This course is designed for students who have an interest in the future of finance, technology, blockchain, cryptocurrency, artificial intelligence, and work. Beginning with an exploration of Fintech (financial technology), we explore technology’s impact on everything from banking to real estate to Wall Street. Additionally, we look at how artificial intelligence (AI) will automate and reduce the need for human workers, as AI, Fintech, and other technologies are combined to automate many tasks.

After gaining a solid understanding of the real-world use cases of Fintech and the everyday ways it impacts the economy, social justice, and our lives, students take a journey of discovery into the world of AI, the Internet of Things (IoT), blockchain, Bitcoin, and cryptocurrency. Since Bitcoin’s launch in 2009, cryptocurrency and decentralized ledger technology, aka blockchain, have emerged as an economic force majeure, disrupting the fundamentals of how people interact and how they perceive money. In addition to pushing the evolution of money, blockchain technology is now poised to disrupt how we organize businesses and the future of work. Course participants explore the organizational impacts and transformations caused by blockchain and cryptocurrencies and examine what this will mean to them as future CEOs and global business and thought leaders.

The course concludes by exploring the perspective of entrepreneurs and innovators, further examining how technologies come together to form the businesses, disruptions, and methodologies of the 21st Century. Participants walk away with a fundamental understanding of what tokens and cryptocurrencies are; how businesses leverage blockchain technology, AI, and other Fintech applications; and how digital transformation impacts social interactions and the future of work.

Please note: This course is not a computer programming course and requires no prior knowledge or experience, but rather looks at these emerging technologies more broadly from business, social, political, and cultural perspectives.

Data science and machine learning are exciting and popular disciplines. While different fields, they work best in sync to help change the way humans think, behave, and interact. In fact, some of the most popular data science methods stem from machine learning. Through this course, students will be introduced to the foundations of both science areas and explore available career opportunities. Beginning with an overview of the landscape and real-world applications, students will learn how data science and machine learning impact the world in which we live, every day. Further, students will gain hands-on experience with introductory coding using Python and become versed in popular machine learning algorithms. By the end of the course, students will use their benchmark knowledge to analyze and present data ethically and effectively. Finally, students will leave the course prepared for more advanced practice in data science and machine learning. 

Please note, this course is for students with little-to-no previous experience with coding/programming. Students with more advanced knowledge should consider Data Science and Machine Learning II. 

The power of data science and machine learning can change the world. From voice activation to video game programming to advancements in medical science - the possibilities for activation are endless. Through this advanced course, students will leverage their foundational knowledge of Python to develop a more sophisticated programming skill set. Further, students will use a variety of mathematical techniques (statistics, linear algebra, and probability) to analyze data and create impactful visualizations. By course completion, students will become well-versed in a range of strategies and techniques in both data science and machine learning and become data-driven decision makers. Further, students will be able to apply communication skills and fairness frameworks to identified solutions, making them invaluable assets to any future data science/machine learning classroom, or future employer. 

Note: This course is for students with prior programming experience (in particular, Python) and/or previous coursework in Data Science and Machine Learning. Further, some background in statistics and linear algebra is helpful. Students with little-to-no prior experience in these areas should explore our Data Science and Machine Learning I course. 

This course is intended for students with a strong programming background, including comfort in applying object-oriented programming and recursion to solve problems. Students will start with the history of artificial intelligence and progress to focus on more powerful, classical techniques. Optimization and probabilistic strategies are explored so as to demonstrate tradeoffs between different types of search strategies. Several well-known problems—such as N-Queens, Knapsack, Post correspondence, and Chess—may be considered. Participants are expected to complete challenging and thought-provoking assignments using the techniques taught in class as well as their prerequisite knowledge. The end goal of the course is for each student to be able to build functioning programs in Python and Java.

Student computers can be either Mac or PC, but should have at least 10GB of free space.

This course provides an intensive introduction to coding with Python, one of the most widely used and intuitive programming languages today. Python is an interpreted language that, while syntactically simple, is equipped with a powerful set of libraries. Data analysis, machine learning, AI, data visualization, and web development can all be done quickly and efficiently with Python, making it an ideal first language for new programmers.

Participants learn the fundamentals of programming with Python through interactive and real world applications; they are introduced to best programming practices, data representation and storage, data structures, functions and scripts, and more. By the end of the course, students will have an understanding of the programming fundamentals required to approach novel and interesting problems with Python.

The course alternates between guided instruction, collaborative exercises, and independent coding challenges. While learning to code in Python, students develop logical thinking and problem-solving skills that prepare them to approach novel challenges with confidence and to continue their studies in computer science, AI, and beyond.

No previous programming experience is required, but participants should have an aptitude for logical reasoning and systematic thinking.

Student computers can either be a PC or a Mac, but should have 8GB – 10GB of free space. Students enrolled in the on-campus program should bring their laptop to class. Please note that Chromebooks are not compatible.