Modules and Bootcamps | Courses | Case Studies
Modules and Bootcamps
A bootcamp designed to introduce students to Python and data science with a focus on its applications in finance. Completion of this bootcamp allows the student to complete the case studies in here.
This bootcamp will run at the beginner of a semester so students are able to complete the case studies during that semester. Topics include basic programming in Python, loops, lists, if statements and popular Python packages for data science. There will also be a section on basic data science techniques.
MGFD40 - Investor Psychology and Behaviour Finance (Python Workshop)
This course contains a mandatory Python workshop as the main programming language used is Python. Topics include: collecting data from the web using APIs and common financial database, manipulating data sets, visualizing data, form weighted portfolios, perform statistical analysis, and evaluate trading strategies. There will be four marked Python assignments given to test one's Python knowledge and problem solving skills.
MFRM, MFIN, and BCom Blockchain Module
Discusses blockchain architecture, how a transaction is done on a blockchain, comparisons of different blockchain implementations by current cryptocurrencies. Also goes over the problems with blockchain and the proof of work algorithm. Additional topics includes tokens and crypto-economics.
RSM316 - Machine Learning
MGT415H5F - FinTech
The course has two main objectives. First, it will introduce students to the emerging field of FinTech. We focus on two main technological innovations, blockchain technology and machine learning (which relates to artificial intelligence), that facilitate this transformation and that these FinTechs use. We will study the process of founding and financing of a FinTech startup. The second objective is to give students the opportunity to develop a viable FinTech product idea, based on a thorough analysis of the business models of two to three successful FinTech firms
RSM2318 - FinTech
The course explores the business models, financial strategies, risk management and technologies used by successful FinTech startups and established Financial Services Corporations. There are 5 modules: comprehensive overview of FinTech innovations, compressive overview of Consumer and commercial payments and lending FinTech, Insurance FinTech, Wealth Management and Capital Markets FinTech and Regulation FinTech; protecting financial innovation intellectual property and FinTech regulations; key FinTech technologies, including blockchain, machine learning, API, cyber security; and, the actual development of an idea into a Minimal Viable FinTech Product with industry expert mentorship.
RSM2511 - Innovation in the Marketing of Financial Services
Based on presentations by fintech founders and senior decision makers at banks, case discussions and lectures, this course explores the number one issue for CEOs of every major financial institution: the onslaught from a wave of well-funded, disruptive startups looking to carve off their most profitable lines of business. The course addresses this from the perspective of disruptors, established financial institutions and venture capital firms, looking at issues of customer segmentation, positioning, product development (including minimum viable products), pricing, distribution, scaling of offerings and competitive insulation.
RSM2328 - Machine Learning and Financial Innovation
The course focuses on how machine learning has impacted innovation in finance. Topics include unsupervised learning, supervised learning, and reinforcement learning. The course will go over models that implement the learning methods, these include k-means, ridge, lasso, elastic net, random forest, SVM, and etc.
RSM4324 - Financial Innovations
The course goes over current innovations finance. Topics include blockchains, FinTech, and artificial intelligence. Discusses the impact and potential uses of blockchains and artificial intelligence in finance. FinTech discussions include robo-advising, ICOs, payment systems and etc.
RSM6313 - Innovations in Financial Technology
Automating Credit Card Approvals
This case study requires the student to develop a model that is able to mimic credit card approvals like how a human would, classifying it as approved or rejected.. The goal is to achieve a performance level very similar to humans based on accuracy, precision, and recall.
Iowa Housing Prices
This case study aims at predicting the sale price of Iowa houses based on factors about the house, which is a regression problem. These factors include number of stories, size of the house in square feet, neighbourhood, and others.
This case studies aims to classify countries based on how "risky" they are. This classification is done by looking at factors of 122 countries. These factors include corruption, peace, legal, and GDP growth rate.