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Kursteilnehmer-Bewertung und -Feedback für Python and Statistics for Financial Analysis von The Hong Kong University of Science and Technology

1,460 Bewertungen
325 Bewertungen

Über den Kurs

Course Overview: 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....



Mar 24, 2020

A very good introduction course to python programming and it has a perfect combination with statistics, which makes financial analysis more interesting and refresh my mind on it, thanks.


Apr 23, 2020

Generally, the course offer many approach with financial data but not very easy to understand for beginner such as myself. I hope there will be more course like this in the future !!!

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151 - 175 von 324 Bewertungen für Python and Statistics for Financial Analysis

von Brian P

Jun 03, 2020

Power of knowledge


May 20, 2020


von Feiting X

Feb 27, 2019

Nice Introduction!

von Santiago L C

Jan 30, 2019

I enjoy very much

von Jonathan M

Jun 28, 2020

very informative

von Artem C

Feb 23, 2020

Great course !


May 26, 2020

Thank you sir

von Bhavya S

Jan 27, 2020

whatta wow :D

von 裴品傑

Jun 05, 2019


von Tsoi K M E

Jun 15, 2020

Great course

von Heiner A M V

Apr 29, 2020

Very usseful

von Henrique G

Sep 24, 2019

It's great!

von Ruikun D

Jan 29, 2019



von Md K I

Jul 04, 2020


von Joydeep p

May 08, 2020

Very good


May 24, 2020


von Kleber L d S

Jun 20, 2020


von John W

Oct 09, 2019


von Zhu, T

Jun 07, 2020


von Xiaobing C

Dec 22, 2019


von Claudio H

Apr 21, 2020

A fine introduction to the use of statistical models for finance (stock trading), showing its implementation in Python. It is NOT a course in either Python or Statistics but shows what one should learn. Alas, it does not give any pointers as to where to go to delve deeper into the needed statistics (nor trading, for that matter). It contains a fair summary explanation of linear regression models, but the recipes for their evaluation are discussed way too briefly.As for Python, it uses 4 common important libraries and directs the student to the corresponding sites. It gives no explanations as to the kind of structures being manipulated. The Jupyter notebooks are well set-up for practice.

von Kushagra S

May 22, 2020

The course provides an overview of how to build a quantitative trading model. However, the instructor does not go into details while either introducing python functions to someone unfamiliar with the language or talking about statistical concepts. I could follow the code based on my background in other programming languages.I will be following up this course with other courses that go in depth on both the programming and statistics front.The Jupyter notebooks are quite helpful and I will be using them for future reference.3.5 would probably be a more honest rating of the course but I don't think the course could have taught the learner more given its length.

von Matthias H

May 14, 2020

Good for what it intends to provide, namely a quick introduction to the topic, but it doesn't go very deep.

It is slightly annoying that there are plenty of typos and grammatical mistakes all over the Python code and the quizzes, which could easily have been avoided if either the author had somebody proofread everything quickly, or if Coursera had any type of quality control.

Nevertheless, coming from another programming language, I did get out of this course what I wanted, namely a collection of all the basic Python commands for this kind of analysis. So thank you for providing this course!