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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.

Status: Data Preprocessing
Status: Matplotlib
IntermediateCourse17 hours

Featured reviews

BM

4.0Reviewed Jul 17, 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

4.0Reviewed Nov 12, 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

5.0Reviewed Dec 9, 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.

ND

4.0Reviewed Jul 31, 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.

BD

4.0Reviewed Nov 23, 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

RS

5.0Reviewed Jan 29, 2023

I am learning so much from this course. Video lectures are very easy to understand and the labs are interactive.My heart full gratitude to all the team of Coursera for providing valuable course.

SC

4.0Reviewed Mar 15, 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.

BK

5.0Reviewed May 9, 2021

I love the practicality of this course. It's not just learning theories but you actually follow along. You only need a good computer and you learn serious staff taught in the best way possible.

AM

5.0Reviewed Apr 17, 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.

MA

5.0Reviewed Dec 1, 2020

A compact course. Good one who want to learn within a short period of time. But if one wants to understand the topics well, then he/she should go through the documentation of respective libraries.

RP

5.0Reviewed Apr 20, 2019

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.

CD

5.0Reviewed Apr 16, 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.

All reviews

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Александр Денисов
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