Coming from programming background and being less theoretical, I have mixed review about this course. This course is taught by two instructors. The theory, taught by prof Lionel, is not really clear for me. The math has gone too far and too deep and overall they made things more complicated than they should. I often had to resolve to external sources to understand what the topic being discussed. The lab sessions, taught by Vijay, on the other hand is very enjoyable to follow. It's clear and clarifies the topic being taught. Vijay is not just some financial engineer that can code Python. He's very good at it. Even I with 5+ Python coding years have learnt many new tricks from his videos. Coming to the week four however, things went downhill fast. The theory is too abstract, while the videos are just too long! I think we have two or more videos with around 1 hour duration, and this is just too much.

This is an excellent course on employing Python to make asset allocation decisions. The concepts are well-explained and the pace is quite brisk. A student can really benefit by following and redoing the Python code themselves.

For that, I would highly recommend going through the excellent Numpy, Pandas tutorials on the Enthought youtube channel, before the first week. Secondly, the course expects an understanding of Asset Allocation concepts, and it will be prudent to read up on 'Modern Portfolio Theory: Efficient and Optimal Portfolios' before the second week.

I admit that I cannot write the sophisticated code for last modules (Dr. Vijay Vaidyanathan made it look as effortless as reading a newspaper), but the course has given me the confidence that I can do that after coming up to speed on Python.

That is also my suggestion for improving the course that maybe some of the more sophisticated techniques be pushed out to later modules while building up python and asset allocation knowledge in the first module.

After finishing the course, it's quite satisfying to examine the mutual fund results, and understand how they were generated or how target date funds work or what's the logic behind the 60/40 asset allocation portfolio.

Enjoyable course. One has to be conversant with basic Phyton to follow this course. What I learnt the most is the ability to use Phyton coding to demonstrate the concept of portfolio investment.

This is one of the best online courses which combines the knowledge of Finance and Python. In fact, with python as a tool, I can have a better understanding of the theory behind it.

Currently half-way through the course. I am really enjoying it. I am learning a lot about portfolio management and python, which is the best of both worlds for me.

The professors are excellent. Dr Vaidyanathan's lectures and labs ensure that the student learns the material and his love of the subject is infectious.

Really enjoyed the course. The lectures were interesting and well produced. The labs were fun. It was enjoyable to program along with the instructor. The main negative that took away from the course was week 4 being much harder than the first 3 weeks. I t felt like the difficulty level increased a great deal and it was hard to keep up. I also think this course is above beginner level. You need to have decent programming skills, you need some finance background, and it helps to have an understanding in stats and linear algebra as well.

Although the course was very good, helpful and very informative but the codes were not updated which caused a lot of confusion and dissatisfaction. The codes which were not updated caused a lot of errors which were a bit frustrating at times. Also there was a bit delay in the response from the staff in clarifying the doubts and queries.

Overall it was a very good and knowledgeable experience wIth professional faculties.

Thanks and regards,

ROHIT RAWAT

Thank you instructors for the fantastic teaching with profound financial principles and advanced Python techniques to make our learnings and programs applicable to present market analysis. Although it is very challenging to make all programs work well when Python version upgrade/changes, it is worthwhile to learn new things, improve Python coding skills and strengthen finance investment skills. Honored and blessed to learn a lot from this course and also from the forums of friendly classmates. Would recommend surely! Best Regards and Blessings.

One of the most hardcore, challenging but knowledge-harvesting courses that I ever had.

Highly recommend, and you will be better off if you type in all codes VJ did simultaneously.

This was a great course, really good materials, great exercises, no unreasonable tasks. Great introduction into Python in finance. One thing I would say that this course is not for beginners. Prior Python knowledge will be highly beneficial. The reason why I am giving 4 is due to the lack of support in forums.

Really enjoyed this course and found it extremely useful, from a couple of perspectives. First, the alternative perspective of managing your portfolio to meet future goals / liabilities as opposed to just return seeking was helpful, and secondly providing the construct of dynamic allocation between a performance seeking portfolio and the liability/goal hedging portfolio to be very useful. I particularly enjoyed the lab sessions that where very helpful in developed a basic understanding of the algorithms to build the code to implement the concepts in practice in my own portfolio. And as a secondary benefit, as someone who enjoys coding, I really benefited from seeing the approach to coding an application and learned a few neat tricks / capabilities along the way. I came away with a new appreciation for python and indeed Jupyter Notebooks / Lab, as I must admit I had fallen into the R camp. Look forward to taking the remaining courses.

One of the best online courses I've taken. It is the first I've actually completed in a while. I would mention a special word of appreciation for Dr. Vijay, his Python Lab sessions are probably the best way to learn to program for a beginner. In just a 4 week module, the amount of content covered is immense considering the course starts with the assumption that the viewer has zero knowledge in the language.

This course is the gold standard by which I will benchmark other courses. The learning I've gained from this course is beyond my wildest expectations. I'm only curious to know there's so much more this field has to offer!

This course is one of the best course I ever took on Coursera (I have completed about 20) !!! If not the best ! The lectures are clear and the lab sessions are very helpful to understand concepts and use them by digging into the implementation. And Python notions are given along the way, which makes you feel that you are following a finance class and at the same time learning new Python features smoothly ! The last week of the course was slightly less clear and thus little bit harder, but I totally recommend this course !

Very Useful course to have a hands-on understanding of how to apply Finance concepts in investments through Python. Lectures are provided in a very succinct manner and the lab sessions are fluidly constructed. Plenty of useful python codes will get compiled in edhec_risk_kit for future use.

Awesome Course, Great instructors that give a nice balance of theory and practice, the practice is very hands-on and will help you understand the theory and give you useful tools from the first week.

I am self taught in Python and have an industry background in Finance. This course was a good connector/provided additional insight on using Python to process portfolio performance and data analysis.

Exceptional quality of instruction. The production and detail of supporting materials made this class very accessible. I learned much more than expected. Bravo on the effort of the instructors!

The course is particularly useful for people with a finance background to learn how to model a complex process using python. Lecturers are very knowledgeable and step-by-step guide in teaching.

The course was very informative and added a lot of learning and the instructors made navigating the whole syllabus very simple, even for a novice programmer and finance student

Very useful course. Both teachers are good to transmit their knowledge at a decent pace. the balance between theoretical courses and labv sessions is perfect.

Loved it, one of the best courses I have ever taken. Only wished I had more time to spend on it, limits of what you will learn are mostly upon yourself.

Great course will continue with the rest of the courses

Excellent course with great pedagogy that will introduce you to individual or institutional investment management (understanding Markowitz efficient frontier and main target in portfolio construction, basic strategies for portfolio construction combining risky high-return and low-risk-return portfolios to meet liabilities, simple random walk modelling for examining virtual scenarios, and also using some real-world data), using theoretical courses as well as coding videos (notebooks are provided to play around) and quizzes using these notebooks.

Python using Pandas & some tricks.

I had almost no basic knowledge in investment and some experience with pandas, with some solid mathematical background though not an expert, and the level was perfect for me.

Watched in 1.5 ;)

very good introductory course to learn how python is used to implement portfolio strategies. coding is taught in a simple enough way to pick up and try to real-world data as well....

This is an excellent course for the finance professional who has a deep and genuine interest in both Python (for Machine Learning) and Portfolio Analysis. Don't take it if you can't check off both because it is rigorous in both regards.

The instructor does especially well in describing the Python code that he is using: in great line-by-line detail for much of the Python notebooks. He falls a little short on providing full Portfolio Finance Theory, ...which is why I provided 4 stars, not 5.