Python for Finance with Intro to Data Science

I did not have any background in coding, c++ or python. I have heard a lot about it but did not know where to start as they have a vast amount of courses out there and it really hard to know which are useful / fundamentals to learn. It was great to go through the courses here, as in many examples in this course showed how c++ and Python can be used in terms of financial application. I don't regret taking these two courses and will definitely come back to refresh my knowledge about the topics learned.

Though I already knew how to code in Python before, this course taught me to code Pythonic!

My friends suggested this course to me. I looked over it and decided to take it because I wanted to learn Python with Data Science. That is exact course I wanted.

It's simple, the class was the best programming class i have taken in a long time. The structure it follows is very similar to the C++ one, so having that background certainly helps the student understand the concepts better, but definitely not necessary. The development of the topics goes really quick, so one needs to be super engaged throughout the course, and be committed to the end for sure, it's quite challenging but yet rewarding at the same time. I 100% would recommend this to anybody who is interested in learning how to code as a quant.

I finished the C++ course in the summer of 2023. I think this kind of course is interesting, so I’m really excited to take the Python course.

Coming from a C++ background but still seeing tons of Python at work, I really needed a structured approach to sharpen up my Python. Sir Avi's course was exactly what I was looking for. Not only was I able to learn some of the more advanced and tricky topics that are more Python specific, but he also gave me lots of advice and help in making my Python code more idiomatic or 'Pythonic'. I always feel like my Python is essentially C++ with Python syntax.

It's been a challenging but great learning process. Course is well designed and h/w help to better understand the theoretical concepts. Even though the TA was always ready to help and answer a lot of even trivial questions you need to be ready to research on your own (sometimes a lot), read some tutorials in order to grasp a full understanding of particular idea. All in all, I would recommend this course especially if you're about to do quant masters.

I took this course after taking the QuantNet C++ course and really enjoyed learning Python. The course is well structured with Part 1 culminating in a case study project that pulls everything learned about Python together. I found Part 2 very practical in that it teaches how to use NumPy, Pandas, Plotly and other libraries. For me, the videos and code examples were extremely helpful in learning Python.

I really wanted to develop a programming skill, so my friend recommend this course to me.
I found this course quite useful, including comprehensive Python programming knowledge. The course provides both fundamental and advanced knowledege, thus making it terrific for beginners to follow up. I was a neophyte in coding before I took this lesson, but now I am able to code as convoluted as ABS model. And I give credits to both the course material and the help of the TA. The homework for the lesson is not something we can palter with. It is really extensive and demanding, and I had to spend countless hours working on it! I had to finish the homework based on the lessons I learnt. I put them into experience. And that is the reason why I got a comprehensive of the knowledge. The homework only told me about the structure of what I should do, so I had to come up with the syntax by myself, leaving me room to think and providing me with the opportunity to hone the programming skills. Sometimes, when I got confused, the forum and TA really helped me a lot. I got timely help from my TA, and the fellow students who learnt this lesson before. I managed to solve the question with their guidance. I really learnt a lot through this course, and it is really a good experience."

I've learnt the basic syntax and more advanced applications in Python and some useful libraries like numpy and pandas. Through this couse, I found myself more confident in coding with Python, and I'm now equipped with the skills to manipulate data and do machine learning through Python coding.

After the C++ course, I had a good experience, so I took the Python course without any hesitation. Great experience with C++ and Python courses! Thanks

I wasn’t good at coding in Python. Now I think my coding skills have improved a lot. This course was really helpful. Appreciate the learning experience!

I chose to take the course because I wanted to learn more about how programming applies to finance. Also, Python is becoming much more popular in the finance industry every day; therefore, learning the syntax and logic of Python is crucial.

I found out about this course through the Quantnet website. Just like the C++ course, Quantnet’s Python course is very solid and went beyond my expectation. From one with little programming experience, I credit these two courses with providing me with a good foundation and interest of the field. Regarding this Python course, I would like to thank Andy and Avi for designing the course very well and for the comprehensive curriculum. I am also grateful to Avi for being a great lecturer and TA who grades homeworks and responds to questions in a timely and helpful manner. Overall, I am thankful to have had the opportunity to take Quantnet’s courses and would recommend them to anyone up for the challenge.

I found the level of the course to be on the medium - high side. I would have found it quite intense if I hadn't known Python previously or I wasn't used to code on a daily basis.
Beside that It has met my expectations since I got to know the tools and skills to improve and do my own research now.
Overall, very satisfied to have done it, although I have to say I've struggle on certain exercises.

I think the course has its uniqueness in that it challenges you more than other courses.
So you would spend a lot of time thinking about how to solve exercises and this is how you improve as coder. The course definitely met my expectation for being rigorous and covering lots of topics. I would say that the only downside is that students with no previous experience will suffer, as well as those who work full-time to complete the course on time.

I started this course after having completed the C++ for financial engineering course. I found to be very helpful as an introduction to the syntax and Python specific features and the capstone project is an extensive case study which was extremely helpful.

My goal is to learn Python and get a hint of the idea of financial engineering; the class definitely did the job. The lecture videos are well-structured and the exercises are good sources for practicing the concepts. I'd say that the course is quite difficult to start with if you've never programmed before, but once you are familiar with OOP in Level 2, you'll enjoy this class (The Forums are extremely helpful). The project was definitely hard, but I had fun building it step by step.
I'm glad I take the class, and I want to thank the TA @APalley, who continuously provides useful tips when I was struggling.

My goal for taking this course was to future-proof my career as things get more automated. They say that the pandemic pushed us 6-7 years into the future in terms of tech adoption.

I didn't want to be out of that party for long.

The students were promised to be ready for the first day on the job after this course. I believe it delivers well on this promise.

First, even in other coding languages (e.g. VBA in my work) I find myself more comfortable dealing with excel objects and methods having been introduced to their nuances in level 2 of the course. Second, aside from the programming aspect, it also delved into the fundamentals of processing data and data tables in numpy/pandas, which is almost always a demanded skill in job postings related to python.

With its pace, its coverage, and great TA support (where else can you get a one-day, personalized feedback?), nothing can beat this course in teaching you all the fundamentals you have to know in such short span. Plus of course the time-pressure and the tuition provide good motivation to get you that certificate.

This time-pressure aspect is very real. I see some comments with people saying they'll take this in just a month or two. The second week will really bring you back to reality. The reality that this course will require your effort, and that you better be prepared to give this time everyday and all of your weekend especially for OOP, the text processing project, and the final project.

Learning Python from the ground up was tough, and the pace of this course was no joke. I spoke with my friends who have taken c/c++/python and they give me a blank stare (or an emoticon rather) when I discuss about dictionary comprehensions on my first day on this course. My senior from work was impressed that we were discussing OOP on level 2 when, in his experience, that was usually touched on in advanced courses. And then we even covered advanced stuff such as generators, lambda, and let's not forget that indispensable introduction to concurrency that really changed my way into thinking about things. That maybe in other languages, things can be sped up by leveraging more of your computer's hardware. This topic was especially surprising to me and to my friend who actually worked on an advanced version of this topic for his thesis (as if it was not advanced enough).

The final project is something special. You will value an ABS using tools you may have never heard of if you're not coming from a very technical background. The amazing thing about this course is that you will be trained with all of the tools you need to do so without all the complexity. And you'll also be using other functions/classes you've used in prior levels. Each project builds on the previous and if you work at it hard enough, you'll find your way to this level confident with your skills that you can implement many of the things you'll encounter in your work. The good thing is, I don't think many of things you'll encounter in the work place (if you won't be working in the quant area) will be as tough as ABS valuation so you may have seen the biggest monster you'll ever encounter, and to have slayed this monster by completing this final project is the best confidence-booster you can get before you apply for a python-related job.

Let's not forget the data science portion of the course. True to the course, we once again get bombarded with theory in the first level of this part (level 8), but the experience you get with these tools sets you up for the following levels in data viz and bootstrapping. I think in terms of employability, the skills you learn here will be indispensable as companies nowadays are hiring people who can manipulate/visualize data, be it in SQL/R/Python, and this course effectively teaches you how to do this in Python as there is no shortage in exercises for this part. What is also good about this part is that it is largely free-hand and you're free to make your submissions as complicated as you need it to be to be able juice out all of the practice you can.

All in all, this course really was time well-spent for me before I went back to preparing for CFA Level 3. Beyond programming concepts, it taught me to see the world in a more exact way, and this for me is the most important takeaway of the course. It has taught me to see things as an object - method group, and to diagnose problems by assessing whether an object is supposed to have that method or function. I was happy that I learned to think more programmatically using a more accessible language such as Python, and I'll be sure to take these lessons to my day-to-day responsibilities.

Thank you Andy for putting this together, and thanks to Avi for the constructive and prompt feedback.

5/5

I think the course is quite good in comparison to other Python courses I have learned. Even though I have been programming with Python for a fair amount of time, the course provides a lot of things to learn (rigorous lecture on OOP, introduction to multiprocessing, wrapper). The data science part is concise, but I was surprised that it covered a lot of things.