects

Target audience

You have completed vocational training or graduated from a university or university of applied sciences.
You have an affinity for IT, software topics and programming.
In the future, you would like to take on activities in the field of data science and work with the Python programming language.

Entry requirements

A notebook computer is required for this training.
The software and tools used are made available during the training via virtual machines
Since the training also includes programming exercises under the guidance of the trainer, it is highly recommended to participate in the training with two monitors.