1, Enterprise Win Training College:
The enterprise wins the advantages of the training college, and the case of the enterprise itself is combined with the case of the industry benchmark enterprise, and the lecturer gives a targeted explanation; Summarized the R&D practice and product management experience of R&D enterprises for many years, and the course system was comprehensive. Introduction of specific tools and methods from market demand to product planning; Practice in group mode and experience the application of the above tools in market demand analysis and product planning.
2. Chanz Podcast Training College:
Chanz Podcast Training College holds the "National Training for IT Key Teachers in Colleges and Universities" every summer, and exclusively undertakes the "National Training Course for Key Teachers in Information Technology Shortage Projects (Software Development and Application)" organized by the Software and Integrated Circuit Promotion Center of the Ministry of Industry and Information Technology. * * * 6 17 teachers from 195 colleges and universities participated in the training.
3. Training institutions for product manuals:
The training institution of product manual data has a completely real teaching system of internet corporatization, and BAT product experts (positions higher than the director) are taught face to face all day, providing all-round guidance on dry goods and actual combat experience, and training product managers in specific directions according to their actual work experience.
Product experts teach in person, which is interactive and can attract product knowledge more quickly; Full-time study five days a week, lasting study, and all-round improvement of product comprehensive ability; 15 arrange students to attend classes every semester, with excellent classes in small classes, and train each student more pertinently.
4. Pass on a big data training institution:
Sichuan Instrument Big Data Training College has a complete set of theoretical teaching materials and project practice manuals independently developed, as well as a perfect project management system and a large-scale open online course online teaching platform. Under the guidance of such perfect academic precipitation, thousands of people have been successfully employed and recognized by many well-known enterprises in the province;
It has successively signed strategic cooperation with well-known enterprises such as Star Network Ruijie, NetDragon, Ruineng, Malata, Cigna, Xoceco, Asia News, Julong, etc., and implemented internal training for employees of many large enterprises such as NetDragon, China Post, Yili Technology and Hitachi Group. The high-quality teaching team ensures the high-level and high-quality teaching of Sichuan Instrument Technology.
5. Dark Horse High-end Big Data Training Institution:
Dark Horse's high-end big data training institutions have established their own universities and created a set of educational ecological chain covering basic education, vocational education and continuing education in primary and secondary schools, which fundamentally solved the problem of systematic education and training with "people" as the unit, from initial enlightenment education to vocational application education in adulthood.
Extended data:
Skills requirements of data analysts:
1. Understand the business: the premise of data analysis is to understand the business, that is, to be familiar with the industry knowledge, the company's business and processes, and it is best to have your own unique opinions. If it is divorced from the industry cognition and the company's business background, the analysis result will only be an off-line kite with little use value.
2. Understand management: on the one hand, it is the requirement of building a data analysis framework. For example, to determine the analytical thinking, we need to use theoretical knowledge such as marketing and management to guide. If you are not familiar with management theory, it is difficult to build a data analysis framework, and subsequent data analysis is also difficult. On the other hand, the function is to put forward guiding analysis suggestions for the conclusion of data analysis.
3. Understand analysis: It refers to mastering the basic principles of data analysis and some effective data analysis methods, and being able to flexibly apply them to practical work, so as to effectively analyze data. The basic analysis methods are: comparative analysis, grouping analysis, cross analysis, structure analysis and funnel diagram analysis;
Comprehensive evaluation analysis, factor analysis, matrix correlation analysis, etc. Advanced analysis methods include: correlation analysis, regression analysis, cluster analysis, discriminant analysis, principal component analysis, factor analysis, correspondence analysis, time series and so on.
4. Understanding tools: refers to mastering common tools related to data analysis. Data analysis method is a theory, and data analysis tool is a tool to realize the theory of data analysis method. Faced with more and more huge data, we can't rely on calculators for analysis, but must rely on powerful data analysis tools to help us complete data analysis.
5. Understanding design: Understanding design refers to using charts to effectively express the analysis views of data analysts, so that the analysis results are clear at a glance. The design of charts is a big problem, such as the choice of graphics, layout design, color matching and so on. These all need to master certain design principles.