DESIGNED FOR NON-PROGRAMMERS
Foundations of Data Science course on Python and Statistics.
TO GAIN TECHNICAL AI SKILLS
Become a power user of AI toolbox including Sci-kit and Tensorflow
IN ONE YEAR
5 courses + 1 foundation course, each for 2 months
Program Highlights
Each course offers 48 hours instruction— NOT a self-help program
Flipped classroom with time devoted to hands-on programming labs— NOT an AI business program.
In the application process of QF Level 6 Qualifications— NOT an unregistered program.
Why Enroll For Postgraduate Diploma in FinAI?
Join an academically rigorous data science and machine learning five-course program delivered over 10 months. Non-programmers are welcome to take the prerequisite course to acquire foundation skills in Python programming and data science.
Gain cutting-edge and hands-on AI knowledge from the latest content developed by the world's leading universities (Stanford, Berkeley), delivered by top academic instructors with rich industry experience.
Become a power user of the latest data science and AI tool box, and apply the newly acquired skills to solve your finance problems more innovatively. Future-proof yourself for tomorrow's finance industry.
What You Will Learn
PYTHON PROGRAMMING
Gain confidence in programming in this popular language
DATA SCIENCE
Acquire the most sought-after analytical skills
MACHINE LEARNING
Learn the latest AI skills through hands-on programming labs
CAPSTONE PROJECT
Apply advanced data science and machine learning techniques to solve finance problems
CAREER DEVELOPMENT
Advance your career through industry connection and internship
This foundation course is a prerequisite for the FinAI Postgraduate Diploma Program. Students who have the required background need not take this course. It is prepared specifically for students who have not previously taken statistics or computer science courses, and is especially helpful for those who want to learn Python programming, refresh statistics knowledge, and apply basic data science practice.
This course explores the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction, and decision-making, with applications in the financial industry.
This course teaches the application of Python programming, with a strong focus on how to solve problems in finance, especially secondary market trading, quantitative modeling and forecasting.
This course provides a broad introduction to machine learning and statistical pattern recognition. This class presents algorithms and approaches including supervised learning, unsupervised learning and reinforcement learning.
This course covers the most established and state-of-the-art deep learning algorithms such as Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, and Network Deployment, and builds projects in Tensorflow / PyTorch and Scikit-Learn / Pandas / NumPy.
Through this capstone project course, students will be arranged into groups and aim to utilize the advanced AI techniques to solve a practical Finance problem.
Postgraduate Diploma
Upon successful completion of the program, students will receive a Postgraduate Diploma awarded by Hong Kong Graduate School of Advanced Studies, recognized under the Hong Kong Qualifications Framework Level 6 (Master’s level). Students can transfer the credits toward Master’s degree programs planned by GSAS or international universities.
Early applicants eligible for Straight-A Scholarship. Apply NOW
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Hong Kong Graduate School of Advanced Studies (GSAS) is a nonprofit institution aimed at training talented graduates to excel at the intersection of advanced technology and industry application. GSAS' predecessor has worked with the world's leading universities (Harvard, MIT, Stanford) in delivering executive programs for the past twenty years. To prepare students with sought-after technical AI expertise in the finance and business industries, GSAS' strategy is to utilize the latest content developed by the best universities and corporations, and to deliver them with first-class industry-experienced professors.
