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!
Topics covered:
1) Importing Datasets
2) Cleaning the Data
3) Data frame manipulation
4) Summarizing the Data
5) Building machine learning Regression models
6) Building data pipelines
Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts:
Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

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.

Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

필터링 기준:

교육 기관: Alexandr D

•Oct 17, 2018

Very low quality of the course. The structure of the course is illogical. Also it takes too little effort to accomplish the course. In the beginning of th course labs contain all the code so a pupil doesn't have to do his/her best to solve tasks. I can just constantly press ctrl+enter and get my certificates. It is not what I expected from the course. Also quizes never contain coding practice, so to accomplish I just need to show the understanding of the basic aspects of the topic, not the coding skills. The, at the end of the course (after I have lost all the motivation during the first weeks you give us difficult function, including custom functions, never explaining them at all). Have a huge doubt about buying the subscribe for the next month.

교육 기관: Guy P

•Dec 06, 2018

So many mistakes in videos and labs, including spelling errors, misnaming functions and code that causes errors.

These have been listed extensively in the course discussion forums, with some complaints from over 6 months ago, and have not been addressed

교육 기관: Amy P

•May 19, 2019

I am working through the IBM Data Science Certificate courses (in order) and this is easily the best one I have taken so far. Once again, the labs provide a variety of hands-on exercises that help to cement the topics introduced in the lectures (which, to be fair, are very fast-paced). Everything taught is practical and relevant. One request would be to fix the pacing of the videos and lecture quizzes, which often appear to test students' comprehension mere seconds after the topic was discussed! I did also notice a few errors in the labs, but they did not stop me from learning the material. Overall, great course.

교육 기관: Karen B

•May 26, 2019

Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.

교육 기관: Oana M

•May 22, 2019

Thank you so much! - Oana

교육 기관: ashirwad s

•May 22, 2019

Recommended course to understand the how to do data analysis using python

교육 기관: Aditya M

•May 21, 2019

Overall apt content for beginners and naive learners.

교육 기관: Jim C

•May 20, 2019

Well organized, good explanations, and very good labs.

교육 기관: Vineet M N D

•May 20, 2019

Great experience

교육 기관: Theodore G

•May 19, 2019

This needs to go much more in depth on the options for analysis, and provide more examples.

In addition, the labs and final exams were not fully completed/corrected/reviewed, so there were many erroneous issues, including assumptions made that was not clear to us students.

교육 기관: Sampras G

•May 19, 2019

best course for beginners

교육 기관: Firat G

•May 18, 2019

A seriouse deal of statistical modelling taught with a perfect content. I really appricate the effort put in order to not being "hard-to-understand", but still finding the way to teach complex statistics. You will have a very good useful knowledge of statistical modelling without getting lost through too many greek symbols and long explanations.

교육 기관: Aditya J

•May 18, 2019

None

교육 기관: Rohit P

•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.

교육 기관: Maksim M

•Apr 18, 2019

Very serious, professional, empowering course. Clear straightforward detailed explanations. A good deal of practice.

교육 기관: Daniel T

•Apr 09, 2019

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

교육 기관: Uygar H

•Mar 14, 2019

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

교육 기관: Pauli H

•Feb 22, 2019

Many typos and other errors. My favorite was the video where they said "150 - 50 = 50"

교육 기관: Ivo M

•Dec 19, 2018

The course had plenty of errors in the videos, Labs and quizzes. The explanations were rushed at times and quite a bit was not easy to follow. The worst course so far!

교육 기관: Florian P

•Dec 11, 2018

Decent introduction to basic concepts of data analysis. However, the 'labs' and quizzes feel insufficient to practice the theoretical aspects. Further on the downside, the quality of the material in this course is quite poor. Even worse, several months after learners mention errors in the discussion forums (and partly get an instructor response), the mistakes remain in the material.

교육 기관: Vikram R

•Dec 04, 2018

I felt the course isn't designed well as it takes you little fast than expected and doesn't explain all the terms! May be one has to be very good at math or revise all the topics before taking this course.

교육 기관: Polina S

•Jul 05, 2019

Thoroughly appreciate the effort to put this course together, however there are several problems (I think this is the worst quality course I've seen on Coursera so far .. or maybe all other ones have just been great!) -- a) the instructional videos contain many errors in both code syntax, and, worse, in logic; b) questions on Forums take a long time to be answered, and staff member who responds to most of them appears to be a bot/only provides vague general info; c) course material has ups and downs, for example Inferential Statistics are blazed through within 15-20 minutes, and there is very little discussion of, say, how to identify the distribution of your data, how to decide on parametric/non-parametric tests and so on.

교육 기관: Sevak G

•Jul 02, 2019

HOW IS THIS COURSE BEFORE DATA VISUALIZATION??????????!!!!!!!!!!!!!!!!!!!!!!!???????????

교육 기관: Katarina P

•Jun 27, 2019

Many typos in videos, stats explained on a very rudimentary way (and often inaccurate), Watson environment is awful as it takes ages for some simple regression plots to be made, it freezes and the interface is not user-friendly, yet we have to use it.

교육 기관: Prakash C

•Jun 06, 2019

Great course. I had fun having a kick start in the field of data in machine learning. I understood the concepts related to how to improve the model.

Thank you