In this course, you'll discover the main features and benefits of the Python programming language, and how Python can help power your data analysis. Python is an object-oriented programming language based on objects that contain data and useful code. You’ll become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. You’ll learn about Jupyter Notebooks, an interactive environment for coding and data work. You’ll investigate how to use variables and data types to store and organize your data; and, you'll begin practicing important coding skills.



Hello, Python!
Dieser Kurs ist Teil von Spezialisierung für Google Data Analysis with Python

Dozent: Google Career Certificates
TOP-LEHRKRAFT
Bei enthalten
Empfohlene Erfahrung
Was Sie lernen werden
Explain how Python is used by data professionals
Explore basic Python building blocks, including syntax and semantics
Use Python's inherent capabilities to explore data effectively with built-in functions and keywords
Recognize the uses and benefits of Jupyter Notebook for data work and as a Python environment
Kompetenzen, die Sie erwerben
- Kategorie: Computer Programming
- Kategorie: Data Processing
Wichtige Details

Zu Ihrem LinkedIn-Profil hinzufügen
September 2025
4 Aufgaben
Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Erweitern Sie Ihre Fachkenntnisse
- Lernen Sie neue Konzepte von Branchenexperten
- Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
- Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
- Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 4 Module
Discover the main features and benefits of the Python programming language, and how Python can help power your data analysis. Python is an object-oriented programming language based on objects that contain data and useful code.
Das ist alles enthalten
2 Videos1 Lektüre1 Aufgabe
Become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. Learn about Jupyter Notebooks, an interactive environment for coding and data work.
Das ist alles enthalten
3 Videos3 Lektüren1 Aufgabe1 Unbewertetes Labor
Investigate how to use variables and data types to store and organize your data; and begin practicing important coding skills.
Das ist alles enthalten
3 Videos1 Lektüre1 Aufgabe2 Unbewertete Labore
Review everything you’ve learned and take the final assessment.
Das ist alles enthalten
1 Lektüre1 Aufgabe
Erwerben Sie ein Karrierezertifikat.
Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.
Dozent

von
Mehr von Data Analysis entdecken
Google
Google
Warum entscheiden sich Menschen für Coursera für ihre Karriere?





Neue Karrieremöglichkeiten mit Coursera Plus
Unbegrenzter Zugang zu 10,000+ Weltklasse-Kursen, praktischen Projekten und berufsqualifizierenden Zertifikatsprogrammen - alles in Ihrem Abonnement enthalten
Bringen Sie Ihre Karriere mit einem Online-Abschluss voran.
Erwerben Sie einen Abschluss von erstklassigen Universitäten – 100 % online
Schließen Sie sich mehr als 3.400 Unternehmen in aller Welt an, die sich für Coursera for Business entschieden haben.
Schulen Sie Ihre Mitarbeiter*innen, um sich in der digitalen Wirtschaft zu behaupten.
Häufig gestellte Fragen
Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace.
Data science is part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.
We highly recommend taking the courses in the order presented, as the content builds on information from earlier courses. This is the first course in a series of six courses that make up the Google Data Analysis with Python Specialization.
A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models.
Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.
Weitere Fragen
Finanzielle Unterstützung verfügbar,