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

4.7
estrelas
16,189 classificações

Sobre o curso

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Melhores avaliações

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.

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.

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1751 — 1775 de 2,445 Avaliações para o Análise de dados com Python

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.

por ANDRÉS A A C

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 Teh C Y

10 de ago de 2021

Week 1 until Week 4 the syllabus are okay & understandable, but when it reached week 5 it's another level, like suddenly jump from beginner level to advance level without detailed explanation. I have to ask people or search online to look for answer & further details to understand the whole concept. This reminds me of the movie series GOT... exciting beginning but terrible ending

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 Celine

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.

por Mouafo D

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.

por Eugene B

2 de set de 2019

Some of the course skates over pretty difficult information really quick and then gives you challenges that haven't really been that well explained, so some self-research is required. The assignments are also pretty copy/paste + modify a couple of variable names so you have to put in the effort to really get good value out of the course.

por Anuradha B O

14 de jul de 2018

The course is very interesting and concise, it has a very logical flow. The best parts about the course are quiz embedded in the lectures and detailed lab assignments. However, there are few errors in the lab and assignments, which need to be rectified. Otherwise, it would have been 5star from me. Thank You for desiging this course.

por Ming

18 de dez de 2019

Easy to understand and grasp for a beginner. Good refresher for those who have some basics of programming down. Typos in the reference codes here and there but no major problems. Other than that the Watson interface is alright to work with however there will be some lagging some times. I enjoyed the process of learning this course.

por Ning C

12 de mai de 2020

Clear structure and message delivering. I have learnt a lot from this course within a short time. Teaching assistants answer questions in each weeke's forum also with good clarity and patience. Although some mistakes, cannnot obscure the splendor of the jade. :) Looking forward to a better version after the improvement on typos.

por Mats B F

1 de mai de 2020

You can consider some more explanations on how the training and testing codes are linked together and what explicitly the Python codes does. This was the elements I struggled to understand. But this was the only part that also was new to me. All in all, the material was well explained and the course was very interesting.

por José F M V

7 de out de 2020

I just have an issue with some minor bugs with the Coursera web app. I don't know if they are specific of this course or as a whole. For example, when clicking in next assignment sometimes it jumps two assignments. Or when you type too fast the system just writes the last letter. Other than that is pretty ok.

por Jeff L

17 de jun de 2020

great lectures and projects. on data analysis topic, IBM has chopped contents into many small courses, which make student confused and hard to find which one to take. IBM should consolidate them into 4 or 5 courses that are focused, heavy weighted, so that students can build rock solid knowledge and skills.

por Roy v E

23 de abr de 2020

The courses are very good to get familiar with Data Science and what it essentially is. I would have like practise examples with answers after each chapter to practise it in but that is just how I learn. Overall I learned a lot about new resources and how to do certain things in the Data Science world.

por Ranjeeta R

25 de mar de 2020

I liked the course. Highly recommended for someone who is looking for coding experience for data Analysis using python. Please practice the lab that will make you confident. Only thing which bothered me is the final assignment review. It was not correctly reviewed. I lost 4 marks. Hope this helps!

por Joseph O

11 de mar de 2019

a few discrepancies here and there, please see the comments in the discussions. Other than that, very good! This course was more difficult than the others, and so i guess this is why employers prefer potential employees hold a PhD, or at least maintain a high algebraic/calculus/statistical aptitude