Recent Courses
BUSF-SHU 271 – AI for Business – Reinforcement Learning
[Most Recent] [Spotlight]
Reinforcement Learning (RL), a cornerstone technique of Artificial Intelligence (AI), is revolutionizing the business landscape by enabling the creation of self-improving systems that enhance decision-making and operational efficiencies. This course is dedicated to empowering students with the skills to architect and refine AI strategies, with a special focus on the application of reinforcement learning to solve complex business challenges.
Past offerings: Spring'23, Fall'22, Spring'22, Fall'21, Spring'21, Spring'20, Spring'19
BUSF-SHU 276 – AI for Business – Machine Learning
Machine Learning (ML), especially with the advent of large language models, stands at the vanguard of contemporary AI. This vibrant field merges computer science, mathematics, statistics, and optimization, where sophisticated algorithms, propelled by increased computational power and expansive datasets, enable applications across diverse domains. This course delves into ML’s bedrock principles and models to tackle problems using large datasets. We discuss ML methodologies, from time-honored supervised and unsupervised models to cutting-edge deep learning.
Past offerings: Spring'21, Spring'20
SHBI-GB 7312 – Network Analytics – NYU Stern – NYU Shanghai MS in Business Computing and Data Analytics
[Most Recent] [Spotlight] [NYU Stern News]
In this course, we navigate the complex networks that underpin our social and technological systems. Students will delve into the architecture of social and information networks and their implications for culture and markets. Bridging theory with real-world applications, the course offers insights in leveraging network theory for predictive machine learning, search algorithms, and economic analysis. Students will emerge with a multifaceted understanding of how networks can be leveraged in various fields.
Past offerings: Spring'23, Fall'21, Fall,20, Fall'19
BUSF-SHU 310 – Data Science for Social and Information Networks
We live in a web of networks, spanning social bonds, corporate structures, and digital connections. Big data now positions networks as critical frameworks for decoding our digitally interconnected society, where minor local interactions can have major system-wide consequences. This course integrates computer science, machine learning, economics, and social science, providing analytical skills to make sense of network data and to solve intricate business challenges.
Past offerings: Spring'22, Fall'21, Fall'20, Fall'19, Fall'18
Stanford University – Machine Learning for the Social Sciences
This course is an introductory-level overview of machine learning concepts for students without previous exposure to the field. We will survey some of the important elements of supervised and unsupervised learning methods. Students will work on hands-on applications of ML to social science problems.
Past offerings: Winter'16, Winter'15
Cornell University – CS2043 – Unix Tools & Scripting
UNIX-like systems are increasingly used on personal computers, mobile phones, web servers, and many other systems. This course provides intensive training in Unix command-line tools and scripting to enable the automation of a wide range of computing tasks. The syllabus guides students from shell basics and piping to regular expression processing, culminating in Bash and Python scripting.
Past offerings: Spring'14, Spring'13