Python & Machine Learning for Financial Analysis (Udemy.com)

Disappointing with the chapter "Predict Future Stock Prices Using Machine/Deep Learning". Predicts the stock price with a lag of one day and the variable volume as an explanatory variable is not included in the model as far as I can see. The goodness and usefulness of the model is not discussed in depth, for example to make predictions. The statement that the model explains well is not substantiated in any way. I would not buy stocks based on the model.

Very good presentation and explanations of Python programming, Stock market dynamics of predictions and using various tools and concepts using vanila methods and neural networks. Highly recommend for beginners.

The course is an absolute reccomendation for those who want to learn how to use python for financial analyses as well as to make a first dive into machine learning. (also recommended for python beginners) The course is very well structured and gives a very comprehensive and sophisticated overview about the most used packages in python. Even if I am not working in finance, the approaches learned can easily be transferred to other fields of action (like for example LSTM just to name one). The only thing that I missed in the course is in the section of stock prediction. We learn very detailed how to build up the model and how to validate it, but I missed how to do actual predictions of the unknown future. However, overall an amazing course with an incredible learning courve!!

Lost for words! Have taken about 8 or more courses taught by Dr. Ryan. He is a dynamite in his own rights; brings passion, exceptional delivery style , enthusiasm and stimulating challenges to his students. He encourages learning by combining all the right teaching arsenals. Even personally, my questions are responded to which bridges any gaps and cements my learning process. Lost for more words...

The learning experience was amazing with a lot of practical application on capital asset pricing model, predicting stock prices, machine learning, asset allocation and statistical data Analysis but I found the section the Auto Encoder session a bit difficult.

Concepts and ideas laying behind every executed technique are clearly translated into common people language, but I don't actually feel that I've gained enough understanding of ML and AI as to give the course a practical application in a real life project. For example, all the 'Sentiment Analysis' lectures are based on training a model with a pre set of twits imported into a .csv file, already classified as positive or negative. Hence, the course does not give any guidelines on how to actually track what people are commenting on Twitter, Reddit or whatever social network about a given stock of interest, or even on how to link a model to yahoo finance to get real stock updated data. Also, there is no interpretation of the results obtained by the model for the 'testing' data, other than the level of accuracy achieved. As a final comment, by the end of the course I felt I was going to crash if I heard the 'I highly recommend that you guys try to solve the mini-challenge alone', AND I'M STILL WAITING FOR THE MONTE-CARLO SIMULATION LECTURES!

Lots of detail. Amazing course for just the Python section alone! Add the financial analysis components and its more amazing! Add Machine Learning and AI parts and its almost unbelievable! One could easily pay thousands of dollars and not get half of the value in this course. Instructor is clearly someone who has taught before and obviously enjoys it.

So..decent course, I am someone with enough of a technical background to grasp this application of Python to Data Science. This course provides a lot of good practice for those new to some Data Science tools/methods/concepts. I would however say that at the time I took it the course is not finished yet...it was missing the module on Monte Carlo simulation. The course content also drifts towards the end and is clearly from other courses by the instructor. What it lacks is more concrete domain examples of the concepts demonstrated...like based on this ML/AI method I will have Python trade for me on a stock or stocks etc. as a trading strategy. Again overall very informative but a little rough in spots and lacking some things I would like to have seen.

Some lectures missing. It is mentioned in the Q&A repeatedly but nothing done.
Apart from that I liked it. Quite understandable.

Some topics are repeated again again this makes the course longer than it needs to be. Also the content related to intuition should be improved.

Maybe a little bit more detail on how to adjust the models to apply to real-world data is helpful.

The end of the course was not explained well. One lecture is missing and the colab files do not work well as the pictures did not often download correctly. I asked for help but the instructor did not get back to me.