1. Self-study: It requires strong self-discipline and the ability to choose learning materials and contents. Otherwise, the efficiency will be very low, so we must make a study plan and implement it according to it.
Including the time to submit your resume, the time to join the company and so on. Give yourself a plan. Otherwise, it is easy to slack off. You can get information through official WeChat accounts of some industries, websites related to data fields, Zhihu and Bili.
2. Class registration: the efficiency will be higher, the harvest will be quick, and it will be integrated into the data circle to obtain more resources. Let yourself have a better development path planning.
However, the choice of institutions should be very cautious to avoid falling into the pit. We can make a comprehensive evaluation from the aspects of teaching staff (whether the lecturer is on the job, remember that the lecturer is an armchair strategist), course practicability (with actual combat and real database) and workplace support (supporting according to the personal background of urban genes to avoid so-called guaranteed employment).
Finally, we must make a career plan for ourselves, understand what skills data analysts at different levels should master, think clearly about their future target positions, constantly learn and improve themselves, and then move towards the goal step by step.
For information about data analysis, please consult CDA(Certified Data Analyst), which is the professional abbreviation of data analysis professionals facing the whole industry in the era of big data and artificial intelligence. Specifically, it refers to a new type of data talent who specializes in data collection, cleaning, processing and analysis, and can make business reports and provide decision-making in the Internet, finance, consulting, telecommunications, retail, medical care, tourism and other industries.