For reliable big data analysis training institutions, lecturers are the core competitiveness. The lecturers of Halo Big Data are frontline developers with many years of practical experience and have rich project experience in the Internet industry. They understand the skills that enterprises need most and the most popular development frameworks. The teaching mode of all trainers is not scripted, but combined with practical application.

2. Frontier courses

Internet technology update iteration is very fast, and big data analysis technology is inevitable. Before studying, you can learn about all aspects of the big data analysis course through professional channels and compare them to see if they are reasonable. Beware of learning outdated and outdated technologies. The big data course is divided into 13 stages, 90 modular courses and 6 real projects of large enterprises. At each stage, there are strength cases and project portfolios, which lead students from simple to professional, step by step into the world of big data development, and help students successfully embark on the road of big data engineers!

3. Standard admission criteria for students

Formal training institutions must have certain screening principles for applicants, instead of "refusing to come" and paying for it. Screening is not only the basis of examining students, but also a comprehensive evaluation and test of students' logical thinking, learning ability, learning attitude, learning desire and major to determine whether it is suitable for learning big data analysis.