Module

Advanced Python Programming for Data Scientist.

Training for object-oriented programming (OOP) with Python

Module description

Part time

German, English

The goal of this course is to learn object-oriented programming (OOP) with Python. In addition, you will learn the basics in Bash and Git to use and create code collaboratively in a team.

The automation of digital processes and the analysis of large amounts of data often require customized solutions for use in the company. For this reason, Data Scientists should be able to generate production-ready code collaboratively in a team.

In this module you will learn:

Advanced Python Basics

OOP Basics

Advanced OOP

Create and customize modules, classes and objects
in the Python framework
Independent processing and presentation of software projects
Use of Git and Bash for collaborative work on software projects

Table of contents

1
Introduction

Goals:

Using the command line to navigate in folder structures
Viewing and searching text documents in the command line
Executing scripts and installing programs
Writing clean code according to recognized standards

Contents:

Introduction
- Get to know each other
- Training process and insight into the modules
- Introduction to the learning environment
Bash basics
- Command line
- Navigation in folder structures
- Creating, copying and deleting folders and files
- Filtering text files and scripts
- Chaining commands with pipe operator
- Editor Nano
- Installation of programs
- Executing Python scripts
- Environment variables
- Rights management
- Bash script
Advanced Python basics
- Function definition
- Flow control
- List and dict comprehensions
- Clean Code & PEP 8

2
Introduction to Git and object-oriented programming

Goals:

Creating and updating projects with Git
Collaborative use of Git

Contents:

Introduction to Git
- Definition of the term: version control
- How Git works
- Creating and cloning projects
- Git workflow
- Branching & merging
- Solving merge conflicts
Introduction to object-oriented programming
- Principles of object-oriented programming
- Classes and instances
- Attributes
- Methods

3
Repetition of OOP, inheritance and composition in Python, unit testing

Goals:

Defining and using classes and assumptions about assertions
Creating and using unit tests

Contents:

Repetition: Introduction to object-oriented programming
Inheritance and composition in Python
- Simple inheritance
- Multiple inheritance
- Composition
- Inheritance hierarchy
Unit testing
- Definition of terms: unit test
- Conventions for test naming
- Test assertions
- Set-up methods

4
Advanced object-oriented programming with Python

Goals:

Using and defining Decorator
Select and use external modules for typical tasks
Presenting results and discussing them using technical language
Writing clean code according to recognized standards

Contents:

Advanced object-oriented programming with Python
- Operator overloading
- Decorators
- Special methods
Modules of the Python standard library
- os
- pickle
- json
- zipfile
- collections
- difflib
Project: Customizing transformers in the machine learning pipeline
Final test

You want this module detached from the entire training program and without an education voucher complete? We offer flexible payment and financing options for self-paying participants. Please contact directly to our consulting team for more information.

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FAQ

What sets StackFuel apart from other training providers?

Our training courses are developed and produced by our own team of data scientists and subject matter experts, who provide you as a participant with personal mentoring during the course. We not only focus on realistic and practical content, but also ensure that all your questions are answered in a personal exchange and thus guarantee your learning success.

Thanks to our "learning-by-doing" principle, you will learn in our interactive learning environment with realistic data sets and real business cases from the industry, preparing you perfectly for a successful career start in a data job.

Why is StackFuel the right choice for me?

With StackFuel, you can rely on a market leader with Germany's most innovative learning platform to develop your data skills in a practical way. In certified training programs, you learn online, flexibly and with 80 % of practical content.

This will enable you to make a lateral entry as a data analyst or data scientist and learn how to use data and the basics of artificial intelligence professionally. Your new data career starts with your online training at StackFuel.

How can data skills help me to start a new career?

Data has become an integral part of our (professional) lives. In almost all areas, data helps you to better understand facts and make more precise decisions. Data skills are the key to being able to use and interpret data correctly. Even though you may not realize it, you work with, interact with and generate data every day.

This data is becoming increasingly important for companies and is the basis for decisions and business models, which makes data professionals incredibly important for companies.

Advanced Python Programming for Data Scientist.

1
Introduction

2
Introduction to Git and object-oriented programming

3
Repetition of OOP, inheritance and composition in Python, unit testing

4
Advanced object-oriented programming with Python

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FAQ

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On German servers from:

Advanced Python Programming for Data Scientist.

1Introduction

2 Introduction to Git and object-oriented programming

3Repetition of OOP, inheritance and composition in Python, unit testing

4Advanced object-oriented programming with Python

Do you still have Questions?

FAQ

Profit promotion program

Sponsored by

Member with

On German servers from:

1
Introduction

2
Introduction to Git and object-oriented programming

3
Repetition of OOP, inheritance and composition in Python, unit testing

4
Advanced object-oriented programming with Python