Course Arrangement
Enrollment status: Enrolling
Course time: rolling classes
Course method: Zoom remote live teaching
Course schedule: 21 class hours for the main academic tutor + 9 class hours for the academic associate tutor + 6 class hours for the main thesis tutor + 21 class hours for the deputy thesis tutor, lasting 7 weeks
Course Description
If it weren't for the massive spending on research and development in the mid-to-late 1990s, we'd still be hearing the crackle of dial-up Internet connections. Facebook and Google will be a fraction of what they are today, and Amazon will likely only sell books. Thankfully, technological advancements have made terabytes of data analysis possible through massive investments in technology during the Internet revolution. From leveraging graphics processing units, GPUs, to performing deep learning, to deploying the entire architecture in the Amazon cloud, it is both beautiful and stunning to say the least. You're in the midst of the biggest technology revolution your generation has ever experienced, learn the skills and develop the research-driven mindset to make a big impact in the world of big data!
Suitable For
High school students and undergraduate students who are interested in data science and machine learning majors
Students majoring in mathematics, computer, information science and other majors, as well as students who hope to work in the fields of big data analysis, business analysis, computer algorithms and other fields in the future
Students with advanced mathematics, statistics , probability and Python programming foundation are preferred
Professor Introduction
Columbia University Professor
Patrick Houlihan
Professor of Data Science at Columbia University
Senior Vice President of Decision Making, Publicis Media Group
American B2B customer data platform CaliberMind data scientist
Co-founder of Quantheta
More than 14 years of professional consulting experience in the semiconductor industry
Leading consulting projects worth over US$500 million
Has hundreds of papers in the fields of software system design and data analysis
TA Introduction
Education background
Master’s/PhD background from TOP30 prestigious universities at home and abroad, over 40% of the team’s PhD students are
Professional and excellent
Have experience in publishing papers in relevant professional fields
Experience
Excellent academic performance & fluent in English, with many years of experience as a teaching assistant
teaching orientation
Seamlessly connect professor topics and participate in teaching and delivery throughout the process
Program Advantages
Complete course hours that meet the academic program requirements of colleges and universities
A complete scientific research project under the personal guidance of the professor
A true and valid recommendation letter personally issued by the professor
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