E-commerce Big Data Training Lab
Introduction
The Lab is designed for students majoring in big data technology and related fields, based on the latest big data application technologies and mainstream tools in the e-commerce industry. It provides practical project resources and supporting practical teaching platforms around the typical work tasks and professional technical abilities required for big data technology talent in the e-commerce industry, with the goal of cultivating core job skills in big data collection and processing, big data analysis and visualization, and big data implementation and maintenance.
Corporate Positions: Big Data Development Engineers, Big Data Collection and Processing Engineers, Big Data Analysis and Visualization Engineers, Big Data Implementation and Maintenance Engineers
Applicable Majors: College majors in big data technology and related fields
Project Products: multiple post level and post group level projects based on e-commerce big data industry application, including big data collection and processing, big data analysis and visualization, big data deployment and operation and maintenance training
Applicable Scenarios: Professional teaching, comprehensive training, competition training
Feature
Industry-oriented and covering cutting-edge technologies
Using enterprise-level development technologies, with Spark technology as the core, mainly using Hadoop distributed clusters, data warehouse Hive, data migration tool Sqoop, big data computing engine Spark, data collection tool Flume, distributed message queue Kafka, and distributed search and analysis engine Elasticsearch, to train students' big data stack development skills.
Industry-level case-based teaching
Based on the TOPCARES educational methodology of Neusoft, the industrial-level project is decomposed into a progressive project system. By starting from the basics and gradually becoming more difficult, it helps students gradually exercise and improve their practical skills. It provides 3 project-level positions and 1 position cluster-level project, for progressive training of different job skills.
The Lab is designed for students majoring in big data technology and related fields, based on the latest big data application technologies and mainstream tools in the e-commerce industry. It provides practical project resources and supporting practical teaching platforms around the typical work tasks and professional technical abilities required for big data technology talent in the e-commerce industry, with the goal of cultivating core job skills in big data collection and processing, big data analysis and visualization, and big data implementation and maintenance.
Corporate Positions: Big Data Development Engineers, Big Data Collection and Processing Engineers, Big Data Analysis and Visualization Engineers, Big Data Implementation and Maintenance Engineers
Applicable Majors: College majors in big data technology and related fields
Project Products: multiple post level and post group level projects based on e-commerce big data industry application, including big data collection and processing, big data analysis and visualization, big data deployment and operation and maintenance training
Applicable Scenarios: Professional teaching, comprehensive training, competition training
Feature
Industry-oriented and covering cutting-edge technologies
Using enterprise-level development technologies, with Spark technology as the core, mainly using Hadoop distributed clusters, data warehouse Hive, data migration tool Sqoop, big data computing engine Spark, data collection tool Flume, distributed message queue Kafka, and distributed search and analysis engine Elasticsearch, to train students' big data stack development skills.
Industry-level case-based teaching
Based on the TOPCARES educational methodology of Neusoft, the industrial-level project is decomposed into a progressive project system. By starting from the basics and gradually becoming more difficult, it helps students gradually exercise and improve their practical skills. It provides 3 project-level positions and 1 position cluster-level project, for progressive training of different job skills.
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