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....

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.

筛选依据：

创建者 Thierno K

•May 28, 2020

Excellent Course, i've learned a lot, i can analyze any data and give a conclusion from it. It's great course with a very clear explanation. If you are not understanding from the videos you can have a full understanding of the course from the Lab Notebook. The best is giving you a chance to access on IBM Cloud, creating new dynamic projects. Thank you

创建者 Ram K

•May 7, 2020

Initial part of course was easy, but the labs proved more and more useful. As I learned the course, I applied the charting skills directly to work, and was able to use Pandas to combine data from 3 databases, evaluate and report on the data to my company. It is already making a difference in our ability to make better data driven decisions every day.

创建者 Mona A

•Jun 17, 2019

Great Course! I got a great insight into multiple steps involved in data analysis using python starting from an initial data set to pre-processing it, exploratory analysis, doing multiple operations to create possible models and ways to evaluate the models. I hope to be able to use them to solve some sample data sets and come up with possible models

创建者 Volodymyr C

•Jun 23, 2019

Did this after Andrew Ng's Machine Learning to learn to do the same things in Python. Great course for people somewhat familiar with Python basics (I used datacamp to get a feel for Python and methods etc. first). Labs were really good for reinforcing knowledge from quizzes and videos. Overall, very nice course - will recommend to others!

创建者 Ramjan A

•Dec 19, 2018

This is my first course that i completed, and i am very glad to do this .

thanking you for giving me this opportunity to enrolled this course

i learned a lot of new things from this course this was very fruitful for me.

the slides was nicely represented and the way of teaching was so amazing

i am very very thankful to all the Coursera Team

创建者 Penchalaiah G

•Aug 7, 2019

This course is very use for regression model end to end scratch of evaluation and easily understand the coding theory explanation but ridge regression is somewhat improvement is needed.

Finally, I suggested to this course for learning data analysis with python.

Thanks for wonder full opportunity to learn this course in course-era team...

创建者 Muhammad Y

•Oct 7, 2018

This course is probably the most concise and well explained course I have ever taken on the subject. Materials are explained very well, and in a concise manner. The only downside is that the assessment for this course is based on quizzes, which are way too easy. Nevertheless, the course contains ungraded labs which are really useful.

创建者 Azhar S

•Mar 2, 2022

Good course for beginners, kindly remove the project at the end of the course, make two projects one after completion of 50% of the course and the remaining after 75% of the course.

increase the questions that are mostly related to project, practical work, interview with more focus on the conceptual understanding, than on the syntax.

创建者 Mihailo P

•Apr 12, 2020

This is the most complex course in the IBM Data Specialization Curriculum until now. There is a lot to cover and I would advise the students to go through the notebooks for practice 2 times to make sure to remember everything. One thing that is a bit confusing are functions for creating plots as we did not cover them in details yet.

创建者 Rohit B

•Mar 16, 2020

Awesome course on gaining Python skills for performing structured data analyses. If you are already attending the IBM Data Science certification, this course is a "step up" from the initial courses to bring a lot of things together. I would highly recommend doing it in the recommended order, else the learning curve may be too steep.

创建者 Diderico v E

•Feb 2, 2020

Wow! Excellent course that provides a great skills-focused overview on how to do data analysis with Python. The videos are first-rate, high quality and summarize the essential points nicely. The data set is real and it is used throughout the course and that helps understand the different features of data analysis taught by pandas.

创建者 Helena R

•May 1, 2022

Not that the course was over-challenging. A few ideas were better explained (Ridge Regression, Polynomial Models & pipelines). Would have preferred to have had access to slides rathan than the textual notes. Thought that the discussion forum was extremely helpful and the staff who responded earned their rightl. Congrats.

创建者 Stuart S

•Apr 2, 2020

Great introduction for using Python for data analysis. I found the segments on using Pandas, scikitlearn, and Matplotlib, particularly useful. Also, the labs' use of Jupyter notebooks, were excellent, because of the ability to introduce new variables or other data, and to see how it affects the outcome. Thank you very much!

创建者 Dongre O

•May 2, 2020

This course gave me very good understanding on basic concepts in Data Science and how we can make use of python. I would recommend this course to people who are searching for basics of data science. If you are from programmer then you will be able to correlate software development life cycle and Data Science Development.

创建者 Mmr R

•May 27, 2019

It was really helpful for me. Now i can clearly explain what is data. How we can explore data from a big data-set, How we can analyze different type of data-set. I am so much happy with this course. Now i will try to use this technique in my next steps. Special thanks Coursera community for creating this opportunity.

创建者 David A

•Oct 16, 2019

Very useful analytical techniques were learned such as cleaning the data, multiple linear regression, and working with test and training data. This course gave me a good foundation on the approach to analyze large databases. I also feel this will help in learning R because I now know the analytical process.

创建者 Mayank S

•Jun 12, 2021

Trust me! This is best course for beginners, This is how it should be taught. No previous coding experience needed, even mathematics used is explained clearly. Making notes will help you in future while writing codes. After this course, you can confidently move to other courses of IBM Data specialization.

创建者 Юрий Д

•May 9, 2022

Hello. Very cool course, designed not for beginners in python. Due to difficulties in translation, I had to additionally search for information on the Internet + take notes in Google documents. Sometimes you get very immersed in the ongoing process and forget about the time. Thanks to course developers.

创建者 Aakanksha R

•Sep 20, 2020

It is a really well-planned and informative course. The labs provided after every chapter are indeed a lot helpful to understand, recollect and visualize what we learnt during theory lectures. I would recommend this course to all as I found it helpful to improve my Data Analysis & Visualization skills.

创建者 Sachin B

•Nov 27, 2021

I always fascinated towards programming languages from university days as it makes the complicated work easier. as having basic cleared about python helps me to sail out through this course. all levels are thoroughly covered with proper scripts which make better understanding even for newcomers also.

创建者 Meenakshi S A

•Nov 20, 2019

It was a very interesting and correctly paced course for learning Data Analysis with Python. The course content and the assignments were very helpful in understanding the course well. Will recommend this course to all who want to do a well paced introductory course on Data Analytics using Python

创建者 Md. R H

•Sep 22, 2019

This course is outstanding valuable for the beginners who wants to build their career as data analysist. I have learned a lots of valuable statistical and progrmming for data analysis. Thanks to all instructor to give us such a opportunity to learn such kind of code and method for data analysis.

创建者 Marta F d O F d N N

•Jun 2, 2020

This was a great introductory course to statistical modeling with Python. I learned a lot of the basic methods to perform linear regression models and to describe statistical variables. The final assignment was slightly challenging, but doable if you follow the labs. All and all a great course!

创建者 Jamiil T A

•Jan 1, 2019

Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.

创建者 Alpesh G

•Aug 11, 2021

This course starts with Importing the dataset in Jupyter Notebook, followed by Data Wrangling, Exploratory Data Analysis, Model Development and Model Evaluation, and end with the final assessment applying all the concepts learned.

Thanks to IBM and Coursera for this great learning experience.