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Voltar para Python and Statistics for Financial Analysis

Python and Statistics for Financial Analysis, Universidade de Ciência e Tecnologia de Hong Kong

4.8
13 classificações
1 avaliações

Informações sobre o curso

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....

Melhores avaliações

por YH

Jan 08, 2019

I great and easy-to-understand course to learn python for basic statistics!

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3 avaliações

por Donovan A

Jan 21, 2019

Perfect for the beginning to intermediate python programmer who wants to utilize finance data to make decisions (i.e. trading).

por Zeyu HUANG

Jan 20, 2019

【Now you know Prof. Xuhu Wan, please avoid his course in HKUST】

0. Course Equivalence😐

This course basically covers 50% content of MATH2411 Applied Statistics (I heard there is ISOM2500 that is similar to MATH2411?). Accidentally I took 2411 right before this winter when this course is out, so I found this course quite disappointing because I expect some practical manipulation of Python is covered while it doesn't. More is discussed in #3.

1. Teaching ☹

If you have the experience of recording a video presentation eight hours before the deadline, with scripts written three days before and you hadn't recited or even gone through it in these three days, you will find the professor the same unpassionate. You will find his tone flat enough and gestures unnatural enough as if he is not emphasizing on anything but focusing to recite his scripts. You will find him lag a lot at strange and unnatural spots as if his brain goes blank and he quickly reads the copy of scripts next to the camera.

I thought business people cares a lot about presentation, but I was wrong.

2. Subtitle 😡

There are tons of me steaks in the subtitles, not only tipos but also worlds of cellar pronunciation.

(There are tons of mistakes in the subtitle, not only typos but also words of similar pronunciation.)

I enable subtitle because I sometimes can‘t understand the professor's perfect Mainland accent, but it turns out the subtitle is on his side but not my side.

I thought business people are very strict about the material that comes along with their presentation, that they always carefully spellcheck every sentence. But I was wrong.

3. Content 😐

3.1 Overall:

Please rename this course "Python and applied statistics". The professor spends sooooo much time talking about the statistics concepts and spends soooo little time applying the knowledge to financial analysis. It is not about "Statistics for Financial Analysis". Replace the data he uses for demonstration with GPA of every student and it becomes "Statistics for Being HKUST President" or "Statistics for Anything". I feel I am taking an introduction course to statistics and financial analysis is just an excuse the teacher use to show us the content he teaches is somewhat useful.

3.2 Pace:

You MAY find the pace quite fast because:

The teacher throws many statistics concepts

The teacher cannot fully explain the concepts (or it is not a 4 week course) so he moves on before you ever (perhaps never will) digest the previous concepts

This is extremely annoying in week 4, e.g. Multiple Linear Regression is taught without introducing a single formula, merely Python codes and black boxes behind them. (Actually this is the way I originally expect the professor to do, but it is quite inconsistent with the style in week 1-3)

You MAY find the pace quite slow because:

After all this course introduces formulas and codes and let you to use them without knowing why.

So I would say this is a 4-day course if you can spare 1 hour each day. After all you are not asked "why" but only "how". If you haven't taken MATH2411 or ISOM, you can spend more time on week 2 & 3 to understand the underlying knowledge. Week 1 is simple and week 4 is needless to comprehend.

4. Jupyter Notebook (JN for short) 😡

4.1 Poor Exercise

Almost useless. Just a copy of the codes appeared in the video, with some variables assigned None instead of the correct expression. Your job is to change the lines of variable assignment (usually one or two lines), and the rest is done for you. Some notebooks are even 100% done for you, and all you need to do is look at it and appreciate. Even if you are fiddling with provided exercises, you don't know how to use JN, because...

4.2 Irresponsible adoption of JN

If you want to do some real exercise, you may want to append empty cells below the given content and type codes from scratch. But oh, this course does not teach you how to use JN! It just throw you a tutorial link of how to INSTALL JN ON YOUR COMPUTER{https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook}. What a shame!

Quickly gone through the linked tutorial, it assumes you have installed multiple instance of Python on your desktop, and know basics of pip, conda, docker, and virtual env, and teaches you how to install and configure JN in various dev. environments. But you just mentioned we can use Coursera's pre-installed JN out-of-the-box, why you want us to learn that huh? And to create cells, run cells, run several cells in order, run all, and other basic operations, is hidden in the last seconds of GIFs, not explicitly explained.

I guess the professor is TOO UNRESPONSIBLE to not only teach students how to use JN himself, but also SPEND AT LEAST SOME TIME to check if the external tutorial really "explains how to use Jupyter Notebooks". Please, not every one taking this course is CS student like me, SBM students they may not know how to use Python stuff.

5. Coursera Technical 😐

Quizzes do not provide correct answer. So it is not that helpful. But getting 80% is not that hard either. But given the assumption that you can't use JN (explained in #4.), you lose at least 10% in Quiz 3 and 20% in Quiz 4. Oh that hurts! (Since Notebook 4.4 is done for you, another 20% in Quiz 4 related to JN is okay.)

por Yau Tsz Ho

Jan 08, 2019

I great and easy-to-understand course to learn python for basic statistics!