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Avis et commentaires pour d'étudiants pour Python and Statistics for Financial Analysis par Université des sciences et technologies de Hong Kong

4.4
étoiles
2,807 évaluations
621 avis

À propos du cours

Course Overview: https://youtu.be/JgFV5qzAYno Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data. By the end of the course, you can achieve the following using python: - Import, pre-process, save and visualize financial data into pandas Dataframe - Manipulate the existing financial data by generating new variables using multiple columns - Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts - Build a trading model using multiple linear regression model - Evaluate the performance of the trading model using different investment indicators Jupyter Notebook environment is configured in the course platform for practicing python coding without installing any client applications....

Meilleurs avis

GZ
25 mars 2020

Very clear explaining of the significant aspects when structuring a financial analysis, applicable in many forms of data if you don't want to make predictions only for the stock market.

PL
7 avr. 2021

An excellent beginner's guide to financial statistics using Python's Pandas module. Can be completed very quickly by those familiar with both basic Python and introductory Statistics.

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601 - 625 sur 630 Avis pour Python and Statistics for Financial Analysis

par Nico M

25 nov. 2019

Too many mistakes in the use of English throughout the course made it hard for me to follow the course properly without getting annoyed. The instructor's English was terrible as well, just too many mistakes, which made it impossible to follow without subtitles. The content was good though which is why it deserves two points.

par Victor M

6 nov. 2019

I was hoping for a little more from this course. While it effectively combines statistics, finance and python, it does not go into great detail in any of the three. There are spelling mistakes and the audio quality is not great. For me the most useful part was learning the python functions and syntax.

par Jonathan Z

29 sept. 2021

Course is good but (a) some Python bits are not up-to-date and (b) final week exam questions should be updated and brought in sync with either lectures or the lectures need to be updated. If Google has a different answer than the course, well, that's not a great place to be in.

par Lale N

28 mai 2020

i am happy with subject and course syllabus but if the data that the lecturer worked on them, was available the course would be much more useful,

without the data, it was just some code that we were watching.

thank you coursera :)

par Nicolas P

1 sept. 2019

I would change the title. It has little practical content on trade, and explains more statistical methods.I would call it "how to use and graph statistics in python, with some trade samples".

par Mohini J

21 mars 2020

The course tried to cover a lot but wasn't really helpful for those who didn't have basic knowledge of either Python or Statistics

par Panguluri B T

10 juil. 2020

Poor Explanation of topics, was in a very hurry to complete than in explaining the concepts in depth. Did not reach expectations.

par Jacob G

23 juin 2021

More coding please. I was looking for more linear modeling examples and implementation. The rest was relatively easy.

par HIMANSHU V

13 août 2019

Lectures are not very informative. Things are said directly and not explained well. Sadly I paid $50 for this.

par Danny w

6 mai 2020

The teacher need to learn better pronunciation and slower pacing

par wegdan

24 févr. 2021

video lecturing lacks clarity and big picture context

par Eliad H

12 mars 2019

very basic,

not improving python skills

par Lubie W

9 août 2020

This course teaches statistics more than Python coding. The codes are not well explained or even not explained by the instructor. The instructor spent more time on statistics concepts than going through the Python coding. I learned very little about Python in this course.

par Liem J L

15 nov. 2019

Should be better explained. Could not get past the first few lines in the practical. Looked at the discussion board and people were saying it was because the course is outdated and the code he explained might not even work with the version we were using

par Anas A H H

16 juin 2021

1- t​he language spoken is not clear (I had t oread the subtitles more than listening which was a horrible experience)

2​- the labs are bot built in the right way, lots of errors and lots of data changes that effected the application of the commands

par Jack M

26 avr. 2020

Horribly worded questions. Difficult to understand the lecturer. Week 1 was good to practice python. Week 2 was awful.

par Sean S

26 nov. 2019

The code examples and quizzes have not been properly reviewed and there were multiple mistakes in them.

par Marshall T

26 mai 2020

codes are not updated to python 3. Also little opportunity to apply codes in IDLE/Anacdona yourself.

par Christeen P

12 mars 2021

Disorganized, and the quizzes are not testing abilities nor knowledge but just quantitative skills.

par Avnish A

26 mars 2020

very vague and non detailed explanations from week 2. almost impossible to catch up.

week 1 was good

par Pedro J G R

14 oct. 2021

Very complex explanations (even if you learnt statistic before) and then zero practice. A fake!

par Kwame N D

5 janv. 2021

Very poor delivery by the instructor. Course title inappropriate for the content.

par Ohad s

2 oct. 2020

the instructor is not understandable and don't really explain the material

par Chavassieux

17 sept. 2021

A​ lot of formulas but it miss some example too generalist sometimes

par Boyan D

5 nov. 2020

I regret starting this course. You should unlist it from coursera.