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IBM

Data Analysis with Python

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

状态:Regression Analysis
状态:Pandas (Python Package)
中级课程小时

精选评论

BM

4.0评论日期:Jul 16, 2020

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should. A good starter course to wet your feet in DA!

MW

4.0评论日期:Nov 11, 2021

Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.

AA

5.0评论日期:Dec 8, 2021

Most of what you'll learn in this package are fundamentals to other knowledge areas. So, practice both in and out of the course. I​ appreciate the coordinators in making it possible. Thank you.

AM

5.0评论日期:Apr 16, 2023

Thanks for course! I met some errors, described them in your forms. I liked every models, but the final assignment was not interesting. I think it can be done better, with decisions and conclusions.

ND

4.0评论日期:Jul 30, 2021

T​otally overwhelmed with the course contents and easyness in teaching. The course will make you familiarize the fundamentals in a way that you will never forget when you used in a real world.

TG

5.0评论日期:Sep 5, 2023

Wonderful course, explained everything in the most easiest way possible. BUt hte module 4 and 5 ffeels kinda hard for a person who is not familiar with data visualization and machine learning.

CD

5.0评论日期:Apr 15, 2020

Great Introduction to Data Analysis, the concepts going from the basic to deep in data-testing and data-training, as well as several applications linear and polynomial regression to data analyze.

SC

4.0评论日期:Mar 14, 2025

This was a comprehensive course which dives deep into data analysis. The visualization part could still be improved, but nothing to take away from the course. It is one of the best out there.

CT

4.0评论日期:May 13, 2021

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

AB

5.0评论日期:Feb 12, 2020

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

BD

4.0评论日期:Nov 22, 2019

Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well

VS

5.0评论日期:Jan 30, 2022

This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.

所有审阅

显示:20/3,121

Александр Денисов
2.0
评论日期:Oct 17, 2018
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2.0
评论日期:Dec 6, 2018
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评论日期:Feb 22, 2019
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1.0
评论日期:Jun 25, 2019
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5.0
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1.0
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Abigail Benecke
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2.0
评论日期:Jul 4, 2019
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1.0
评论日期:Dec 1, 2019
Rohit Pradhan
5.0
评论日期:Apr 20, 2019
Stijn de blauwe
2.0
评论日期:Dec 29, 2018
Ahmed El Refaey
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评论日期:Mar 30, 2020
Vikram Raghava
2.0
评论日期:Dec 4, 2018
Usman Afridi
5.0
评论日期:Jul 28, 2020
TJ Griesenbrock
3.0
评论日期:May 19, 2019
Vera
1.0
评论日期:Apr 7, 2021
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1.0
评论日期:Apr 3, 2020
Mykyta Solonko
1.0
评论日期:Apr 27, 2020
Ivo Marcelino
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评论日期:Dec 19, 2018
Sobhan Ahmadi
1.0
评论日期:May 6, 2020