Where is it better to learn big data?

The key to participating in big data training courses is to choose the right training institutions, such as curriculum settings, teachers, training projects, hardware facilities (cluster servers), employment rates, etc. There are many talents from reliable training institutions and good employment opportunities, mainly related to personal learning effects, ability and quality, such as whether they master real big data technology, what is their academic qualifications, communication skills, thinking skills, etc.

Within your time and budget, you should clarify your own needs and find a training institution that suits you, and learn targeted learning with goals, in addition to learning knowledge, you should also learn some problem-solving thinking and ideas. Even if you join a new company after the training, you have to continue to learn, consolidate some computer foundation and foundation, and continue to improve.

If you want to learn big data, it is recommended to go to the CDA Data Certification Center, which is the abbreviation of data analysis professionals in the era of big data and artificial intelligence for the international scope of the whole industry, specifically refers to the new type of data talents who specialize in data collection, cleaning, processing, analysis and can make business reports and provide decision-making in the Internet, finance, consulting, telecommunications, retail, medical, tourism and other industries.

Now big data is more popular, there are many people who want to learn big data development technology, and they don't have much programming foundation, they feel that they are not suitable for self-learning big data, and they are afraid of stepping on the pit when they choose a big data training institution

1.Employment rate and study cycle.

In order to be able to better find employment, partners should make a careful investigation and understanding of the authenticity of the employment information displayed by the training institution in the process of choosing a training institution.

Generally, the learning cycle of reliable big data training institutions is about 5-6 months, if the learning cycle of the training institution is too short during the inspection, it is likely to compress the course, and such institutions are still recommended to choose carefully.

2.Mobility of trainers and course content.

For the mobility of teachers in big data training institutions, if an institution changes a teacher every once in a while, the teaching of such an institution will definitely not be good, after all, each teacher's teaching method is different, and the students will change teachers as soon as they get used to it, so that in the whole learning process, the students have to re-adapt to the teaching methods of the new teachers, so that the students will not learn well. The stability of the teachers of a reliable big data training course is very important, which is also an important factor to highlight the faculty of the training institution.

In terms of the content of big data training courses, we must carefully investigate, after all, this is the real thing that can be learned, one looks at the knowledge points covered by the course syllabus, and the other is to see whether the actual project is an open enterprise project, and whether the students have a public graduation project. This is of great help to the partners to choose a systematic and complete course content system, and at the same time, the partners can also learn the technical knowledge of programming and development with high gold content.

3.Teaching mode.

Now there are more big data training institutions on the market, and the related teaching modes are also different, and there are generally several teaching modes on the market: offline teaching, online courses, ** teaching, and ambidextrous. Among these teaching modes, the offline teaching mode is a training mode with a wide audience and better learning effect, and the training institutions with strong teaching ability generally adopt the offline teaching mode.

It is recommended that you can judge from a number of aspects:

1. Employment rate.

2. Faculty team.

3. Practical training projects.

Fourth, the enrollment threshold.

5. On-site audition.

Welcome to Henan Xinhua to visit and learn about computer technology, free trial courses, and reimbursement of travel expenses.

The concept of big data originally originated in the United States, and was developed by the initiative of Cisco, Veritage, Oracle, IBM and other companies, and has reached its current locationBig data technology still needs to be on par with North America.

The recommended major is North American big data, and the instructors have a team of experts from North America to bring cutting-edge technology courses, and the colleges and universities include: Classroom Workshop, Nanjing Peking University Jade Bird, Zhongbo Software College, etc. It is recommended that you take a field trip.

The key to this big data, do you have a foundation in the network computer, if you don't understand anything, you can start with the basics, of course, from some schools, go to your school.

The data collection, which is mainly characterized by large capacity, multiple types, fast access speed and high application value, was first applied to the IT industry, and is now rapidly developing into a new generation of information technology and service formats that collect, store and correlate data in a huge amount, scattered and diverse formats, and discover new knowledge, create new value and enhance new capabilities. Big data must adopt a distributed architecture to carry out distributed data mining on massive data, so it must rely on the distributed processing, distributed database, cloud storage, and virtualization technology of cloud computing.

1.Compare the campus environment, teachers, facilities and equipment, practical courses, etc., I hope you will study in a good school and win a good future! If you are professional, you can choose to be interested in automobiles, and if you like cars, you can choose automotive new energy and intelligent networking major or computer graphic design; If you are a girl, you will be able to do it.

1.See if the school's qualifications are regular! Is the equipment perfect?

What is the scale of the school? The school's social reputation, investment in teaching facilities and equipment, teachers' qualifications, student employment rate and other related aspects were investigated. It is more beneficial for the future development of the individual.

2.With the increasing number of cars in China and the deepening of reform and the development of high-tech intelligence and automation, the rapid development of the auto repair industry in recent years. You can learn courses such as automobile maintenance, automobile inspection, automobile circuit, beauty decoration, second-hand car identification and evaluation, new energy vehicle inspection and maintenance, etc.

3.From the perspective of digging under several aspects to investigate and compare, qualifications, whether there is a school license approved by the ** department.

The equipment, whether the jujube is complete, whether it is really used for practical training. Judge blind shouting.

management, whether the safety management of campus guards is strict, students are civilized and polite, campus environmental hygiene, etc.

strength, the number of teachers, the level of education, practical experience, teaching level, etc.

Process, observe the order of the class, the state of the students, whether the students are doing the operation, and whether the operation process is standardized.

Now is the era of big data, and many people want to pursue a career in big data. What is the main learning of big data?

Basic stage: Linux, Docker, KVM, MySQL foundation, Oracle foundation, MongoDB, and Hadoop:

Hadoop concepts, versions, history, how HDFS works, introduction to yarn, and components.

Big data storage stage: HBase, Hive, and SQOOP

Big data structure design stage: Flume distributed, zookeeper, and Kafka

Real-time computing stage of big data service failure: mahout, spark, and storm

Big data collection stage: Python, Scala

Big data business practical stage: practice enterprise big data processing business scenarios, analyze requirements, solution implementation, and comprehensive technology practical application.

Big data (bigdata, mega, data) or large amounts of data refers to large-volume, high-growth, and diversified information assets that require new processing models and stronger decision-making, insight, and process optimization capabilities. In The Age of Big Data, written by Victor Meier Schönberg and Kenneth Kukye, big data is not a shortcut to stochastic analysis (sample surveys), but uses all data for analysis and processing. 5V Characteristics of Big Data:

volume, velocity, variety, value, veracity

The 5 Vs or characteristics of big data are:

First, the volume of data is huge.

The difficulty is certain, the key is to see whether you work hard or not.