Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
제공자:
IBM이 강좌에 대하여
최근 조회 658,897회
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공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
초급 단계
완료하는 데 약 14시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 터키어, 영어, 스페인어, 페르시아어
배울 내용
Describe Python data acquisition and analysis techniques.
Analyze Python data using a dataset.
Identify three Python libraries and describe their uses.
Read data using Python's Pandas package.
귀하가 습득할 기술
- Predictive Modelling
- Python Programming
- Data Analysis
- Data Visualization (DataViz)
- Model Selection
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
초급 단계
완료하는 데 약 14시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 터키어, 영어, 스페인어, 페르시아어
제공자:
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 2시간 필요
Importing Datasets
In this module, you will learn how to understand data and learn about how to use the libraries in Python to help you import data from multiple sources. You will then learn how to perform some basic tasks to start exploring and analyzing the imported data set.
완료하는 데 2시간 필요
6개 동영상 (총 20분), 1 개의 읽기 자료, 6 개의 테스트
완료하는 데 2시간 필요
Data Wrangling
In this module, you will learn how to perform some fundamental data wrangling tasks that, together, form the pre-processing phase of data analysis. These tasks include handling missing values in data, formatting data to standardize it and make it consistent, normalizing data, grouping data values into bins, and converting categorical variables into numerical quantitative variables.
완료하는 데 2시간 필요
6개 동영상 (총 19분), 1 개의 읽기 자료, 6 개의 테스트
완료하는 데 2시간 필요
Exploratory Data Analysis
In this module, you will learn what is meant by exploratory data analysis, and you will learn how to perform computations on the data to calculate basic descriptive statistical information, such as mean, median, mode, and quartile values, and use that information to better understand the distribution of the data. You will learn about putting your data into groups to help you visualize the data better, you will learn how to use the Pearson correlation method to compare two continuous numerical variables, and you will learn how to use the Chi-square test to find the association between two categorical variables and how to interpret them.
완료하는 데 2시간 필요
6개 동영상 (총 20분), 1 개의 읽기 자료, 6 개의 테스트
완료하는 데 2시간 필요
Model Development
In this module, you will learn how to define the explanatory variable and the response variable and understand the differences between the simple linear regression and multiple linear regression models. You will learn how to evaluate a model using visualization and learn about polynomial regression and pipelines. You will also learn how to interpret and use the R-squared and the mean square error measures to perform in-sample evaluations to numerically evaluate our model. And lastly, you will learn about prediction and decision making when determining if our model is correct.
완료하는 데 2시간 필요
6개 동영상 (총 27분), 1 개의 읽기 자료, 6 개의 테스트
검토
- 5 stars75.70%
- 4 stars18.78%
- 3 stars3.84%
- 2 stars0.92%
- 1 star0.73%
PYTHON을 사용한 데이터 분석의 최상위 리뷰
CT 제공2021년 5월 13일
Good course, sometimes moves a bit fast in the final modules and the labs are quite tough but great course and would recommend to broaden your knowledge of coding, data analysis and visualisation
MA 제공2020년 7월 28일
AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.
SC 제공2020년 8월 11일
Thank you very much to the instructors. I liked the course but it could have been better designed. More exercises ascending from easy to hard & real and teaching quiz questions would make it perfect.
RP 제공2019년 4월 19일
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
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