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.
이 강좌는 Introduction to Programming with Python and Java 특화 과정의 일부입니다.
10,641명이 이미 등록했습니다.
이 강좌에 대하여
최근 조회 82,360회
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 2번째 강좌:
초급 단계
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
완료하는 데 약 17시간 필요
영어
자막: 영어, 한국어
배울 내용
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
귀하가 습득할 기술
- Data Science
- Python Libraries
- Python Programming
- Data Analysis
- Data Visualization (DataViz)
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 2번째 강좌:
초급 단계
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
완료하는 데 약 17시간 필요
영어
자막: 영어, 한국어
제공자:
펜실베이니아 대학교
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.
석사 학위 취득 시작
이 강좌은(는) 펜실베이니아 대학교의 100% 온라인 Master of Computer and Information Technology 중 일부입니다.
전체 온라인 학위 프로그램이 귀하에게 적합한지 여부를 결정할 수 있도록 주제, 자료 및 강사의 미리보기를 제공합니다.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 6시간 필요
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.
완료하는 데 6시간 필요
8개 동영상 (총 31분), 9 개의 읽기 자료, 3 개의 테스트
완료하는 데 5시간 필요
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.
완료하는 데 5시간 필요
14개 동영상 (총 31분), 5 개의 읽기 자료, 4 개의 테스트
완료하는 데 5시간 필요
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.
완료하는 데 5시간 필요
18개 동영상 (총 22분), 5 개의 읽기 자료, 4 개의 테스트
검토
- 5 stars66.96%
- 4 stars25.44%
- 3 stars4.46%
- 2 stars1.33%
- 1 star1.78%
DATA ANALYSIS USING PYTHON의 최상위 리뷰
GK 제공2021년 3월 26일
Good introductory course. Brandon Krakowsky explained all the concepts clearly.
SA 제공2021년 4월 13일
I can't really put it into words or appreciate enough how wonderful and valuable this course is.
KG 제공2021년 4월 12일
Excellent course. Assignments /home work explaination need to be rethought. Special thanks to Jahnavi for helping through out the course.
PS 제공2022년 2월 21일
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.
Introduction to Programming with Python and Java 특화 과정 정보
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.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
재정 지원을 받을 수 있나요?
How much math do I need to know to take this course?
This course was fun. How can I learn more?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
