Retour à Python and Statistics for Financial Analysis

4.4

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1,466 évaluations

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328 avis

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....

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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par 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!

par Jing-Yeu M

•Mar 02, 2020

In general a satisfactory course and not too to follow through. It is focused more on the stat side than finance which I kinda have a mixed feeling toward. Professor could probably have done a little better job on explaining the meanings behind the formula but for the most part it is not hard to figure it out yourself by searching or reviewing the materials a few times by oneself. I also feel this course is a bit short, and if in the future it can try to cover more topics that will be awesome.

But hey I did learn stuff and am happy to have taken this.

par Heung K Y

•May 05, 2020

This course is more suitable for someone who has basic python knowledge. understand that there is a challenge with teaching programming languages via online platforms. It is quite difficult for the instructor to shorten the whole course into 4weeks material. Appreciate that the instructor and TA do spend time to answer student’s questions in the coursera forum. Candidate needs to spend extra time to view other sources to better understand the course material.

par Tristan H

•Mar 31, 2020

A wonderful course to get an introduction into financial statistics and a few python basics. This helped me understand many things about prediction and trading strategies. However to truly understand how to code a financial trading strategy you will need a lot more practice than you get in this course.

I really liked the course and would recommend it to anyone who wants to learn more about financial trading and python!

par Abderrezak

•May 07, 2020

-: some little mystakes, exercice level very low

+: large présentation that provide both python and core financial statistics skill within high level

Might need more time than expected, maybe twice, in order to code the exercice meanwhile watching the video. Cause the final exercice for each week consists just in changing some value. Not enough to know about coding. Except if you already properly know Python

par Dan S

•May 05, 2020

This course is a good starter for you to apply financial analysis by using Statistics models with Python programming. If you have experiments in either programming or statistics, you will find lessons are quite easy to understand. I recommend classmates could take a look at some python plugins such as flask, yfinance. They are wonderful tools for further study.

par Varun S

•May 08, 2020

The course was helpful and definitely interesting. The only problem I found was that a lot of pre-existing knowledge was required and I had luckily studied some of it but the course did not cover it, It would also be helpful to add more indicators to show what each variable stands for in the formula since I found myself forgetting and had to rewind.

par Yashus G

•Jun 10, 2020

The course provides a very good learning experience. The course explains the various statistics that go into evaluation of stock data and further its execution using Python. The explanations could be bettered as there were many instances where pronunciations could not be comprehended. Overall the course provides a good learning experience!

par PUREUM W

•Jun 30, 2019

전공이 금웅공학이나 금융분야는 아니지만 관심이 많아 찾아보던중 이 강의를 들어보았습니다. 결과적으로 말씀드리면 이 강의는 대학교의 명성만큼 어느정도 수준이 높은 강의이며, 기초지식으로 파이썬과 통계학을 요구합니다. 저같은 경우, 전공이 IT여서 파이썬과 통계학을 배웠음에도 불구하고 금융적인 해석능력이 부족하여 많이 고생하였습니다. 만약 이 강의를 듣기를 고민하고 있다면, 자신이 통계학과 파이썬을 어느정도 할 수 있는지 자체 레벨테스트를 할 필요가 있습니다. 강의의 구성과 교수님의 설명은 전체적으로 만족스럽습니다. 이 교수님이 조금 더 낮은 레벨의 강의를 개설하여 입문자를 더 많이 늘렸으면 좋겠네요.

par Shiang-ping H

•Feb 14, 2020

Great Intro. course to Python application in the Financial domain. It will be beneficial to have some Python and Pandas background. Good examples, very practical.

It's a great course - with many practical examples. But this course needs some basic Statistics and Python knowledge to really follow along with some "deep concepts".

par Mario

•Mar 25, 2020

It is a short and well organized course with a gently introduction to the popular Python's data analysis library, Pandas. In addition, the course shows sufficient statistical and financial tools to build simple and practical strategies that put some light on the obscure (at least for some people) market stock analysis.

par George S

•Apr 13, 2020

First course I've completed using Coursera initially found it difficult to get to grips with embedded python, but quickly got to grips with it, really interesting course and a brilliant introduction to python and statistics for financial analysis think the course was really well structured.

par Goh S T

•Apr 04, 2020

Generally a very informative course on how to use python for financial analysis. Some of the concepts are not clearly explained. Would recommend to have a little basic finance background and to have some ideas about statistics as these concepts are only vaguely explained during the course.

par Pokman Y

•Apr 19, 2020

Good and quick course for beginner to use python for financial analysis. The Jupyter Notebook is advanced development environment for python and academic/scientific researcher, but difficult for beginner. Would suggest to have a summary card for all the commands used during the course.

par Diego A C C

•Jun 21, 2020

Es un curso que presenta conceptos interesantes sobre el mercado bursatil, y explica de manera clara la manera en que se pueden analizar los comportamientos de diferentes indices bursatiles. Es importante tener conceptos previos de estadística y algo de logica de programación.

par Juan d D

•May 25, 2020

The content of the course is really good.

The amount and density of the information for the last week is high. Specially compared with first week. Would be great if it could be balanced information per week.

Time to time the (English) pronunciation wasn't good enough.

par Deep S

•Jun 02, 2020

The course has offer me a insight in Python in Statistics and how I can implement in the field of Finance.

Overall difficulty was moderate to high, Week 4 was way to difficulty, I would suggest that a person with Knowledge on Statistics should apply to this course

par Bryan M

•Jun 10, 2020

It has been a really interesting course, but I expected to learn a way to get the signals using a price action analysis, or even identify some support/resistance areas. However, it has given me some ideas to continue with my learning.

Completely recommended!

par Julian W

•Jan 09, 2020

Nice intro to using python in financial statistics. I dont have financial background so a lot of things were too complex for me. In general this course will not teach you statistics or python but will rather show potential in learning both of them together.

par Zacharias L

•Mar 10, 2020

I have learned quite a lot from this course. Econometrics and statistics are an important part of Financial Analysis of course. I would prefer if the course drew more deeper into the mechanics of Python, however.

par Matthew B

•Aug 03, 2019

Good course with introduction to some statistical concepts and surface level python. Does not go into great depth with python and the jupyter notebooks could be a bit more challenging but overall a solid course.

par Saksit S

•Jun 29, 2020

This is very fun course but i'm not recommend for beginner at least you need to have knowledge of statistics and basic machine learning(test,train) these will help you more understanding while study this course

par Quentin D

•Oct 02, 2019

Good class to learn the basics of statistics for financial analysis, the Jupyter Notebook is great and the exemples are very practical. It makes it a good starting point if you never used python before.

par Eric C

•Nov 10, 2019

The course was very good and gave useful skills for statistical analysis with python. I do wish there was a more detailed introduction to the course for people who may not have a technical background.

par Edoardo C

•Apr 19, 2020

Very basic and easy to follow if you have enough programming and mathematics background.

It provides a useful insight on some of the foundations of the techniques and ideas used in Financial analysis.

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