To Be Better | Study with North Carolina State University (NCSU) with CDA!

North Carolina State University (NCSU or NC State) is a top public research university founded in 1887 and enjoys a high reputation in the United States. There are nearly 30,000 existing students (including about 1,000 international students) with strong faculty, and 19 professors have been elected as academicians of the National Academy of Sciences or National Academy of Engineering. North Carolina State University is rated as one of the top 5 public universities in the United States.
This winter, study with North Carolina State University (NCSU) with CDA!
North Carolina State University is one of the earliest schools in the United States to establish big data majors, and is well-known in the field of big data. Therefore, the CDA institute and North Carolina State University (North Carolina State University) provide Chinese and American big data analysis courses (overseas study tours) for college students and in-service staff.

Introduction:
The course is divided into two stages. The first stage is a domestic basic course, which takes 4 weeks (teaching on weekends); the second stage is an American training course (US teachers provide on-site instruction in English), and the time is two weeks (teaching within weeks). The CDA Sino-US study tour project will help students master the international general process of data analysis through case teaching, understand the latest developments in the field of data analysis in the United States, and have comprehensive capabilities in modeling, computing, and visualization that should be undertaken by commercial data analysis projects. To lay the foundation for students to further study abroad or enter the employment of multinational companies. At the same time, build a Sino-US big data exchange platform to provide students and practitioners with an international perspective.
detailed arrangement:
Chapter 1: Statistical Basics of Data Analysis Chapter 2: Basics of Mysql Database Chapter 3: Python Programming Basics and Pandas Data Analysis Chapter 4: Using Python for Web Crawler Chapter 5: Python for Statistical and Regression Analysis Chapter 6 : Python for dimension reduction and other analysis methods Chapter 7: Python for time series and comprehensive case analysis Chapter 8: Python data visualization Chapter 9: R language programming basics and descriptive analysis Chapter 10: R data cleaning and statistical analysis Chapter 11: Business English (NSCU class)
Chapter 12: Model Theory (2 Kaggle cases, one each for R and Python) (NSCU class)
Chapter 13: Model Practice (NSCU class)

Other benefits
Two-week study tour to the United States (1. On-site study at North Carolina State University; 2. Outlet shopping, Duke University / University of North Carolina Chapel Hill / or Triangle Research Park) ; Closing banquet and issuing certificate (Joint certification of North Carolina State University and CDA).

Project lecturer:

Tao Pang # Project Director * Tenured professor of North Carolina State University, director of financial mathematics project, financial big data expert. Chartered Financial Analyst (CFA), Financial Risk Analyst (FRM). Former President of the North Carolina Branch of the Global Risk Management Association, a specially-appointed expert of the United States Genworth Corporation.

Project lecturer 2 # Statistics professor of North Carolina State University * Big data statistical analysis and modeling expert, proficient in R language. Has more than 20 years of teaching and scientific research experience. Distinguished experts from companies such as Bayer, Merck, GSK, CDC and government agencies. 2008 Beijing Olympics specially hired overseas data analysis experts. He once served as deputy dean of the Institute of Applied Mathematics and Statistics.

Project lecturer 1 # Professor of Operations Research, North Carolina State University * Doctor of Carnegie Mellon University. Expert in numerical calculation modeling. Python expert for many years engaged in teaching and scientific research on industrial and commercial optimization modeling and calculation.