This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Introduction to Programming with Python and Java
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Spezialisierung Introduction to Programming with Python and JavaUniversity of PennsylvaniaÜber diesen Kurs
83.739 kürzliche Aufrufe
Flexible Fristen
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Zertifikat zur Vorlage
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100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Anfänger“
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
Ca. 17 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Koreanisch
Was Sie lernen werden
Apply basic data science techniques using Python
Understand and apply core concepts like Data Frames and joining data, and use data analysis libraries like pandas, numpy, and matplotlib
Demonstrate how to load, inspect, and query real-world data, and answer basic questions about that data
Analyze data further by applying learned skills in data aggregation and summarization, as well as basic data visualization
Kompetenzen, die Sie erwerben
- Data Science
- Python Libraries
- Python Programming
- Data Analysis
- Data Visualization (DataViz)
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Anfänger“
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
Ca. 17 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Koreanisch
von
University of Pennsylvania
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieser Kurs gehört zum reinen Onlineabschlusses Master of Computer and Information Technology von University of Pennsylvania. Er bietet Ihnen eine Vorschau auf die Themen, Materialien und Lehrkräfte, damit Sie entscheiden können, ob der komplette Online-Studiengang das Richtige für Sie ist.
Lehrplan - Was Sie in diesem Kurs lernen werden
6 Stunden zum Abschließen
Module 1 : Loading, Querying, & Filtering Data Using the csv Module
This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.
6 Stunden zum Abschließen
8 Videos (Gesamt 31 min), 9 Lektüren, 3 Quiz
5 Stunden zum Abschließen
Module 2 : Loading, Querying, Joining & Filtering Data Using pandas
In this module, students are introduced to core concepts like the Data Frame and joining data. Students will get experience using pandas, an industry-standard data analysis library, to load and query real-world data and to answer questions about that data. This module demonstrates how to do advanced filtering and indexing, slice subsets of data, restrict data attributes in query results, and do basic computations over the data. Includes how to build a simple recommendation system, and approaches for cleaning data, dealing with missing values, and creating new data.
5 Stunden zum Abschließen
14 Videos (Gesamt 31 min), 5 Lektüren, 4 Quiz
5 Stunden zum Abschließen
Module 3 : Summarizing & Visualizing Data
This module takes data analysis a step further by providing an overview of the process of aggregating, summarizing, and visualizing data. Students are introduced to the concept of grouping and indexing data, and how to display results in a pivot table using pandas. This module also demonstrates how to prepare and visualize data using a histogram and scatterplot in Jupyter Notebook. Students will gain skills in data aggregation and summarization, as well as basic data visualization. In addition, students will get experience using data analysis libraries like numpy and matplotlib.
5 Stunden zum Abschließen
18 Videos (Gesamt 22 min), 5 Lektüren, 4 Quiz
Bewertungen
- 5 stars66,96 %
- 4 stars25,44 %
- 3 stars4,46 %
- 2 stars1,33 %
- 1 star1,78 %
Top-Bewertungen von DATA ANALYSIS USING PYTHON
von AL24. März 2021
Very informative course. However lessons feel more like telling than teaching. The lecturer could go more in depth.
von JJ3. Mai 2021
this was very useful and well prepared course. Thanks a lot
von LH24. Mai 2021
I'd like for this to be a little more in-depth. I had fun with the data visualisations. However, probably more of manipulating the data would be good.
von PS21. Feb. 2022
Great course for the beginners, would like to thank faculty and staff for making a great course, and the discussion forms were really helpful, Thanks to TAs for reverting back to all the questions.
Über den Spezialisierung Introduction to Programming with Python and Java
This Specialization starts out by teaching basic concepts in Python and ramps up to more complex subjects such as object-oriented programming and data structures in Java. By the time learners complete this series of four courses, they will be able to write fully-functional programs in both Python and Java, two of the most well-known and frequently used programming languages in the world today.
Häufig gestellte Fragen
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How much math do I need to know to take this course?
This course was fun. How can I learn more?
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