Tech Finance
Tech Finance Tech Finance
Program overview
Introducing the Tech Finance Executive Certificate: a cutting-edge program designed for those eager to explore the forefront of finance through the lens of artificial intelligence and machine learning. In today’s rapidly evolving business landscape, driven by both technology and regulation, it is essential not only to understand finance but also to grasp the transformative AI methods reshaping the industry. Notably, with Article 4 of the AI Act mandating that anyone dealing with AI systems must have adequate training, acquiring these skills is more crucial than ever.
This program equips participants with a solid foundation in AI, focusing on Machine Learning (ML) and Large Language Models (LLMs). Key techniques include supervised and unsupervised learning, regression, classification, and neural networks, applied to practical challenges like stock prediction, credit scoring, fraud detection, and antimoney laundering. Participants gain insights from experienced academics and practitioners, ensuring a comprehensive understanding of the technologies that revolutionize finance today. Additionally, the program covers the essentials of FinTech, including blockchain and cryptocurrencies, providing a well-rounded perspective on the future of finance.
Tech Finance
PARTICIPANT PROFILE AND PREREQUISITES
The program is aimed at:
TechFin is intended for current and aspiring corporate executives, business leaders, technical professionals, engineers, scientists, or any employees who deal with an AI system in their organization and want to obtain a deep, hands-on understanding in the cutting-edge field of machine learning and FinTech. Some knowledge of programming is useful, although not necessary to be able to follow the program. TechFin aims to provide its participants with a working understanding of the architecture of Python programming and how Python can be used to create applications in Machine Learning and AI.
* Net price, HEC Paris is not subject to VAT. Prices, dates, faculty, and program content are subject to change.
Objectives
Acquire a qualitative understanding of data science and machine learning concepts related to finance
Enhance quantitative skills through hands-on problem solving
Gain intuition for advanced machine-learning concepts, topics, and tools.
Optimize trading strategies, credit scoring techniques, or text interpretation methods used in Finance.
Analyze the corporate impact of FinTech and regulation compliance.
Improve business strategies by a better predictive ability of their consequences.
Develop global perspectives and boost networking opportunities
Apply concepts and methods learned during the program to your professional environment
Academic Director(s)
Learning methods & evaluations
Learning methods
Most courses in the TechFin program are delivered by alternating between lectures, case studies, exercises, simulations, applications, group work, and in-class presentations. Most courses require preparation before class: reading case studies or articles, answering preparatory questions, or solving a pre-class assignment. In the second module of the program (Applications), participants work in groups on problem solving that involve Python programming on Google’s Colab platform. These problems give participants the opportunity to get hands-on experience with problem solving and applying what they have learned during the previous courses on a group project.
Evaluations
Participants are evaluated along multiple dimensions: group work write-ups or presentations on projects or case studies, quizzes, in-class or take-home exercises, multiple-choice questionnaires, final exams, post-class analyses, and class participation. The weights instructors choose among all these dimensions vary with each class.
Program
The program is comprised of a 4-day module of foundational courses and an 8-day module of applied courses. The foundational courses provide an overview of the main concepts in data science, machine learning, AI, FinTech, financial markets, corporate finance, banking, and risk management. The applied courses take an in-depth, hands-on approach by investigating machine learning approaches to return predictability, trading strategies, credit scoring, fraud detection, regulatory reporting, text interpretation, sentiment analysis, and also by various FinTech and RegTech applications.
Are you interested?
Do you feel that this program could be made for you?
In order to get feedback from our admissions teams regarding your suitability for the program, please do not hesitate to fill in our short online form below or contact us .
This program is accessible for people with disabilities. Please contact us if you have any specific requirements or to obtain the Public Accessibility Register.
Contact
Funding options
Find out more about possible funding options for the program you have chosen.
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