Brief introduction of CDA data analysis training institutions;
1, Shenzhen CDA Data Analysis Training Big Data Class's learning skills of actual combat theory+business project training are more solid, and the learned skills are seamlessly connected with big data positions.
2. Shenzhen CDA data analysis training institution offers Python reptile training, academic quantification training, big data development training, data visualization training, Julia data science training, Stata training, DSGE training, data strategy analysis training, CatBoost training, business strategy training, R language introduction training and other courses.
3. The requirements of enterprises for the Big Data Division have changed from a single special big data capability to a platform-wide big data. The Big Data Division needs to have comprehensive capabilities of big data, big data and mobile python big data.
Taboo points in data analysis:
1, the purpose of data analysis is not clear. When we want to analyze a data, we must first determine our own purpose and why we should collect and analyze such a data. With a clear purpose, we can know what data to collect next, how to collect data and what data to analyze.
2, there is no reasonable arrangement of time. Data analysis should also arrange time reasonably. Generally, we have several steps: collecting data, sorting out data, analyzing data and beautifying tables. Before doing this, we should estimate how long each step will take, which step is more important, and need more time. This should be planned before starting to collect data.
3. Re-collection and light analysis. Many students made such mistakes in training. It took three weeks to complete this task, but it took more than two weeks to collect data. Finally, there was basically no time to analyze, so I rushed to hand in an unanalyzed data.