Introduction

 The Big Data Analysis and Visualization Lab at Neusoft is primarily aimed at the Big Data Technology major, covering over 50 knowledge and skill points related to big data analysis and visualization. Through 4 core courses with over 170 3-5 level projects, and four 2-level advanced projects, the lab aims to cultivate big data collection and processing engineers for the position, helping students effectively train their job skills.

Enterprise Position: Big Data Analysis and Visualization Engineer

Applicable Major: Higher Vocational School Big Data Technology and Other Related Majors

Course Products: Big Data Analysis and Application Technology, Python Data Analysis Technology, Data Mining Application, and Data Visualization Technology and Application

Project Products: Big Data Analysis and Visualization Practice Project (E-commerce Operation Analysis and Data Dashboard System), Transportation Big Data Analysis and Visualization Practice Project (Traffic Travel Analysis and Visualization System), Financial Big Data Analysis and Visualization Practice Project (Financial Credit Analysis and Data Visualization System), Telecommunications Big Data Analysis and Visualization Practice Project (Telecommunications Multi-dimensional Analysis and Data Visualization System) 4 comprehensive projects

Applicable Scenarios: Professional Teaching, Integrated Training, Competition Training.

Industry-Oriented and Covering Advanced Technologies

Covering Python data analysis and the use of various visualization tools, using enterprise mainstream technologies, including PyEcharts, time series analysis, clustering analysis, offline data warehouse, columnar storage, stream data processing, Python data analysis, Superset, FineBI chart setting, etc.

Features industrial-level case teaching disassembly

Based on the TOPCARES educational methodology of Neusoft, the industrial-level project is disassembled into a progressive project system, from simple to complex and from easy to difficult. The 180+ 1-5 level projects help students gradually exercise and improve their practical skills.