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Вернуться к Анализ данных с Python

Отзывы учащихся о курсе Анализ данных с Python от партнера IBM

4.7
звезд
Оценки: 13,454
Рецензии: 1,974

О курсе

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....

Лучшие рецензии

RP
19 апр. 2019 г.

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
5 мая 2020 г.

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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151–175 из 1,955 отзывов о курсе Анализ данных с Python

автор: Ketan K

28 дек. 2018 г.

Really a step up in terms of difficulty compared to "Data Science with Python". Since the final week's content is judged on quiz and not a stand alone assignment, one must revise this course from time to time for the libraries referenced and model analysis approach. Great resource!

автор: Anthony G

25 янв. 2021 г.

This course was presented clearly and explained statistical concepts in a way that made them relevant and practical. The assignments were challenging, requiring review of notes and Python techniques made during the lectures, thereby reinforcing the learning outcomes in a good way.

автор: Gajula J

16 июля 2018 г.

This course is very good start for students who are planning to go into machine learning specifically.Students who have no Idea about regression and math find bit hard but little more effort from student side is needed. At the end you will have a zeroth tool for machine learning.

автор: Babak K Z

30 нояб. 2020 г.

very good and goal oriented cours, no loss of time , covers rapidly subjects that really increase students knowledge on python tools for data analysis. very interesting and useful cover on regression for tolls as well as explaining the statistical concept in a very simple way.

автор: RISHI K

26 окт. 2020 г.

THE RATING IF POSSIBLE TO GIVE 100 THEN I CAN GIVE 100 FOR SURE , BUT OUT OF 5 IT DESERVES 5 WITHOUT ANY DOUBT I CAN SAY THIS COURSE CONTAINS THE ALL BASICS + ENSURES A GOOD UNDERSTANDING OF ALL THE THINGS NEEDED TO DEVELOP THE DATA ANAYSIS SKILLS ALONG WITH PRACTCAL APPROACH .

автор: federico b c

12 мая 2020 г.

It's a great course. I enjoyed a lot. Easy to follow.

However I miss go deeper with the meaning of the numbers (for example the R2 each time we calculate it) and to get deeper insights of the data after having on the table many interesting number for the analysis.

Thanks for all.

автор: Veon G

5 июня 2020 г.

I have a specialist diploma with business analytic. However that was using software to do the visualization and analysis.

I guess it helps on my journey. I can relate the machine learning concept to this course.

This course is fantastic. Teaching you step by step progressively.

автор: Matt M

29 июня 2020 г.

Great overall experience. Although it would be great actually understanding the Python language in ways where you're actually learning about what each code means and does, I think this is more of an introductory course in terms of just understanding what Data Science is.

автор: Dharmeshkumar P

14 апр. 2020 г.

Good course giving exposure across all expect of data mining and data analysis with regression modeling and evaluation model through visualization and correlation, Rscore and much more. Very well organised modules with jupyter notebooks for each assignment and practice.

автор: Jason J D

12 сент. 2019 г.

Really good course in Data Analysis for beginners. The videos and labs are very well planned and structured. Personally, I can say for sure that I have gained more knowledge about Data Analysis and am even more motivated towards Data Science after completing this course.

автор: Sushant S

7 апр. 2019 г.

This course give a great introduction to the Python Packages and methodology to visualize the data and also evaluate the Model. This is good introduction course which gives concise understanding of concepts and all important python libraries required to get the job done.

автор: Holt M

19 июля 2020 г.

This is how all the courses should be set up. Weeks are set up in an organized fashion of Videos, Lab, Quiz. No major things missing from instructions that waste your time, like the other IBM SQL course. Shout out to Joseph Santarcangelo for planning a beautiful course.

автор: Sergey F

7 авг. 2020 г.

Very good introduction course into data analysis. Would be nice to elaborate more on Ridge and pipelines. Explanation of the math behind the library functions or references for further study would also help understand what method is more suitable for certain tasks.

автор: Javed A

20 окт. 2019 г.

What an amazing way to learn such a special set of skills from best platform of Coursera.

The IBM Skills Network Lab is really fantastic.

Also on IBM studio is speechless.

I will definitely recommend this must have course to all passionate learners around the globe.

автор: KULDEEP P

13 июля 2018 г.

Help to understand the process of doing projects on Data Science , As i tried to start with one Data set but i was not sure what to do, how to do. with the help of this course, I came to know the step by step process of Data Wrangling and making models. Thanks

автор: Theodore G

18 февр. 2021 г.

Covered a lot of great material. Sometimes I went to other sources on the internet to get some more detail on parts that I did not understand. I all turned out well. The quizzes and labs are important. I must have taken a lot of work to put all this together.

автор: Sagar S

17 сент. 2018 г.

This is very condense course. However the quizzes after every chapter are very timely, and one at the end of the week for entire week, helped a lot. The labs seems very real world, downloaded some notebook am sure will be using them in real world later on.

автор: Lu L

28 июня 2020 г.

Well-structured. Offered clear instructions in the subject of model development, model selection and model evaluation. This lays the foundation to help me to learn further on these topics. The exercise for each unit is a good summary, helpful for review.

автор: Juan F B

11 апр. 2020 г.

Very good coverage of basic skills needed for Data Analysis. Not very challenging if you have previous experience programming and have a general understanding of basic statistics. Would've liked a more "interactive" course regarding the codding assignments.

автор: Jacob G

4 мар. 2021 г.

The labs that included Jupyter Notebooks were very well done and left me feeling like they weren't impossible, but challenging enough to solidify my skills. Labs are extremely important for me in an online learning environment, and these were great.

автор: Abdulahi O F

21 авг. 2019 г.

I am highly impressed with the teaching methodologies and how the course is structured. By now, I can import, determine data types, conduct data wrangling which involves replacement ir dropping and regressions. Thanks to Cousera for the opportunity.

автор: Ittiphon S

4 июня 2021 г.

This it the first course I take it help me to understand Data Analyst way such as Systematic Thinking, Coding concept,This is great

And to the future learner You should have a basic of coding in PYTHON it may help to easily complete this course but

автор: Luciana M G

14 мар. 2019 г.

This course is an excellent continuation of the previous IBM ones. Actually there should be one whole course teaching the basics of statistics so that what is taught in this model makes more sense for those who have never studied statistics before.

автор: Riccardo B

14 июля 2020 г.

I really enjoyed this course. The content was well described. Quite complex, it required me to explore other external material, probably because I lacked the sufficient statistical knowledge to run through the course smoothly.

Thank you Coursera!