Dearest primates, we're super excited to announce two new courses that can help you learn something productive while you're stuck inside.
Python Fundamentals
Machine Learning for Finance
* Intro to Python as Foundational Skill
* 70+ detailed video lessons
* 22 video exercises
This course is really geared to teaching someone with a finance background the fundamentals of Python. Priced at $97 (dirt cheap for the quality)
Applied Machine Learning Algos
* Prerequisite: Python Fundamentals
* Over 150 video courses
* Over 30 detailed lessons
This course builds on the Python Fundamentals course and takes the student through building a machine learning investor classifier with Python. Priced at $197 (again, a steal with how thorough this course is)
If you want to invest in both, you can get $47 off and get both for $247.
For Package Deal, Click Here - $47 Off.
These come with the same 12-month, no questions asked 100% $ back guarantee we have on all our courses: https://www.wallstreetoasis.com/courses.
Happy studying!
Patrick
ps - sneak preview and more detail below...
Python Fundamentals
Machine Learning for Finance
The fundamental course starts by teaching you the basics of Python Programming, which we will use to transition to more advanced topics.
Key concepts the course is going to cover are:
* How to set-up Anaconda and Jupyter Notebooks for Python
* Python Native Data Types (Strings, Booleans, Integers, Lists, Tuples, and Sets)
* Input/output formatting
* How to build custom functions
* For loops and conditional logic
* Using the Numpy and Pandas Package
This Python Fundamentals course will demonstrate the foundations of Python programming and how it is used in the finance industry. Upon completing this course, you will be able to:
Write and execute basic Python code to perform advanced calculations, generate outputs, create variables, abstract from data, etc.
* Create and manipulate important data structures such as lists, tuples, sets, and dictionaries
* Use for loops and conditional logic to create your own custom functions
* Import external packages including NumPy and Pandas
* Generate random integers and samples
* Filter, segment, and summarize data
Applied Machine Learning Algos
This course will utilize the knowledge you learned from the Python Fundamentals course to build machine learning investor classifiers. We are going to explore real case studies from investment banking and capital markets applications that are being used today to advise Fortune 500 companies all over the world.
This course will demonstrate how machine learning algorithms are used in the finance industry. By the end of the course you will be able to:
* Identify overfit regression models
* Compare different regularized regression algorithms and decision tree ensemble algorithms
* Explain the confusion matrix and its relation to the ROC curve
* Construct training data sets, testing data sets, and model pipelines
* Perform advanced data cleaning, exploration, and visualization
* Engineer features based on conditional relationships between existing features
* Build and finalize a machine learning classifier
If you want to invest in both, you can get $47 off and get both for $247.
For Package Deal, Click Here - $47 Off.
Again, these come with the same 12-month, no questions asked 100% $ back guarantee we have on all our courses: https://www.wallstreetoasis.com/courses.
Nice!
WallStreetOasis.com Patrick this is awesome and a great addition to the site's product offering. One question / piece of feedback - could you add some more screenshots / maybe a short teaser video to the info page? Would like to see a bit more of a preview of the content & teaching style before committing to purchase. Thinking of going through this now that CFA has been postponed and want to be productive with my time. Thanks!
Your badge says you're in PE why do you want to go for CFA or learn Python??
Learned python in college & wrote a bunch of stuff on Quantopian but haven't used it since, so I could use a refresher. CFA in part because I am not going to b school; I'm not in a very "traditional" PE role - the CFA has use, value, & applicability to what I do / the space I'm in. Broadly speaking, even if I was in traditional LBO PE, why let yourself stagnate & not add python/CFA to your resume, especially as a junior? Both are essentially call options on your career prospects, where the premium you pay is mostly in time. And tbh, the time committment for the CFA is much lower for those with both finance/accounting undergrad and/or professional experience than the majority of the stories you read online. The oft quoted 300 hours of prep can amount to less than 2 hours a day on weekdays only if you start preparing far enough in advance, and if you're in the aforementioned camps, can and should be a fraction of 300 hours.
I mean I guess if that's what you want. I still don't see how you would use Python in your day to day unless you plan to automate the most trivial of work which doesn't seem to need the ML algos since you could just automate the task with out having to bring in any stats. As you move up the chain of command in PE though I don't see how having a technical skill like programming will help you in bringing in deals and closing them.
Imagine being this naive and myopic of your career & skills building. What a hilariously bottom bucket mentality to have. Your response is also sadly presumptuous and frankly off-base and misguided. Again, I am not in traditional PE and there are plenty of things I can (and do) automate and/or do more efficiently via Python and VBA now at my job. My job & firm, even at the more senior levels, is not just about closing deals. What if I simply enjoy programming & writing trading algorithms on Quantopian as a hobby? Furthermore, nothing is guanteed. What if I were to get laid off because of an economic slowdown? What if I simply decide to leave finance altogether someday? In either circumstance I'd be better positioned by having a more diverse and in-demand skillset to provide myself with at least temporary employment or adhoc consulting-like projects. Your tag says you are a first year analyst in IB where technology is over a decade behind the rest of the industry; maybe if you make it to the buyside you'll better see the applicability of programming to finance. There is a very apparent and clear direction in which the finance and, even more broadly, entire professional services industry is heading with respect to programming. In the 21st century it is as essential as learning basic arithmetic. Individuals who went to college between let's say '05 - '18 were likely caught in the middle of the transition and didn't feel the need to learn programming and are likely most at-risk of becoming technically deficient & replaceable in the next decade. Newer college cohorts are taking basic programming classes in greater and greater numbers each year; the abundance of Udemy / Khan Academy classes (as well as this new WSO offering) also speak to the growing demand & expectation for basic programming skills in the market.
Please see the original post. I just embedded a preview of the LMS and what you'll see on the backend. This is the same custom LMS we use for all WSO Courses. Happy studying!
Perfect, thanks!
Might i suggest providing a compare / contrast to other similar courses on sites like Udemy and FreeCodeCamp.org and other popular elearning sites?
One thing that made amazon grow was the power of honest user reviews and comparisons among products.
Came here to post this, excellent resource and entirely free.
Thanks ironchef - the course is much more geared toward finace professionals and not just python for the sake of python (ie practitioners, not programmers)...that's why in the fundamentals course we take a lot of concepts from Excel that a lot of our members are familiar with and apply them to Python.
we are slammed so didn't have the time to put together a pretty sales page (you'll see it's very similar to our other landing pages) explaining the course since we wanted to get this out while people had the time to study. We'll get to that (eventually)!
Exactly how much does the Machine Learning Algo class cover? In other words, what will one be able to do after completing the course?
Thanks for sharing this! How useful/relevant do you think these course materials would be for someone in "vanilla" corp fin roles, like FP&A? For us, the more useful features of python are being able to automate time-consuming operational tasks and some advanced filtering, etc. versus advanced statistical regression or whatever else quants do.
Do you think there's enough material in the course to satisfy these wants as well?
Commenting for future use
Thanks for sharing these!
Forgive me if this is a stupid question, but what exactly is an investor classifier?
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