Python for Finance: Financial Investment and Data Analytics
Original price was: $129.99.$24.99Current price is: $24.99.
What you’ll learn
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Learn how to code in Python
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Take your career to the next level
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Work with Python’s conditional statements, functions, sequences, and loops
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Work with scientific packages, like NumPy
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Understand how to use the data analysis toolkit, Pandas
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Plot graphs with Matplotlib
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Use Python to solve real-world tasks
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Get a job as a data scientist with Python
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Acquire solid financial acumen
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Carry out in-depth investment analysis
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Build investment portfolios
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Calculate risk and return of individual securities
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Calculate risk and return of investment portfolios
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Apply best practices when working with financial data
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Use univariate and multivariate regression analysis
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Understand the Capital Asset Pricing Model
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Compare securities in terms of their Sharpe ratio
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Perform Monte Carlo simulations
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Learn how to price options by applying the Black Scholes formula
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Be comfortable applying for a developer job in a financial institution
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Do you want to learn how to use Python in a working environment?
Are you a young professional interested in a career in Data Science?
Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?
If so, then this is the right course for you!
We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.
An exciting journey from Beginner to Pro.
If you are a complete beginner and you know nothing about coding, don’t worry! We start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks.
Finance Fundamentals.
And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, we will focus on Finance, covering many tools and techniques used by finance professionals daily:
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Rate of return of stocks
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Risk of stocks
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Rate of return of stock portfolios
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Risk of stock portfolios
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Correlation between stocks
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Covariance
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Diversifiable and non-diversifiable risk
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Regression analysis
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Alpha and Beta coefficients
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Measuring a regression’s explanatory power with R^2
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Markowitz Efficient frontier calculation
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Capital asset pricing model
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Sharpe ratio
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Multivariate regression analysis
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Monte Carlo simulations
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Using Monte Carlo in a Corporate Finance context
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Derivatives and type of derivatives
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Applying the Black Scholes formula
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Using Monte Carlo for options pricing
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Using Monte Carlo for stock pricing
Everything is included! All these topics are first explained in theory and then applied in practice using Python.
Is there a better way to reinforce what you have learned in the first part of the course?
This course is great, even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context.
Teaching is our passion.
Everything we teach is explained in the best way possible. Plain and clear English, relevant examples and time-efficient videos. Don’t forget to check some of our sample videos to see how easy they are to understand.
If you have questions, contact us! We enjoy communicating with our students and take pride in responding within the 1 business day. Our goal is to create high-end materials that are fun, exciting, career-enhancing, and rewarding.
What makes this course different from the rest of the Programming and Finance courses out there?
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This course will teach you how to code in Python and apply these skills in the world of Finance. It is both a Programming and a Finance course.
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High-quality production – HD video and animations (this isn’t a collection of boring lectures!)
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Knowledgeable instructors. Martin is a quant geek fascinated by the world of Data Science, and Ned is a finance practitioner with several years of experience who loves explaining Finance topics in real life and here on Udemy.
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Complete training – we will cover all the major topics you need to understand to start coding in Python and solving the financial topics introduced in this course (and they are many!)
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Extensive Case Studies that will help you reinforce everything you’ve learned.
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Course Challenge: Solve our exercises and make this course an interactive experience.
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Excellent support: If you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day.
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Dynamic: We don’t want to waste your time! The instructors set a very good pace throughout the whole course.
Please don’t forget that the course comes with Udemy’s 30-day unconditional, money-back-in-full guarantee. And why not give such a guarantee, when we are convinced the course will provide a ton of value for you?
Just subscribe to this course! If you don’t acquire these skills now, you will miss an opportunity to separate yourself from the others. Don’t risk your future success! Let’s start learning together now!
Who this course is for:
- Aspiring data scientists
- Programming beginners
- People interested in finance and investments
- Programmers who want to specialize in finance
- Everyone who wants to learn how to code and apply their skills in practice
- Finance graduates and professionals who need to better apply their knowledge in Python
12 reviews for Python for Finance: Financial Investment and Data Analytics
Add a review
Original price was: $129.99.$24.99Current price is: $24.99.
Essa M –
This course is a great way to get into finance and programming. It’s direct and clear (most of the time). There are instances where you might have to watch a video several times to understand the topic especially if programming in python is new to you.
Tran Kim Hong –
should have more explanation about monte carlo simulation section, there are confusing finance formulas make it more complicated when applying in Python.
Aleksandar Nedeljković –
This course was amazingly thought out and executed. Both instructors put great effort to explain the concepts in detail; hence, I had no problem to follow the course even though I’m a beginner in programming. Furthermore, both instructors do their best to keep the student motivated and give lectures in a fun way. Another great thing is that lectures are always accompanied by homework, so the student gets to test him/herself on the concepts covered and to do practical exercise. Finally, the knowledge gained through the course is extremely useful and it could make a huge difference on a job interview for a finance-related position. Basically, these guys teach students to apply in the real world the concepts taught only theoretically on universities. Thank you for taking the time to create this exceptional course. Purchasing it was truly one of the best investment I made in my entire life.
Taiki Hashizume –
All of the theorical lessons from the finance part are good explanations, very straight foward and clear. Part one where only python is explained have decent lessons. But I felt like the applications to finance lessons where a bit too shallow.
Alexander Sel –
great course to get started in Python. I highly appreciate the great videos for coding. Big thank you to Martin for showing each programming step and the great exercises.
Overall, great intro to financial data analysis, though course touches on several financial concepts which have to be separately further researched to get better understand.
Also, I felt that financial topics were not fully finished, like getting tangent to efficient frontier, etc. I guess this is for next step.
Thank you I really enjoyed this course for a total beginner in programming!!!
Shuang Wang –
The lecturers are great but sometimes a little bit tedious since your voice is sometimes too slow. It could be more organized if you show us prior to the lecture, what is the purpose, for example calculating the call option price and what do I need to go through, which formulas and which variables I need to fill in. Furthermore, when I asked question of why I cannot import spicy packages, no one helps.
Bruno Saldivar –
Im a musician, so I don’t define as a bright math science brain… but this course showed me that anyone can learn it!; thanks so much for make this understandable for people who is willing to learn python and finances even when Im an outsider from the science/math fields, thanks! VRuno
Mohammad Hasan Abdelqader –
I decided to leave my review tell the end. I is a very informative, hands-on, and life changing course. very will structured and organized. I highly recommend it for any researcher or programmer.
Yafoor Waizi –
Like their other courses, 365 Career’s doesn’t cease to amaze me with their great quality materials. 1st section (python) was a good refresher, and 2nd section (Finance) was very instructive.
Chun Wei Liu –
I love this financial python course, which gives me lots of insights and useful information about python financial basic concepts. And the course is suitable for beginners.
Mariana Pote –
Good basic introduction. A bit outdated, but still has some good application. Not useful if you’ve already been introduced to Python. Appendix also doesn’t add any useful information.
Christoph Sawade –
It gives a great introduction to the fundamental concepts of finance and how to implement them in python. However, there are a couple of smaller flaws and discrepancies between the implementation and the theory presented.