Introduction
The Lab is designed for students majoring
in big data technology and related fields. It provides practical project
resources and supporting teaching platforms based on the latest big data
application technologies and mainstream tools in the financial industry. The Lab
is designed to meet the typical job tasks and professional technical abilities
required for big data technology talent in the financial industry. It aims to
cultivate the core competencies of big data collection and processing, big data
analysis and visualization, and big data implementation and maintenance for
various positions. Through project practice, students will become proficient in
using technologies and tools such as JDK, Hudi, Flink, FlinkCDC, Kafka, Hive,
Spark, Hadoop, Mysql, SpringBoot, Vue, Miniconda, Python, TensorFlow, Nginx,
FineBI, which will help enhance their problem-solving ability and innovation
ability.
Enterprise positions: Big Data Development
Engineer, Big Data Collection and Processing Engineer, Big Data Analysis and
Visualization Engineer, Big Data Implementation and Maintenance Engineer
Applicable majors: college majors in big data technology and related fields. Project Products: Financial Big Data Collection and Processing Practice Project (Financial Big Data Real-time and Offline Processing System), Financial Big Data Analysis and Visualization Practice Project (Financial Credit Analysis and Data Visualization System), Financial Big Data Implementation and Maintenance Practice Project (Hudi Financial Big Data Platform Deployment), Big Data Full Stack Technology Integrated Practice Project (Financial Big Data Statistical Analysis Platform)
Project Courses: a number of post level and post group level projects based on the application of big data in the transportation industry, including big data collection and processing, big data analysis and visualization, big data deployment and operation and maintenance training
Applicable scenarios: professional
teaching, integrated training, competition training.
Feature
Industry-oriented and covering cutting-edge
technologies
Based on the latest Hudi data lake
technology in the industry, the real-time data lake storage mode is used to
provide more efficient support for big data analysis and mining, using Python,
Pyecharts and FineBI self-service data visualization tools to achieve data
visualization; using SpringBoot and React frameworks to realize the web display
of data visualization dashboards, training students' big data full stack
development skills.
Unique industrial-level cases,
teaching-based disassembly
Based on the TOPCARES educational methodology
of Neusoft's unique feature, the industrial-level project is decomposed into a
progressive project system, from simple to complex, helping students gradually
improve their practical skills. We provide 3 position-level and 1 position
cluster-level projects, progressively training different job skills.