What is the major of big data science and technology?

Big data science and technology majors mainly study the related knowledge and technology of big data processing and analysis, as well as the knowledge of machine learning, deep learning and artificial intelligence.

1. Basic knowledge of big data

Big data science and technology majors need to learn the basic knowledge in the field of big data, such as Hadoop, Spark and other big data frameworks and their components, understand distributed computing, and be familiar with data storage and processing methods.

2. Data mining technology

Data mining is an important part of big data science and technology, and it is necessary to learn the principles and implementation methods of various data mining algorithms, including clustering, classification, association rule mining, anomaly detection and so on.

3. Machine learning

Machine learning is a widely used technology of big data and an indispensable part of big data science and technology. It is necessary to learn different machine learning models and algorithms such as supervised learning, unsupervised learning and semi-supervised learning, and learn to use TensorFlow, Keras and other frameworks to build neural networks for deep learning and training.

4. Data visualization

Big data science and technology majors also need to master data visualization technology, and present the results of data processing in a graphical way, which is helpful to better understand the data and find anomalies, including statistical charts, three-dimensional visualization, large-screen display and so on.

5. Artificial intelligence

Artificial intelligence has a lot to do in today's era of big data. Big data science and technology majors also need to learn about artificial intelligence, such as causal reasoning, natural language processing and other technologies, and master the combination of artificial intelligence and big data.

To sum up, learning big data science and technology requires mastering the basic knowledge of big data, data mining, machine learning, data visualization and artificial intelligence. Understanding these technologies is helpful to obtain valuable information from massive data and help decision makers make more accurate judgments and decisions by using data-driven methods.