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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
17,703 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews

RP

Apr 19, 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.

SC

May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

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401 - 425 of 2,715 Reviews for Data Analysis with Python

By Furkan G

Jul 28, 2020

This course is a good opportunity to test yourself in data science and moreover it provides you to advance your knowledge and skills in data analysis.

By Jorge S

May 15, 2020

Excellent module. It gave me a good overview of all components about data analysis. I applied it immediately to a case that I had in hands in my job.

By Xiaolin Z

Mar 12, 2019

This course is about regression, how to create models, how to evaluate and select a model or parameters. These are exactly what I would like to know.

By Walter M

Jan 27, 2021

I will recommend it. You should take care and you should try to understand the concepts first with the module exercises. Great base knowledge course!

By Ho Y C

May 29, 2020

Course lectures and materials are very well delivered and written. The lab sessions are interesting and difficulty level is just right for beginners.

By Anurag g

Mar 11, 2019

Amazing course to start data analysis with python. It covers most important aspects of data preprocessing in machine learning using python libraries.

By Moez B

Jan 31, 2019

Excellent course. The level of difficulty is not high, but you can still learn quite a bit from the videos and especially from the Jupyter notebooks.

By Minhaj A A

May 2, 2020

Refreshed my concepts about the statistics, regression and error calculation. Explained most of it in a very unambiguous manner. Highly recommended.

By Soumak M

Mar 22, 2020

An insightful course which is consized appropriately making one comfortable with basic statistics ,creating model pipelines and data visualizations.

By fedebenavides

Oct 26, 2019

Great course, I loved the final project because it really puts what you've learned to test. I wish there was more like a project like this per week.

By subiksha k

Jul 13, 2019

One of the best course for data analysis with python. It covers the concepts to start working on a project and has well detailed explanation to all.

By Tanveer J

Jul 7, 2019

Excellent combination of core statistical concepts being translated into digestible python codes.!! Yes I can comfortably use linear regression now!

By Justine “ S

Oct 2, 2022

Good comprehensive course about data analysis and how to use Python. It was more broad in toic and goes to show how to create and evaluate models.

By jevontkw

Sep 16, 2020

Great hands-on lab examples and step by step teaching which makes the content easily digestible even to those without much prior python experience.

By Jorge A C C

Jan 19, 2020

Muy didactico y util, recomiendo repasar algunos conceptos de estadistica para que sea mucho más comprensible los analisis que se estan realizando.

By Jesús A G C

Nov 7, 2020

I perceived a responsible and loyal attitude towards the student.

I learned a lot about how to analyze and manage data with a specific objective.

By SACHIN G

Oct 11, 2019

The course is made in very simple language, anyone can learn from this course. The most amazing part of the course is Lab. Love you IBM & COURSERA

By Reuben S A

Jun 7, 2023

The course was fun to do and a lot f learning and implementation of knowledge with the labs. much appreciation for all those who made it possible

By Sadgi S

Jul 15, 2019

Amazing course! I was looking for a comprehensive course which takes up step by step process for Data Analysis. I hit a jackpot with this course.

By Floribel G C

Jan 28, 2021

Excellent class. It includes everything you need to do data analysis and model in python.

Also includes practices and good audiovisual material.

By Fahad H

Aug 30, 2019

All the content was brilliant and complete, The teacher was quite amazing and he actually complete almost every thing in this course perfectly.

By Amit C

Jul 14, 2018

This course is very helpful as it is more industry oriented. I have personally found this course to be very smooth and beneficial for learning.

By Siddhi S

Aug 2, 2023

whoaa!! learnt a lot particularly in this course. Challenging, sure, and informative about lots of statistical measures used in data analysis.

By Pham T H

Nov 29, 2022

The course is well structured with excellently understandable instructions. The practice tasks are suitable for beginners like me. Thank you!

By Mariia G

Jun 26, 2020

Excellent course, provides all the needed information, practical examples. The way how material is presented is very convenient for learning.