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

13,335 classificações
1,951 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

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.

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.

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1351 — 1375 de 1,931 Avaliações para o Análise de dados com Python

por Muhammad S H

17 de Mar de 2020

I think the course was good, but the complexity level of the labs was a bit high. I mean, the leap in skill level required could have been made more easier. There are many new functions utilized in the labs that we have not been made familiar with. So, a lot of documentation-perusal and sifting of other online resources was required, especially with the Polynomials and Ridge Regression, the last Lab. I think the contents of the last Lab (Model Evaluation & Refinement) should be elaborated on and explained with greater clarity, introducing new functions and code-parts along the way.

por Arnold W E

22 de Fev de 2020

One of the few good courses I have had. I learned a lot, used much of it in the labs. The lab for Week 5 was very confusing, as was the final one. The other labs were great, but Week 5 and the final were very disjointed and uneven. There were several things I had hoped they would put in the lab, but there was no first-to-last example lab, which is what I wanted. Without actual instructors (as in live training) this should be expected, and if I had paid for this I would be upset. Problems 7-10 on week 5 are garbage!

Still, one of the best on Coursera, from my limited point of view.

por Abdelrahman S

19 de Ago de 2020

The course is great but they don't really give enough information about some stuff, I hoped they would explain what is really the goal of alot of snipets of code and which part does what in a deeper level instead of just scratching the surface,

i had to teach myself somestuff and it was a little challenging for a while specially that i don't have statistics background i, Iam not talking about more content i mean more info more details in other words what's obvious for the developers who provided this course isn't that obvious for new learners

por Imtiaj A C ,

18 de Abr de 2020

Of course I've learnt a great deal about data analysis using python in this course. The course videos were made in a way that even the most difficult topics could one learn very easily. And after-module-labs were great to test the topics learnt.

One thing that stopped me from giving full 5-star was the final assignment. It was way too simple in my opinion. Most of the discussed topics weren't even there. I guess it would be much better to make the final assignment a little bit more thorough and to some extent, more difficult.

por Everett T

29 de Jun de 2019

The course is overall very helpful to learn Data Science with Python while it does require foundations for statistics for this module, so it appears difficult to understand some mathmetical concepts for beginners. Thus I suggest some more detail explainations/practices for core parts like model development.

Moreover, there are some mistakes/typos in labs, e.g. Week5's Model Evaluation and Refinement, though most of them are minor. Also some libaries are outdated (discovered thourgh warning outcomes), which may need updating.

por Jonathan K

8 de Mar de 2020

Good because provided breadth - teaching lots of different data analytics tools. The cons were that it didn't actually force you to code until the final product, and it also tried to do way too much in one course. I wish it just went more in depth into beginner topics like cross-tabs and linear regression, as opposed to trying to cover introductory stuff as well as beginning machine learning in one course - which caused the course to sacrifice depth - a deep understanding of any given topic.

por ira d G

4 de Jun de 2020

I love this course! I think it's well organized. And they made sure you really learn in the lab. I'm very hands-on when it comes to embedding important skills (via the lab exercises). I do wish they would associate the terms with, say, statistics or machine-learning, so I would delve into more research -- even more than necessary. Not everyone who wants to learn Python is already well-versed with the prerequisites. But overall, the course is thorough enough and well-articulated.

por Juan M L F

23 de Jan de 2020

This course is good if you already have some experience in Python and its structures, or if you have some knowledge in programming. You will learn some basic data manipulation and exploration techniques and also start with some of the model evaluation metrics in order to assess the (regression) models created. Overall good experience. If you already have some knowledge of Python SciKit Learn and Pandas, you could easily cram this course in 2 days (all-in) without too much sweat.

por Sk. T R

3 de Abr de 2019

It has been a fantastic experience to have gone through this course materials. Although I found the lecture videos quite quick to the extent that we fail to understand the concept well. But while going through the labs carefully, I was able to get the concepts right. So only because the lab part was well organized, the course was helpful to me. But had it been the lectures alone, then it would have been difficult to grasp all the concepts clearly.

por Di C

6 de Jul de 2018

Great course! More hands on and practice, a bit lack of theories, compared with Andrew Ng's ML course. And there are a few typos or mismatch in the course materials that need more attention. However, I especially like the fact the example, i.e. predicting car price, has been revisit and further developed through the 5-week course. Just finished round 1, guess I need to go over it again (maybe again) to grasp more details. Recommend the course!

por Jianxu S

7 de Set de 2019

Overall the course is well written. There are a few typos including in the instructions for final assignment. I feel that a summary is missing for the overall data analysis process and methods. This course is the longest in the series so it takes a lot of effort to get through. I did not have much Python background so it was a bit challenging at the beginning but the material was very helpful in bringing me up to speed.

por Francisco M

5 de Abr de 2020

The course is good but sometimes the exercise texts are not very clear and some of the lessons are very straightforward, leaving many doubts. The course should have a larger series of exercises and an automatic correction system that facilitates the review of the exercises. In addition, it would be interesting to have a module on how to use IBMDB2 without the online platform, but through Jupyter on the computer.

por Matthew S

20 de Jun de 2019

This course was challenging. I will probably want to come back to it after learning a bit more statistics. But it was cool stuff, and at the right level of depth. (The only criticism I have is that there are some problems with the final assignment, a small discrepancy between the question in the notebook and the question on the assignment submission, and some other formatting issues on the submission form.)

por Veena W

8 de Nov de 2020

It's a great course for beginners. A lot of topics are squeezed under this course. But, I wish the topics were a bit more elaborated and the number of videos increased. To back up the topics related to any calculations, actual algebra and statistics implementation should have been shown. Because of the confusions, tons of questions were arising during lab activity. Quizzes and lab activities were good.


30 de Mai de 2020

Although this course comprises the most common techniques used for Data wrangling and basic modeling, it does not go any deeper into understanding the logic behind many of the subjects.

Perhaps, giving out some aditional lectures for every week lessons could be of good help to better understand this topics, so the learning process would not be just a "follow through" that just works for ideal scenarios.

por HUNG K

26 de Abr de 2020

The final project left out some higher cross-validation methods like Grid search and model comparison. Nevertheless, the course tried to cover a lot of useful and relevant examples of the whole process, as well as providing good practice opportunities. Personally, I would love to have more practice on each module so that I can turn the knowledge into my own. Overall, a well-designed course!

por Ekaterina K

20 de Ago de 2019

Very good lectures, but the final project takes way longer to set up than to complete: finding the link to the final assignment and making it work in Watson took me too much time. There should be an option to do it outside Watson environment without loosing points because Watson is very slow. Moreover, the assignment and the link to the dataset should be posted more clearly.

por Chrysant C

1 de Jan de 2020

The material are structured very well. The explanation in the video and lab tutorial really help to understand. The discussion forum is active and the teachers are responsive. You will also get a free certificate and IBM badge. Though there are some typos and errors and some things left unexplained, but overall it's good. Hope you guys can increase the course's performance.

por Venkata P U

25 de Jul de 2020

This Course is extremely useful for quick learning of skills. This course takes you into world of data analytics at the same time giving you practical experience, unlike many other courses. All the topics in this course are up to the point and tell you its application rather boring you with details. If you are a beginner then this is a perfect course to begin with.


20 de Jan de 2020

Well design for beginners with a scientific profile. The course starts moderately and covers a large amount of concepts. I advise to take notes and often to deepen certain concepts in dedicated tutorials on google or YouTube and other appropriate platforms. Cleaning mistakes on the slides and the notebooks will be great and make the learning experience more fluent.

por Jess M

27 de Fev de 2019

Covers a lot of content very quickly with not enough opportunities to practice using and applying the code. Having lots of quizzes is good for testing passive knowledge, but more active hands-on application in labs would be most welcome. Useful content, but I am going to go take an intro to Python course so that I can actually follow and use what is presented here.

por Sanjay R

3 de Abr de 2020

The course videos were excellent! The final project did a good job in covering the course material. However, the support to the course was unacceptable. I never got a response to any of my questions after posting them twice and waiting for a day. I then just decided to submit my project without waiting for a response since I felt my wait will be in vain.

por Jeremiah T

16 de Abr de 2020

This is a well organized class and consistent with the rest of the course series so far. One improvement could be to reinforce the concepts more such that we can create our own projects and decide what we need to do. At this point we're just performing methods for the class, but I don't yet feel comfortable starting my own project using these methods.

por Benyaphorn P

9 de Nov de 2020

The overall modules were great. But a few comments, I think I am supposed to get more score for my final assignment. The reviewer did not grade me fairly, even though my answers were correct and matched the rubric. I do not seriously mind the issue. But to be honest, this is kinda annoying and your team should care about how to handle it.

por Jaime A G P

22 de Fev de 2020

Es un curso introductorio, realmente no es complejo, solo se trata de entender las bases del análisis de datos. Sí, es cierto que los videos y los laboratorios tiene algunos errores (que si has pagado por el curso no serían aceptables en ningún momento). Es básicamente una introducción para saber como se trabajan en el análisis de datos.