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Comentários e feedback de alunos de Análise de dados com Python da instituição IBM

4.7
estrelas
13,847 classificações
2,048 avaliações

Sobre o curso

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....

Melhores avaliações

SC
5 de Mai de 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.

RP
19 de Abr de 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.

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51 — 75 de 2,041 Avaliações para o Análise de dados com Python

por Nora I

12 de Mar de 2019

Really great! Tons of information complemented with exercises. To deal with the amount of material, I suggest following the labs very closely and doing a bit of research in the Python documentation avalaible online. I have to say you really hit the core of the matter in this course!

por Luis H

4 de Jun de 2019

I liked so much that I solve more short test because it helps me to remember information easily and guess it allowed me to perform better. It's the first time I get 100% three times in final tests of each week.

por Cecil K

7 de Fev de 2020

The courses from IBM on Data Analysis, Visualization, Machine Learning are great. I am in an online M.S. program, and the material from IBM is lightyears ahead of my university material.

por Opetunde A

12 de Jul de 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

por Prakash C

6 de Jun de 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

por Siddhartha S

4 de Jun de 2019

Great Course. Amazing Work By the team. Concepts explained clearly, followed by the week end quiz to revise. The Labs Do a great work in helping out

por Aldy P S

7 de Mai de 2020

helps me a lot! FYI I was new to data science and programming language but this course helps me to understand business analysis with Python!

por Ted H

6 de Jun de 2019

Covers a lot of ground but the Python Labs are great at bringing everything together.

por Paulo B M d S

4 de Jun de 2019

A very complete course of Data Analysis.

por Mahmood H

16 de Mar de 2019

Tough but useful.

por Itshak C

13 de Abr de 2021

Loved the labs. Hated the Videos. The amount of information that is thrown at you in a 1 min video is very unsettling as it makes you think you haven't understood a word of what they say and then the labs immediately clear everything up and then you feel like the smartest person alive. It's an uphill battle at times but the end result is pretty helpful regardless of the reason you're perusing the course.

por Vincent Z

10 de Mar de 2019

The course content is definitely interesting, but the approach is superficial. You will get a broad overview of the keyword to search for, and what is available in popular Python packages. However, the quizzes are way, way too easy. The course needs a final "open" assignment, where you have to use the tools without being guided along the way. This is the only way to truly learn.

por Mahvash N

4 de Mar de 2019

Course was great but it had number of errors and typos, that per my experience and other attendees caused some confusion.

I am sharing so it could be improved as it is a dream come true for myself to gain this valuable knowledge as conveniently as possible.

Thank you.

Mahvash Nejad

por Natalia Z

21 de Set de 2020

A very comfortably created course - no stress at all. However all that you can get is become familiar with the data analysis tools. May be that's the point.

por Ruchir

19 de Dez de 2018

I think few more practical exercises or at least references of the same would help better understand the overall fundamentals.

por Rebecca V

5 de Mar de 2019

Material covered is useful, but there are a lot of typos and mistakes in the lecture slides and labs.

por Rene P

24 de Mar de 2019

There could be links to functiones libraries in the lab for a fast check of a function if needed.

por Ugur S O

21 de Dez de 2020

I think the quizzes can be in the format of programming required questions.

por Charles C

5 de Fev de 2019

Some mistakes/ typos in the exercises and slides, but great overall

por Yogish T G

30 de Mar de 2019

An assignment should have been included

por Miguel E M

15 de Abr de 2020

There where some typos in the labs that could confuse most learners. I didn't feel like the course prepared people for real applications. The final project was quite hard because of this .

But it does give you a wide vision on hoy pandas work and some basic but apparently often used tools.

I see this course as a complement to a more detailed data analysis resource or perhaps as simply as an introductory view.

por Jaime V C S

22 de Fev de 2019

Hello,

in this course there were some errors on the slides, and some quite complicated topics (almost every time related to statistics) was given in a very over-viewed way. Also, some of the python codes were not explained very well, with some terms of them seem to be kind of arbitrary for those who are beginners in the language. My impression is that this course should be longer and more detailed.

por arda

20 de Nov de 2018

Overall I benefitted the course material as a beginner in python and data analysis. The questions were too trivial but maybe that helped me remain engaged with the course and complete it in a short time frame. There were some bugs, typos and minor quality issues that did not really effect my overall experience.

por Katarina P

27 de Jun de 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.

por Sadanand B

7 de Fev de 2019

Seems like there are quite a few errors in the labs that confuse the heck out of a student. The labs need to be fixed else the material becomes useless.