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.
Este curso faz parte do Programa de cursos integrados Introduction to Programming with Python and Java
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oferecido por
Programa de cursos integrados Introduction to Programming with Python and JavaUniversidade da PensilvâniaInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
Aprox. 17 horas para completar
Inglês
Legendas: Inglês, Coreano
O que você vai aprender
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
Habilidades que você terá
- Data Science
- Python Libraries
- Python Programming
- Data Analysis
- Data Visualization (DataViz)
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
Aprox. 17 horas para completar
Inglês
Legendas: Inglês, Coreano
oferecido por
Universidade da Pensilvânia
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.
Comece a trabalhar rumo ao seu mestrado
Este curso está relacionado à graduação Master of Computer and Information Technology 100% on-line pela Universidade da Pensilvânia. Ele fornecerá uma prévia dos tópicos, materiais e instrutores para que você possa decidir se o programa de graduação on-line completo é adequado para você.
Programa - O que você aprenderá com este curso
6 horas para concluir
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 horas para concluir
8 vídeos (Total 31 mín.), 9 leituras, 3 testes
5 horas para concluir
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 horas para concluir
14 vídeos (Total 31 mín.), 5 leituras, 4 testes
5 horas para concluir
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 horas para concluir
18 vídeos (Total 22 mín.), 5 leituras, 4 testes
Avaliações
- 5 stars67,82%
- 4 stars23,25%
- 3 stars5,42%
- 2 stars1,55%
- 1 star1,93%
Principais avaliações do DATA ANALYSIS USING PYTHON
por KP12 de abr de 2021
course is overall good but face some problem in understanding of homework questions, proper explanation is needed
por AM7 de fev de 2021
Videos touching same theme were too short (26 sec, 1 min, etc.) and disruptive. Wish there could be more practices.
por KG12 de abr de 2021
Excellent course. Assignments /home work explaination need to be rethought. Special thanks to Jahnavi for helping through out the course.
por FS29 de jul de 2021
it would be better if sections were covered more of panda and matplotlib and even seaborn
Sobre Programa de cursos integrados 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.
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