Python for Finance with Intro to Data Science

MFE Pre-requisite. Great course for enhancing understanding of advanced python.

Just like the C++ course, I consider this one of the most useful courses I have ever taken. The entire course introduced many very practical Python and data analysis skills, and also served as an introduction to machine learning, making it much easier for me to further pursue related topics.
Additionally, the ABS model project from this course was very appealing, both to me and to interviewers. I included this project experience separately in my resume, and when I applied for finance and engineering internships, I found that the interviewers were very interested in this project, which undoubtedly increased my chances of success in the applications.
Finally, I would like to express my gratitude to all the instructors, especially my TA, for the support they provided throughout the course.

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.