Retour à Python and Statistics for Financial Analysis

4.4

étoiles

2,108 évaluations

•

467 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....

EJ

3 août 2019

Great course! Very didatic explanations about financial and statistical concepts also with some interesting practical Python for Finance! Looking forward for new courses from same Univ. and prof.!

LH

23 mars 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.

Filtrer par :

par Claudio H

•21 avr. 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.

par Kushagra S

•21 mai 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.

par Brandon B

•8 sept. 2020

This course shares a lot of info on how to use statistical analysis formulas like RMS, p-value, std. deviation, etc., and how to apply this knowledge using data modeling in a really easy way. There are some small hurdles to get over when taking the quizzes as some of the answers can be interpreted in multiple ways. out of the 4 quizzes I took, i attempted at least all of them 2 to 3 times. Not sure if I failed to absorb the knowledge well or if the goal was to go back and review the course material with a finer comb, either way, I found the course helpful and useful. I'd recommend it to friends and colleagues.

par Matthias H

•14 mai 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

•2 mars 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 Masaki S

•22 oct. 2020

This is an awesome course which takes you through the statistics for the financial analysis. The course needs some update to correct some broken links, inconsistencies. It requires some basic knowledge of statistics and python programming beforehand or study of these topics alongside this course, which should be made obvious to some learners who may be puzzled (I see in the forum that several learners were quite upset about some difference in expectation vs the reality which I think could be narrowed down).

par camillo s

•6 sept. 2020

The course was indeed helpful for my main goal to improve my skills using Python libraries to carry out mathematical / statistical caclulations.

One minor issue:

As I downloaded the notebooks for replaying them in my local Jupyter installation which is based on Python >= 3.6, I had to manually correct some statements due to changes in pandas, e.g.

pd.DataFrame.from_csv -> pd.read:csv or

pandas.tools.plotting -> pandas.plotting

mho it would be good to check for such issues

par Heung K Y

•5 mai 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

•31 mars 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

•7 mai 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

•5 mai 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

•8 mai 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

•10 juin 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

•30 juin 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 Daniel H

•13 févr. 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

•25 mars 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 MESSAN A

•11 nov. 2020

In general, the course is very interesting, very clear with a lot of explanation. However, I dislike some part of the quiz: when we need to follow the link to answer the question, it is not possible because the link doesn't show the notebook but our course's process. It will be greater if you ameliorate this part.

par George S

•13 avr. 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

•4 avr. 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

•19 avr. 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 John

•5 août 2020

Good pace, instructor at times is hard to understand, had to look at the transcript to understand some parts. Course only scratches the basic parts of python and statistics -- good beginner course, but may require small knowledge of python and basic statistics before beginning.

par Diego A C C

•20 juin 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

•24 mai 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

•2 juin 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 Sergio J

•21 août 2020

I agree the content is extremely useful, especially, for people who are starting to learn about finance, and statistics. The only complain was that my expectations were rather a focus in python than in the finance concepts themselves. Overall, a great course

- Recherche d'un but et d'un sens à la vie
- Comprendre la recherche médicale
- Le japonais pour les débutants
- Introduction au Cloud Computing
- Les bases de la pleine conscience
- Les fondamentaux de la finance
- Apprentissage automatique
- Apprentissage automatique à l'aide de SAS Viya
- La science du bien-être
- Recherche des contacts COVID-19
- L'IA pour tous
- Marchés financiers
- Introduction à la psychologie
- Initiation à AWS
- Marketing international
- C++
- Analyses prédictives & Exploration de données
- Apprendre à apprendre de l'UCSD
- La programmation pour tous de Michigan
- La programmation en R de JHU
- Formation Google CBRS CPI

- Traitement automatique du langage naturel (NLP)
- IA pour la médecine
- Doué avec les mots : écrire & éditer
- Modélisation des maladies infectieuses
- La prononciation de l'anglais américain
- Automatisation de test de logiciels
- Deep Learning
- Le Python pour tous
- Science des données
- Bases de la gestion d'entreprise
- Compétences Excel pour l'entreprise
- Sciences des données avec Python
- La finance pour tous
- Compétences en communication pour les ingénieurs
- Formation à la vente
- Gestion de marques de carrières
- Business Analytics de Wharton
- La psychologie positive de Penn
- Apprentissage automatique de Washington
- CalArts conception graphique

- Certificats Professionnels
- Certificats MasterTrack
- Google IT Support
- Science des données IBM
- Ingénierie des données Google Cloud
- IA appliqué à IBM
- Architecture Google Cloud
- Analyste de cybersécurité d'IBM
- Automatisation informatique Google avec Python
- Utilisation des mainframes IBM z/OS
- Gestion de projet appliquée de l'UCI
- Certificat stratégie de mise en forme
- Certificat Génie et gestion de la construction
- Certificat Big Data
- Certificat d'apprentissage automatique pour l'analytique
- Certificat en gestion d'innovation et entrepreneuriat
- Certificat en développement et durabilité
- Certificat en travail social
- Certificat d'IA et d'apprentissage automatique
- Certificat d'analyse et de visualisation de données spatiales

- Diplômes en informatique
- Diplômes commerciaux
- Diplômes de santé publique
- Diplômes en science des données
- Licences
- Licence d'informatique
- MS en Génie électrique
- Licence terminée
- MS en gestion
- MS en informatique
- MPH
- Master de comptabilité
- MCIT
- MBA en ligne
- Master Science des données appliquée
- Global MBA
- Masters en innovation & entrepreneuriat
- MCS science de données
- Master en informatique
- Master en santé publique