Summer Course Add/Drop Deadline: Some summer courses do not follow SGS add/drop deadlines since they are scheduled at unique dates. Please note the add/drop deadline in the course schedule below. If you would to add a course that is still within the course add deadline, please fill this form out with your signature. If you are having trouble dropping a course and it falls within the drop deadline, please use the same form. Please pass the form to firstname.lastname@example.org for processing.
|FINANCE AND MANAGEMENT|
|Course Description *Click course title for syllabus link||Admin Info||Next Session Details||Fall 2023||Winter 2024||Summer 2023|
|APS500H1: Negotiations in an Engineering Context||FALL 2023: Starts Sept 7, Monday 2-3pm, MY360, Thursday, 2-4pm, MY360||x|
|APS502H1: Financial Engineering||FALL 2023: Starts Sept 7, Wednesdays 12-3pm, in BA1180|
WINTER 2024: Starts Jan 8, Wednesdays, 12-3pm, in BA1130
|APS1001H: Project Management||Course will be delivered Asynchronously||FALL 2023: Sept 11 - Dec 15|
WINTER 2024: Jan 8 - April 5
SUMMER 2023: ONLINE
1st Subsection (F): May 1 - June 23
Course add deadline: May 8
Course drop deadline: May 26
2nd Subsection (S):
July3 - August 25
Course add deadline: July 10
Course drop deadline: July 28
|APS1004H: Human Resources Management: An Engineering Perspective||WINTER 2024: Jan 8 - April 1, Mondays, 6-9pm, BA1210|
SUMMER 2023: August 14 - Aug 25, Monday-Friday, Daily, 6-9pm in BA1220
Course add deadline: Aug 15
Course drop deadline: Aug 18
|APS1005H: Operations Research for Engineering Management||Exclusion: MIE262||SUMMER 2023: ONLINE, June 6-June16. Daily Tutorial 4pm to 5pm (in-person) in GB120. June 15th tutorial is 4-6pm, Room GB120|
Final Exam Tuesday June 20, 9-12 (in-person in ECF lab)
Note: tutorial is in-person only
Course add deadline: June 7
Course drop deadline: June 12
|APS1009: Natural Resources Management||FALL 2023: Sept 14 - Dec 7, Thursdays, 3-6pm, WW119||x|
|APS1016H: Financial Management for Engineers||FALL 2023: Sept 13 - Dec 6, Wednesdays 12-3pm, BA1200|
SUMMER 2023: May 3 - July 26, Wednesdays 3-6pm in BA1180
Course add deadline: May 8
Course drop deadline: June 26
|APS1017H: Supply Chain Management and Logistics||SUMMER 2023: May 1 - May 12*, Monday-Friday, Daily 9-12pm in BA1190|
*May 11, 12 in GB220, 9-12pm
Course add deadline: May 2
Course drop deadline: May 5
|APS1020H: International Business for Engineers||FALL 2023: Sept 12 - Dec 5, Tuesdays, 3-6pm, MY370|
SUMMER 2023: May 23 - June 29; Tuesdays and Thursdays, 3-6pm in MY330
Add Deadline: May 24
Drop Deadline: June 8
|APS1022H: Financial Engineering II||SUMMER 2023: May 15 - May 26, Monday - Friday Daily, 10-1pm in BA1190|
Course add deadline: May 16
Course drop deadline: May 19
|APS1028H: Operations and Production Management for Manufacturing and Services||Synchronous Delivery||WINTER 2024: Jan 9 - April 16, 100% online delivery, first class Jan 9, 9-12pm|
SUMMER 2023: May 23 - June 9, Week 1 - May 23-May 26, May 30th
Week 2 - June 5- June 9 Daily 1-4pm, in MY315
Course add deadline: May 23
Course drop deadline: May 25 *updated*
|APS1032: Introduction to Energy Project Management||FALL 2023: Sept 11 - Dec 11, Mondays, 5-8pm, in MS2173||x|
|APS1049H: Management Consulting For Engineers||FALL 2023: Sept 12 - Dec 15, Tuesday 9-12pm, in IN312E|
Summer 2023 - May 29 - June 16, Week 1 - May 29-June2, Week 2 - June 12-June16; Daily 9-12pm in MY350
Course add deadline: May 30
Course drop drop: May 31 *updated
|APS1050H: Blockchain Technologies And Cryptocurrencies||FALL 2023: Sept 12 - Dec 12, Tuesdays, 3-6pm, GB221|
WINTER 2024: Jan 9 - April 9, Tuesdays, 3-6pm, SF3202
SUMMER 2023: May 9 - Aug 15, Tuesdays 3-6pm in BA1190
Course add deadline: May 8
Course drop deadline: June 26
|APS1051H: Portfolio Management Praxis Under Real Market Constraint||FALL 2023: Sept 13 - Dec 13, Wednesdays, 3-6pm, GB120|
WINTER 2024: Jan 10 - April 10, Wednesdays, 3-6pm, GB119
SUMMER 2023: May 10 - Aug 16, Wednesdays, 3-6pm in BA2175
Course add deadline: May 8
Course drop deadline: June 26
|APS1052H: A.I. in Finance||FALL 2023: Sept 14 - Dec 14, Thursdays, 3-6pm, GB120|
WINTER 2024: , Jan 11 - April 11, Thursdays, 3-6pm, GB220
SUMMER 2023: May 11 - Aug 17, Thursdays 3-6pm in BA1190 (First class on May 11 held in GB119)
Course add deadline: May 8
Course drop deadline: June 26
|APS1053H: Case Studies in AI in Finance||FALL 2023: Sept 15 - Dec 15, Fridays, 3-6pm, BA2185|
WINTER 2024: Jan 12- April 12, Fridays, 3-6pm, WB119
Not offered in Summer 2023
APS500H1: Negotiations in an Engineering Context
Instruction of concepts, theories, and research but most importantly the practice of negotiation skills. The course will cover all kinds of negotiations scenarios that individuals might face in the course of their careers as Engineers; this could include a range of single-issue single-party negotiations to multi-party multi-issues negotiations.
APS502H1: Financial Engineering
This course will focus on capital budgeting, financial optimization, and project evaluation models and their solution techniques. In particular, linear, non-linear, and integer programming models and their solutions techniques will be studied. The course will give engineering students a background in modern capital budgeting and financial techniques that are relevant in practical engineering and commercial settings.
APS1001H: Project Management
Darya Duma | Course Syllabus
Course intro here. Project management has evolved from being an accidental job title into being a chosen profession with career paths and a body of knowledge. This course covers most of the knowledge areas of the Project Management Institute: integration, scope, cost, time, risk, human resources, procurement and communications management. We take a practical, applied approach, with the “PMBOK Guide” textbook, in-class exercises, and a team paper on “lessons learned” from an actual project. This a completely asynchronous online course.
APS1004H: Human Resources Management: An Engineering Perspective
This course analyzes the relationship between management and workers in an engineering (including construction and manufacturing) environment. The course takes a holistic and strategic view of how industrial relations affect the business environment. Students will study industrial relations from the context of engineering-related industries, economics, sociology, and psychology. Students will develop an historical appreciation and perspective of the evolution and development of labour relations through concepts presented by figures such as Adam Smith, Fredrick Taylor, Charles Deming, and J.M. Juran. The goal of the course is to provide a general manager with a thorough understanding of how they can develop a competitive advantage for their organization through effective and thoughtful human resource management practices. In the context of how they relate to engineering and industrial relations, the course topics include: organizational behaviour including methods of motivation, scientific management, quality control, employment and economics, employment as a social relation, unions and other forms of employee representation, internal labour markets, strategic planning and the formulation of human resource strategy, practices and policies.
APS1005H: Operations Research for Engineering Management
This course introduces optimization techniques applicable in solving various engineering programs. These techniques are widely used in engineering design, optimal control, production planning, reliability engineering, and operations management. The contents of this course can be classified into two major categories: modeling techniques and optimization algorithms. Topics include linear programming, sensitivity analysis, nonlinear programming, dynamic programming, decision making under uncertainty, new developments in optimization techniques. The course will also examine several case studies to gain understanding of real applications of optimization techniques.
APS1009: Natural Resources Management
This course focuses on management of projects on Natural resources and offer graduate engineering students the opportunity to learn specific management skills and management tools, from a holistic view of issues related to the management of natural resource projects and enterprises, and the required knowledge to identify and develop sustainable solutions to the interdisciplinary challenges related to the sustainable management of natural resources projects. The course also considers the management of public enterprises that are in charge of planning and developing national resources and important sustainable national and regional natural resources projects, such as water, environment, energy, minerals resources, or biological resources, not only in Canada, but also internationally. This course will help students to develop the necessary skills and capabilities needed and required in real life from graduate engineers, to be able to work successfully in natural resources management and natural resources projects and enterprises, whether working with the public sector or private sector, or in P3-Public Private Partnership and projects or working with a non-governmental organization, These skills will enable the students to work with different stakeholders,thinking strategically and keeping in mind always, the social responsibility as a core of all the projects related to natural resources. The course utilizes lectures, guest speakers,class discussions and analysis on real cases, and requires students to write and present a final team project report.
APS1016H: Financial Management for Engineers
The students will be exposed to classical equity valuation methods; such as discounted cash flow analysis, net asset value, fundamental analysis and relative value analysis, using measures such as P/E multiples and P/Cash flow multiples. The students will be introduced to the principles of bond and stock valuations with a special emphasis on its relation to the cost of capital. The course will take an in depth view of capital budgeting, capital investment decisions and project analysis and evaluations. It will introduce students to the concept risk and return in equity markets. The students will get hands on experience in calculating cost of capital and hence the appropriate discount rate to use in valuations. Theory of optimal capital structure and financial leverage will be discussed in addition to economic value added principles. The relevance of dividends and dividend policy will be debated in class. The concept of “does dividend policy matter” will be subject of a vigorous debate. Finally the topic of mergers and acquisitions will be covered in depth, with particular reference to recent mergers of Canadian companies.
APS1017H: Supply Chain Management and Logistics
This course is to provide students with a framework to design and control supply chain systems. To achieve the goal, the course will cover key modules in supply chain. The students will be exposed to topics such as: inventory theories, transportation, postponement strategies, supply chain dynamics, value of information, supply chain flexibility, and environmental issues. We will focus on the analytical decision support tools (both models and applications), as well as on the organizational models that successfully allow companies to develop, implement and sustain supplier management and collaborative strategies.
APS1020H: International Business for Engineers
This course provides an important background on sustainable international business for all engineering disciplines through Learning skills on International Business, learning management tools, and "hands-on" project work and BUSINESS CASES analysis for engineers. Each week there will be class discussion on an international business case and/or on new business concepts and learning new Management tools as part of the weekly learning and assignments. The course utilizes lectures, International experienced guest speakers, such as CEO or members of the board of directors of International Engineering firms with projects and experience both in Canada and abroad, as well as guest speaker with global experience, also the course uses real case analyses, and requires students to write and to present a final Team project report. There will be tutorials by appointment for those students (teams) that will require additional time for learning or understanding IB issues and concepts for the course and for the Final team project. This course reaches beyond merely learning the basic concepts of international business. We will use real life examples to practice and debate the different principles and best practices used to pursue cross-border operations considering all the different stakeholders. This course on IB provides context to enable the graduate engineering student for a deeper learning on IB, and related skills. Also, this course provides what could be, for some students, the first true international business course for engineers with the guidelines and help from your experienced instructor. This 2023 course is about not just the updated knowledge on IB but to acquire the practical skills and management tools needed when pursuing sustainable business across the borders. You will get an understanding of the current issues (2023), such as the current trade war between USA vs China, and Brexit, Also the current geopolitical events in The Americas, affecting the whole continent, also about Europe and MENA regions current issues affecting international business and how it may affect Canada, Europe, Asia, and Africa, pointing out in class discussions about opportunities and Risks. How may be affected international businesses with the recent high interest rate environment. Also, we will explore how new technologies such as AI and blockchain are changing the arena of International Business and how we can prepare for the present and future on international business. The interrelation between different Stakeholders and Corporate Social Responsibility is a core learning consideration on this course, within the learning of holistic analysis approach of international projects considering ESG, Environment, Social and Governance factors, risk, and opportunities.
APS1022H: Financial Engineering II
Roy H. Kwon, C.G. Lee
The course presents two important topics in financial engineering: portfolio optimization and derivative pricing. These two topics are explored by the application of a number of mathematical tools, including linear programming, nonlinear programming, statistical analysis, and the theory of stochastic calculus.
APS1028H: Operations and Production Management for Manufacturing and Services
Operations Management is the systematic approach and control of the processes that transform inputs (e.g. human resources, facilities, materials, processes, enterprise management information systems, etc.) into finished goods and services. The operations function consists of the core wealth creation processes of a business and helps an organization to efficiently achieve its mission while constantly increasing productivity and quality. This course focuses on the role of operations management as a strategic element of the total organization. We will cover classic and up-to-date tools and concepts used to support operational managerial decisions in variety of industry sectors both in manufacturing and the service sector. The course covers areas such as strategy, product design, process design, plant location and plant layout, inventory management, role of technology in OM, HRM, Socio-Tech Systems, Group Technology, ERP / CIM, Quality Management, Maintenance Management. The course is tailored for engineers that aspire to senior management positions starting as departmental / functional managers of operations or engineering, and then progressing to directors, VP Operations, VP Manufacturing and eventually becoming a Chief Operations Officer (COO) or C-Level Certified Management Consultants in small to large scale enterprises. This course will incorporate academic scholarly readings to provide the broad theory of OM but most of the readings and discussions will be based on the instructors many years of hands on practical experience in OM in a variety of industry sectors.
APS1032: Introduction to Energy Project Management
Project management is important for any business organization, but particularly so for the energy industry. Sufficient controls are needed during initiation, study, implementation, and closeout of any energy project, and project managers within the energy environment (such as oil, gas, nuclear, …) face unique challenges and important risk management considerations. This course will expose students to best project management practices within the context of the energy industry. The course will introduce the particular characteristics of managing energy projects from the planning phase to closeout. Environmental assessments, geopolitical considerations, the political landscape, risk management and the roles of different players will be discussed. Tools to monitor the health and progress of a project will be introduced. Examples of different types of energy projects in the fields of nuclear, bio-mass, oil, gas, wind and solar will be used to illustrate concepts.
APS1038H: Strategic Sustainability Management for Businesses and Products
This cross-disciplinary graduate course provides a holistic overview of the environmental, social, economic and governance (ESEG) aspects of strategic sustainability management for businesses and products. You will have the opportunity to learn about a variety of industry sector, business and product sustainability challenges along with collaborative solutions applied and results achieved. You will gain a broad, cross-functional, cross-disciplinary perspective that will prepare you to facilitate sustainability management programs.
The importance of integrating strategic sustainability management into the interconnected network of systems that make up the business-to-business value chain will be discussed. The value of managing sustainability impacts throughout the full life cycle of products will also be addressed. Internationally recognized frameworks, best practices, methodologies and tools based on ISO international standards will be introduced as vehicles for practical application of solutions that support leadership in sustainability performance improvement.
This course is for graduate engineering students who wish to gain a broader and deeper understanding of business and product strategic sustainability management from multiple stakeholder perspectives that make up the business-to-business value chain. This course is for you— if you aspire to be a sustainability change agent within industry, who believes that businesses can and should be a thriving force for good in the world. You seek to understand, facilitate and influence how stakeholders can collaborate to lead the development and implementation of transformative sustainability management systems and programs.
Students will have the opportunity to select and research an existing cross-sector sustainability challenge along with the solutions applied and results achieved. You will present a summary of your work to the class to enhance peer-to-peer learning.
APS1039H: Enterprise Risk Management
Risk Management is a highly valued discipline and eagerly sought after by organizations that are heavily regulated, requiring high resiliency, that deal with environmental, health and safety issues, involved in project management, insurance, financial services and also within the public sector.
Enterprise Risk Management (ERM) is a decision support system that helps such organizations understand risk and assure the achievement of their goals. Engineers often play an integral role in an organization’s ERM effort, from identifying risk and assisting in the design and implementation of risk response solutions. This course is intended to provide to a high level understanding of what is risk and what does an ERM process look like for organizations including some common challenges and pitfalls of institutionalizing an ERM culture.
APS1040H: Quality Control for Engineering Management
This course introduces quality control techniques applicable in various engineering settings. These techniques are widely used in monitoring and improving the quality of both products and services. Topics include process quality inferences, statistical process control, various control charts, system capability analysis, design of experiments, and acceptance sampling. Various simulation models will be used to represent and generate data sets in various settings, for analysis and charting with widely available software.
APS1049H: Management Consulting For Engineers
Management Consulting will continue to be a significant career option for many graduate students, regardless of whether a student’s academic foundation is in business, engineering, or the basic sciences. Careers in Management Consulting often provide individuals an opportunity for challenging work, continued self-development, access to important social and professional networks, and, over time, significant financial rewards. This course is designed to enable graduate engineers explore, and prepare for a career in management consulting. The course is taught by Fellow Certified Management Consultant (FCMC), licensed professional engineer, and as an entrepreneur built and sustained a management consulting business over a period of 25 years. The Global Management Consulting Industry has grown in size and complexity particularly since the early 1990’s. Although there are many small niche firms, the industry is dominated by a relatively few very large global organizations that practice in a variety of business settings and business disciplines. In addition many businesses have developed internal consulting organizations to provide consulting related services within the organization and often in conjunction with external consulting services offered by third party firms. In this course we explore what it means to be a Management Consultant, and will introduce students to consulting frameworks and methods; simulate consulting project activities and situations using business cases; and network students with practicing consulting professionals from a variety of global and local firms. Within the context of this course, consulting is viewed broadly and is inclusive of a number of practice areas including Strategy , IT and Systems Integration, Marketing, Human Resource Management, Operational / Process / Supply Chain, Organizational Development, and the very specialized area of Engineering and Product Development Management. Consulting also cuts across a wide variety of industry sectors from public sector (government, health care, infrastructure, defense etc), to private sector (manufacturing, oil gas, natural resources), Course participants will be organized into teams and will have the opportunity to identify and complete a project on the practice of management consulting that is aligned to the emerging needs of the profession (collaborating with external partner firms). In addition students will wear an entrepreneurial hat, and will be required to develop an individual blue print, and business plan of their future management consulting business which might be in an emerging field of consulting such as life sciences, data analytics, cyber security, crowdsourcing and digital strategy.
APS1050H: Blockchain Technologies And Cryptocurrencies
Loren Trigo and Sabatino Costanzo
Bitcoin is a particular implementation of Blockchain technology that has led to a disruptive “product”: a set of digital cryptocurrencies with the potential to compete with fiat currencies. This course will provide students with the concepts and mechanics of the Blockchain technologies starting from Bitcoin. Unlike ECE1770, this course is not focused on middleware software design per se, but on how the Blockchain middleware can serve as a platform that supports products (cryptocurrencies, tokens) and applications that are relevant for businesses and other users. Students become acquainted with the history and typology of Blockchain technologies; develop and apply a set of selection criteria for the evaluation of Blockchain consensus strengths, weaknesses and risks; trace a likely path for the adoption of Blockchain technologies-- beginning with the identification of processes where Blockchain ledgers lead to efficiencies, to the emergence of new business models where the use of cryptography is essential. For this reason, this course includes a gentle but complete introduction to cryptography that covers all the essentials from asymmetric encryption to “zero-knowledge-proof-of-knowledge” proofs. On a practical level, participants acquire a concrete understanding of Blockchain technologies through the installation, operation and modification of a number of Blockchain technologies that operate in real-world testnet networks: starting from the operation/modification of a simple Bitcoin node; moving on to the operation of Bitcoin and Ethereum wallets, and to the operation/modification of Ethereum clients or DApps providing a business service, and ending with the trading of a cryptocurrency account. For more details please go to the Course Layout section of the Syllabus.
APS1051H: Portfolio Management Praxis Under Real Market Constraint
Sabatino Costanzo and Loren Trigo
After an introductory review of the techniques most commonly used to evaluate investment portfolios and investment managers and an overview of the theoretical foundations of modern finance, this course will, through a combination of lectures, readings, real case studies and hands-on exercises, enable students to learn how to use --in real time and under real constraints--, the five main algorithmic trading & portfolio management systems developed by the instructors to manage their own clients’ investment portfolios in their professional private practice. After completing this course the participants should be able to manage basic Stocks and ETF portfolios as well as trading currency pairs and basic derivatives portfolios of Credit & Debit Spreads, by using time-tested “value” and “momentum” strategies, statistical-arbitrage pairs-trading techniques and covered options algorithms, all coded in the python programs developed by the instructors to that end. Students will also be able to manage the risk of any basic investment portfolio using index-option’s hedging and/or market breadth- based algorithms, and to apply the best known tests to evaluate the back-testing results of different trading systems. As collateral benefits of this course, participants will be exposed to the basics of python in finance -as they learn how to calibrate the trading software shared by the instructors-, as well as to basic equity valuation methods, basic portfolio optimization methods and basic bond and derivative pricing methods. Participants will be also exposed through case studies to the portfolio management strategies of some of the most important contemporary portfolio managers and apply digested versions of their techniques to basic portfolios under real market constraints. In the long run, after having assimilated and tested what they’ve learned in this course, students should be able to assemble general portfolio management strategies well adapted to their own risk/return profiles. For more details please go to the Course Layout section of the Syllabus.
APS1052H: A.I. in Finance
Sabatino Costanzo and Loren Trigo
In this course we’ll give an overview of several applications of machine learning to capital market forecasting and credit modeling, beginning with regressions, “shallow” layered machine learning models (e.g. Support Vector Machines, Random Forests), and ending with “deep” layered machine learning models (e.g. Long Short Term Memory Networks). Each model is discussed in detail as to what input variables and what architecture is used (rationale), how the model’s learning progress is evaluated and how machine learning scientists and capital market traders evaluate the model’s final performance so that by the end of the course, the students should be able to identify the main features of a machine learning model for capital market forecasting and to evaluate if it is likely to be useful and if it is structured efficiently in terms of inputs and outputs.
The course covers (but it is not limited to) the following subjects: Training and testing workflow: scaling, cross-validation pipelines. Gradient descent: mini-batch, stochastic. Financial metrics: profitability and risk. Financial feature engineering. Models: multivariate regression, logistic regression, support vector machines, principal component analysis, decision trees, random forests, k-means, and hierarchical clustering, Gaussian mixtures, MLPs, LSTMs, and auto-encoder neural networks. Applications: credit modeling, financial time-series forecasting, investment portfolio design, and spread trading, credit cycle regime identification. For more details, please see the Course Layout in the Syllabus.
In terms of requisites, the participant should be familiar with the foundations of statistics, the basics of logistic regressions (desirable), and basic linear algebra (desirable); however, since our course intends to be self-contained, we will provide a review of these concepts as needed. As the examples of our course come from finance, some familiarity with capital markets and the basic financial concepts is recommended. Basic knowledge of Python or some other programming language is recommended, even though the objective of the course is not to learn how to program (shallow & deep) machine learning models from scratch, but rather, to understand how they work and to learn how to adapt them to the particular needs of the user and to optimize their application to market forecasting. The mathematical foundations of the basic machine learning models (regressions, neural networks, support vector machines, trees etc.) will be discussed and followed by a panoramic view of the inputs that are most likely to provide valuable information for market forecasting. Standard benchmarking methods used in the industry will be also covered. Subsequently, a number of basic --already programmed-- models will be discussed in detail and their performance evaluated.
APS1053H: Case Studies in A.I. in Finance
Sabatino Costanzo and Loren Trigo | Syllabus
This course has been structured over a collection of (more than 20) real-life case studies that are practical applications of many of the topics discussed in the other courses we teach. The course ("Case Studies of A. I. in Finance"), will be taught in the format of a seminar, which means, among other things, that it will be delivered in an informal [(*) Refreshments included] but collegiate atmosphere in which participants are considered as colleagues, with all the advantages and responsibilities that this entails.
The course will start with some introductory sessions (taught by the instructors and possibly some guests) aimed to establish the theoretical foundations needed to make the course self-sufficient regarding the topics to be discussed during the seminar presentations. Specifically, the introductory sessions, --to be held before the “reading-week break”--, will consist of general reviews covering topics that go from a "Basic Finance Primer" to a "Comprehensive Introduction to Reinforcement Learning". (After the reading-week break, though, the seminar sessions will consist of presentations of case studies assigned to the participating students).
The Fall Term will is a good opportunity to take this seminar, given that it may not be offered in the future as frequently as our other courses due to the organizational challenges that its logistics imply.
Since the long-term goal of this seminar is to establish the foundation of a stable platform for promoting Fin-Tech research, we want to extend here an open invitation to all students of the Winter 22 and the Fall 23 editions of this course, to keep attending its future editions as active speakers, so that this event may transcend its condition of being "one more course in Finance" to become a functional and growing community of professionals interested in Fin-Tech.
Summarizing, APS 1053 focuses on the application of advanced artificial intelligence techniques to more than 20 solved case studies in stock trading and hedging strategies, portfolio construction, modelling options strategies, investor’s modelling, financial news and building Robotic-Advisors. The advanced techniques include the incorporation of recently open-sourced libraries for the calculation and evaluation of financial indicators, the incorporation of custom functions for cross-validation, evaluation and model selection, the reformulation of problems in terms of reinforcement learning and the implementation in Python of reinforcement learning solutions and the analysis of situations where reinforcement learning fails. Only basic coding skills (preferably in Python) and a very basic familiarity with Finance terminology will be needed for the course.