1. Mathematical foundation: Many theories and algorithms of AI need a deep mathematical foundation, including linear algebra, probability theory, statistics, calculus and so on. These mathematical knowledge is the basis of understanding and implementing AI algorithm.
2. Programming skills: The development and implementation of AI requires programming skills. Python is the most popular AI development language at present, because it has many libraries and frameworks for AI development, such as TensorFlow and PyTorch. In addition, you need to master some basic algorithms and data structures.
3. Machine learning: Machine learning is an important branch of AI, and its goal is to enable machines to learn from data and make predictions or decisions. Therefore, it is necessary to understand various machine learning algorithms, such as supervised learning, unsupervised learning and reinforcement learning.
4. Deep learning: Deep learning is a subset of machine learning, which attempts to simulate the working mode of the human brain and learn and predict through neural networks. Therefore, it is necessary to understand the working principle of neural network and how to train and use deep neural network.
5. Data processing: A large amount of data needs to be processed during the development of AI. So you need to master the skills of data cleaning, data conversion and data analysis.
6. Problem solving ability: The goal of AI is to solve practical problems. Therefore, it is necessary to have good problem-solving ability and be able to apply theoretical knowledge to practical problems.
7. Soft skills: In addition to technical knowledge and skills, you need to have some soft skills, such as communication skills, teamwork skills and project management skills.
Generally speaking, AI is a field that needs profound technical foundation and extensive knowledge, but as long as you are interested and persistent, you can master this knowledge and skills through study and practice.