Voltar para Python and Statistics for Financial Analysis

estrelas

3,268 classificações

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....

SL

13 de abr de 2021

Un curso con una perceptiva muy refrescante en cuanto a los conceptos técnico-estadísticos y sumamente prácticos. e incluso baratos, de implementar dentro del mundo de la inversión. Muy buen trabajo.

EJ

3 de ago de 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.!

Filtrar por:

por Karel H

•12 de jan de 2020

Good

por Nicholas P B

•9 de abr de 2020

First parts were pretty good. Good explanation of pandas and how to work with python for statistical analysis. As the course went on, it deviated towards statistics. At times I didn't understand what the professor was saying as he didn't fully explain what he was doing. Sometimes he would go through topics to quickly without explaining them in depth, which meant I had to re-watch many videos several times to understand (or at least trying to). I would have also liked to have more of an explanation on the python aspect of how to do things as the course went on. As I said initially, it explained things very well at the beginning, then, it was a bit hard to follow,. Therefore a bit more explanation in the programming at the later stages of the course would have been much appreciated. Overall though it was a good course to get an initial feeling of financial analysis, however you need a good level of statistics to understand most things.

por Maria C F

•24 de mai de 2020

I expected to learn to build stock market modeling in Python using statistics but did not really learn anything.The videos are short but you may have to take hours to digest the videos. Also, many of the codes shown in the videos are outdated so when I tried to re-create the model in my JN the codes didn't work. Even the codes already given in the course notebook contain so much errors when I try to run it. Please update the codes so they can run properly.Also all the technical formulas were not explained clearly. The professor just showed the formula and explained a little bit but did not go in too much depth leaving me confused of the use of the formulas.I would not say doing the course is a total waste of time. It has some values but I think it will be much much better if the codes are updated and the formulas are explained better.

por Kenley L

•26 de abr de 2020

Pros:

A neat introduction to python and financial analysis.

Good use to example/Case Study

Great forum of students.

Cons:

Instructor can get very unclear.

The assumed knowledge required in this course is not 100% suited for be beginners, as i've had to do ALOT of individual research on the side. 2 hours worth or work could extend to the whole day.

The expectation is to understand python and methods of financial analysis on a high level, but instructor deep dives into granular detail (which is a pro as well) which arent explained properly.

Continuing from the above comment, the codes in the videos are outdated/misleading. They definitely need to be fixed. A huge chunk i had to spend alot of time to diagnose.

Overall:

I believe the course can be updated and assist alot of individuals learning python and financial analysis

por Kelvin Y

•20 de mai de 2020

Statistical concepts have little explanations on the theories behind them. It almost felt like it was just being listed out at times before showing how it's implemented in Python. If you never took a stats. course in your life, I'd recommend doing your own research on how those concepts came to be on your own before moving on to the next one. I also understand not all Professors' are fluent in English verbally, but sometimes you still had to guess what the Prof. was saying because even the transcripts were wrong. There were also some mistakes in the course material, but fortunately it was pointed out and clarified in the discussion forum. All in all, despite the negatives, I do think it's a good, straightforward introduction to using programming for financial analysis.

por Ruiping G

•12 de nov de 2020

The ppt slides are very nice. The concepts are explained in a very simple way, and the Python codes are helpful.

But for the 4th quiz, the links do not give the right places to go for answering the questions. I would recommend to include snapshot pictures in the questions rather than having links there.

This course can be very helpful for people who are taking Financial Mathematics course, in particular for those who do not know how to use Python yet. Following the course and steps given by this course can really save these students tons of time on their assignments.

por Timothy E T

•3 de nov de 2019

Xuhu made a commendable effort in the early part of the class in teaching the basics of this course. Over the last 2 weeks of content however, significant external reading is required for students to do independently from the course content (not a bad thing) but know that extra effort is required to pass the later stages. For the most part, you should have the basics of python prior to taking this course or you will struggle midway. Nonetheless, it was definitely a commendable effort from this course.

por Surendranath M

•2 de jul de 2021

Either content should be split into more modules or more lectures to be added in existing modules such that details are covered with a slightly more elaboration. Notebooks must include exercises rather than passive demos of techniques. Students may be provided with reading materials/links as followed by Coursera in other courses.

This course gave me an idea of financial analysis tools available and its usage in Python. Thank you for the free course

por Reo W

•31 de mai de 2020

Overall good, the professor is delicated and responds to the forum actively. But the course could be better designed. Even though I have learned the knowledge of statistics, econometric, and python and got a 100% certificate, the course is still difficult for me to digest. I have to pause the video and think 5-8 times per video. The pace is so fast that some usages of the python or applicaions of finance equations lack sufficient illustration.

por Andrew C

•16 de out de 2019

I wish the concepts in this course were gone into more in depth. They aren't necessarily difficult but they can get complex and when the instructor spends an accumulation of 30 or less per module it is hard to fully understand. More practice is needed as well. All the code was done for you except for just a few lines. People who learn by application will not gain much from this course.

por Muhammad U K

•14 de fev de 2021

Though, the course has got potential to be further refined with the inclusion of some of the foundational concepts of finance.

I would rate it 3 out of 5, because of slight difficulty in understanding lectures due to speech delivery, lack of challenge in the form of already filled labs, however, there are some good foundational concepts as well to get yourself started in stock trading.

por Kwok T F E

•25 de jul de 2020

Pros: Learn some python code and review statistical knowledge (SLR, MLR)

Cons: The python code is outdated and may not usable. So time consuming to update the code.

For Example: pd.DataFrame.from_csv(..\...\AAA.csv) which is commonly used in the course

It is not usable as DataFrame.from_csv has been replaced by pd.read_csv(r'...)

Also for loc has significant changes

por Dawid V

•17 de abr de 2020

The statistics element is basic and there is very little practice coding with Python. Instead, it is more of a demonstration how Python can be used to implement some regressions and basic trading strategies. Informative in showing this, however overall a bit disappointing as there was less Python learning and practice as anticipated/advertised.

por Sanson

•18 de jun de 2021

The course is trying to cover multiple area of skills (python, statistics, and financal analysis) in a short period of time. It might be difficult for people who do not know much computer programming experience to follow the Python part. Vice versa, it might be difficult for people to pick up much financial concepts as an amateur.

por Gustavo V

•26 de fev de 2022

It's very hard to follow what the instructor is meaning. I dont agree with some mathematical definitions he states as learned by other methods (estimators as aleatory variables to determine the best estimator). It is the first time that heard of "degrees of freedom". I wish placing more focus on Python than in statitics.

por dan t l p

•4 de jul de 2019

Interesting and easy to understand for people with basic background or have basic knowledge about finance or statistic. However, I wish some of the videos may have explained more about how to use the data to solve real life issues. Even though some of the practices may explore it, it appears not deep enough for me

por dima z

•22 de jan de 2022

I'm not sure for whom this course is dedicated. To undestand what's going on here you have to know statistics' topics and some Python libraries. This course is showing (not explaining, just showing) to you how to use your statictic knowledge in Python libraries whiches you have to be familiar with.

por Alexander D

•3 de dez de 2020

This is overall a good course; it is well explained and very quick. However, it would benefit with assigning more exercises or ensuring that the labs are more interactive. In this topic, practice makes perfect and is very necessary. Also, the quizzes require clicking on links that do not work.

por Miranda G

•10 de set de 2020

Good course but I think that economic concepts should be explained in more depth so that we can work better on Jupyter (which is a great way to teach / learn). I also think that more written material with illustrative examples could be included, not just lines of code that generate results.

por Cesar D

•5 de mai de 2020

Course content is valuable from Statistics applied in Python code. Unfortunately, it didn't give enough examples or use cases for Financial Analysis. I'd like to see more stocks market predictions, studies and models using the Statistics concepts explained on this course.

por Roberto P

•28 de jan de 2022

Mixed opinion for this course: is a good introduction to Python, statistics and econometrics, and you actually learn something. But sometimes it asumes you know things that weren't explained before, the exams contain some errors, and the explanations are not always good.

por Eduardo F R

•2 de set de 2020

It has wide explanation of statistics basics on the other hand the model development with python applied in finance has too few examples. I would also suggest data acquisition with Yahoo Finance or Google to be explained as it is widely used in financial analysis.

por Mingyue W

•14 de jun de 2020

Tough for a person not familiar with statistics and completely new to python. Would have been good to provide more basics to python as well. However, i would believe it'll be very beneficial for one who has already strong foundation in statistics to follow.

por Marcos T

•9 de nov de 2021

No profundiza sobre ningún tema, es más bien un curso introductorio de estadística y finanzas, utilizando phyton para programar, pero al no tener un soporte más robusto de algunos temas de phyton, es difícil volver a replicar lo aprendido

- Analista de dados do Google
- Gestão de projetos no Google
- Design de UX no Google
- Suporte de TI do Google
- Ciência de dados da IBM
- Analista de dados da IBM
- Análise de dados da IBM com Excel e R
- Analista de Cibersegurança da IBM
- Engenharia de dados da IBM
- Desenvolvedor de nuvem full stack – IBM
- Marketing em mídias sociais do Facebook
- Análise de marketing do Facebook
- Representante de desenvolvimento de vendas da Salesforce
- Operações de vendas da Salesforce
- Contabilidade da Intuit
- Preparação para a Certificação em Google Cloud: Cloud Architect
- Preparação para a Certificação em Google Cloud: Cloud Data Engineer
- Inicie sua carreira
- Prepare-se para uma Certificação
- Amplie suas qualificações profissionais

- cursos gratuitos
- Aprenda um idioma
- pythonpython
- Java
- web designweb design
- SQL
- Cursos grátis
- Microsoft Excel
- Gestão de projetos
- Segurança cibernéticaSegurança Cibernética
- Recursos humanos
- Cursos gratuitos de ciência de dados
- falar inglês
- Redação de conteúdo
- Desenvolvimento Web completoDesenvolvimento Web Completo
- Inteligência artificial
- Programação em C
- Habilidades de comunicação
- Blockchain
- Veja todos os cursos

- Competências para equipes de ciência de dados
- Tomada de Decisões Baseada em Dados
- Habilidades de engenharia de software
- Habilidades Pessoais para Equipes de Engenharia
- Habilidades Administrativas
- Habilidades de marketing
- Habilidades para Equipes de Vendas
- Habilidades de Gerente de Produto
- Habilidades Financeiras
- Cursos de ciência de dados populares no Reino Unido
- Beliebte Technologiekurse in Deutschland
- Certificações populares de segurança cibernética
- Certificações populares de TI
- Certificações populares de SQL
- Guia de carreira de gerente de marketing
- Guia de carreira de gerente de projeto
- Habilidades de programação em Python
- Guia de carreira de desenvolvedor Web
- Competências de análise de dados
- Habilidades para designers de UX

- Certificados MasterTrack®
- Certificados profissionais
- Certificados universitários
- Graduações em negócios e MBA
- Graduações em Ciência de Dados
- Graduações em Ciência da Computação
- Graduações em análise de dados
- Graduações em Saúde Pública
- Graduações em ciências sociais
- Graduações em gestão
- Graduações nas melhores universidades europeias
- Mestrados
- Bacharelados
- Graduações com uma trajetória de desempenho
- Cursos em Ciências (BSc)
- O que é uma licenciatura?
- Quanto tempo leva um mestrado?
- Um MBA on-line vale a pena?
- 7 maneiras de pagar pela pós-graduação
- Ver todos os certificados