C++ Programming for Financial Engineering

It is an excellent course. It build a great understanding of C++ from ground up, as well as some knowledge of Boost and STL libraries.

I found Avi Palley, Daniel Duffy and Pavlos Sakoglou very helpful through out the whole course.

I think that this online C++ course is very helpful to those like me who have some or little experience on C++ or equivalent programming languages. The material has covered a wide range of topics and difficulties from data type and object-oriented programming to financial applications such as Monte Carlo simulation and FDM method. My TA Avi is very knowledgable and responsible. I appreciate all the suggestions he has given to me.

**Fantastic Course!**

Accepted into CMU's MSCF and needed to take this course or some conventional C++ Intro course.

I could not be more happy with my choice.
Talking about this class with computer science graduates, it's clear the content here is perfectly catered to the material you actually need to learn in quantitative finance/numerical methods.

Getting quickly to Generic Programming and Boost Libraries is incredibly useful and surprisingly rare in other intro C++ courses.
As far as time commitment goes, anyone can succeed in this class if they block off time in their schedule and work hard. I have a full-time job in industry research, but working 5:30-7:30 am and every other weekend provided ample time.
Big Thanks to @Daniel Duffy @APalley @Justine Morgan @Andy Nguyen and the students on the Forum.

And Best wishes to those of you taking this course in the future.

A good course introducing important elements of c++ programming. Exercises are simulating and motivate self learning by reinforcing concepts presented in video lectures and notes. Course builds on basic concepts of writing simple functions, and then layers in advance ideas of OOP, template programming and boost library. I have enjoyed going through this course and recommend it to aspiring students of financial engineering.

The course has been great in overall, and the exams / quiz / HW are made in a way that encourages you to self-study in a very organized way. I highly suggest this course for all those who aim to be a financial engineer but lack general programming knowledge.

I thought the TA support was remarkable. I've never received such fast response time in a class.

I was kind of disappointed in the quality of the pdf notes. I found a lot of typos, and wouldn't expect this from a course I am paying almost 1.5k for.

I found the lectures to be absolutely terrifyingly boring. I have to admit, I only watched them when I absolutely was unclear about something.

The forum was very helpful in the HW. I liked that the sections were split up. But, I would have liked the option to have a search box to search through the posts of a level. Sometimes, I would search through threads for a longer time than I wanted to find the answer to a question I had.

The quizzes were good. I would have liked more code snippets, like we got on the final. I think these are the most useful besides practicing, when learning. To have questions like what is the difference between parametric polymorphism and some other type of polymorphism, maybe is useful but honestly, I forgot the answer right after taking the quiz.

Firstly, I would like to applaud the way the course is structured. It is very systematically designed so that in each level, all the important concepts of the current as well as preceding levels needed to be utilised in order to complete the rigorous assignments. Especially, Level 9 was very challenging. It requires a combination of mathematics, programming and finance. Coincidentally, I read Dr. Duffy’s post somewhere during the same time which said “The first 90 percent of the code accounts for the first 90 percent of the development time. The remaining 10 percent of the code accounts for the other 90 percent of the development time.” Personally, I found the forum discussions and TA’s prompt responses extremely useful. Thanks to Dr. Duffy, Avi, Baruch College and QuantNet.