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Comentários e feedback de alunos de Exploratory Data Analysis for Machine Learning da instituição IBM Skills Network

4.6
estrelas
801 classificações
189 avaliações

Sobre o curso

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing. By the end of this course you should be able to: Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud  Describe and use common feature selection and feature engineering techniques Handle categorical and ordinal features, as well as missing values Use a variety of techniques for detecting and dealing with outliers Articulate why feature scaling is important and use a variety of scaling techniques   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience  with Machine Learning and Artificial Intelligence in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics....

Melhores avaliações

AE

26 de set de 2021

Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.

ML

21 de set de 2021

Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.

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151 — 175 de 195 Avaliações para o Exploratory Data Analysis for Machine Learning

por EMANUELE F

26 de set de 2021

The course touches all the topics that are of interest for the a Machine Learning pratictioneer. I've found the course sometimes oversimplified, that paradoxically made it harder to grasp some concepts, expecially the topics of the Week 2. Overall I've found It to be a good course because at least it gives you the path to follow from where you can study on your own to go deeper in the topics you are interested.

Note: I would suggest to edit the notebooks. It is not a good idea to have the solutions in the same notebook where you should do an exericise, because it makes also the video lectures that came after pretty useless. I suggest to separate the exercises from the solutions, and to put the solutions in the video lectures so you must follow them with some focus to understand what the solution was. Furhtermore i would review the notebooks. Some of them were different from the ones presented in the video lectures which made it a little bit confusing to follow.

por Sunil G

1 de jul de 2022

The speaker appeared to be a third party - reading off a script, and not the actual course instructor. This aspect made the subject drier that it actually is.

As for the course and the notebooks, it has been done very well.

I would still rate this as a 101 in terms of real depth of experience, but perhaps that is as is expected.

The assignments do not do a regirous test of skills aquired.

por Alexander S

25 de abr de 2021

The quality of this course is very good. It helped me to get a basic understanding of exploratory data analysis. Whereas the first weeks topic was more or less early for me, the seconds weeks topic about statistics was more challenging and I also had to do some own research to deepen the contents discussed in the lectures.

por Anna R

15 de nov de 2021

I really liked this course, has been extremely useful for me as a starting point for next IBM courses. One suggestion to improve - some concepts are covered a bit superficially, in my view, e.g. Hypothesis Testing. Maybe going a bit more into theory would help.

por jake t

5 de jan de 2021

The information was good though basic. I thought the info on hypothesis testing and probability was probably not necessary for an ML course where this should be assumed. The teacher was clearly reading off a script which was at times not so engaging.

por Hizkia F

2 de jun de 2022

The course is great but in my opinion the teaching material will be even better and more exciting if it has less text and more graphical visualization of the topic being explained. I feel like the instructor read the slides for me.

por Arnav G

24 de mai de 2021

It is fairly difficult for a beginner - although the level is intermediate for this course and there are a few prerequisites, somehow I still feel that a lot is pending to be explained, esp. in the DEMO/LAB exercises

por Ghanem A

30 de set de 2021

Excellent content and examples. Would be great if another example for hypothesis testing is added to demonstrate this concept with a typical ML dataset (maybe use one of the previous datasets used during the course)

por Erick O A

28 de jun de 2021

Great instructions, wonderful demos and insightful comments on the results. The only part that I did not find well explained is the part on hypothesis testing. Some details could be added on t-test and z-test.

por Ignacio A S B

21 de jan de 2022

It lacks a deeper view of the topics and applications on programming for a real world Exploratory Data Analysis (EDA), but gives the basic tools and understanding to introduce you to EDA.

por Alexandros A

14 de dez de 2021

The first week of this course was very informative and with a lot of examples. Although, the second week was difficult to understand, the concepts nad the examples were not clear.

por Sawan G

25 de jul de 2022

Great course. Just some concepts should be explained slowly and carefully but they are just skimmed through... overall a good course for EDA.

por Aditya M

18 de dez de 2020

Good introduction. The time estimates to complete assignments are off.

Need a lot more material and direction for assignments to aid learning.

por Dany D C

2 de mai de 2021

I know some basic statistics knowledge is required, but sometimes the analysis story is unconnected, and sometimes make the story confusing.

por JORGE M B

10 de dez de 2021

The course is good. What it lacks to get the 5 stars is to be able to download the slides of the classes or to have a documentation.

por Arunav C

1 de out de 2020

It is a really insightful and interactive learning experience. Furthermore, the trainers and coaches were very knowledgable.

por Gautam D

31 de jul de 2022

I​t was good course which help me to understand data cleaning , Feature engineering , EDA , and basic of statistics .

por Mahmudul F A A

6 de nov de 2020

In week 2, the lessons were a bit in rush and it would be better to have a bit more detailed discussion.

por Medha J

14 de mar de 2022

Very Nice course , will teach you in detail all the techniques of EDA with practical code.

por Aravind S

11 de abr de 2022

Was able to learn and practice many topics in this course. Very useful for Data Analysis.

por Sebastian N

16 de mai de 2022

Good instructor, good knowledge level, minor mistakes in some of the notebooks provided.

por Joseph F

2 de mai de 2022

Good introduction. Quiz questions mostly on terminology and not understanding.

por Roberta D

13 de abr de 2022

Very interesting course, good for getting ideas to deepen the topic!

por Daren L P

27 de jun de 2022

I​ enjoyed the course, the example code/labs were awesome

por Olivier F

7 de out de 2021

G​ood introduction and Exploratory Data Analysis course.