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....

May 06, 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.

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.

筛选依据：

创建者 Albert O

•May 19, 2020

Amazing content. I learned a lot of concepts used in analyzing data in Python. Examples in the course made it simple and easy to practice and understand.

创建者 AVIJIT B

•Apr 21, 2020

This course is good for someone who wants to start learning machine learning. It covers all the relevant topics which will help you in machine learning.

创建者 Ezeoke C

•May 12, 2020

This course was packed with a lot of details. I mean a lot. If one doesn't take his/her time to go through everything, it would just become overwhelming

创建者 Robert F

•Mar 08, 2020

Very Good Course. I really learned what Data Analysis really is ... opened my eyes! Very useful course for industry as well, I would imagine. Thank you!

创建者 Dwight

•Jan 26, 2020

This was an excellent course that had datasets with which to work with. With practice and exploration of data wrangling, my confidence level is growing.

创建者 Wedrick A E

•May 14, 2020

This course is quite challenging compared to the past courses. It really needs you to review and understand everything before you can pass the quizzes.

创建者 Bill G

•Sep 20, 2019

Wow!! Great course!

I learned a LOT. The material is not easy, especially for a non-math person but is one of the best courses I have taken on Coursera.

创建者 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.

创建者 朱晓琳

•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.

创建者 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.

创建者 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.

创建者 Moez B

•Feb 01, 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.

创建者 Minhaj A A

•May 02, 2020

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

创建者 Soumak M

•Mar 22, 2020

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

创建者 Federico E B C

•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.

创建者 K. S S

•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.

创建者 Tanveer J

•Jul 07, 2019

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

创建者 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.

创建者 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

创建者 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.

创建者 Syed F H R

•Aug 31, 2019

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

创建者 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.

创建者 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.

创建者 Uzair A

•Apr 02, 2020

Very well thought out course to help someone kick-start their career in data science/analysis. Really loved the videos and the lab exercises.

创建者 Ramanuj M

•Dec 26, 2019

The course gave a brilliant insight into data analysis using Python. Some issues related to deprecation will hopefully be resolved with time.