AI is used in almost all the popular automated tools that we created decades ago to improve their performance and make calculated decisions to produce better outcomes. Before starting your journey into AI, it’s important to have a solid foundation in mathematics and computer science. Here are some of the core concepts and skills you should learn:

1.            Mathematics: Linear Algebra, Calculus, and Statistics are essential for understanding the mathematical foundations of AI algorithms.

2.            Programming: You should be familiar with at least one programming language, such as Python, which is widely used in AI development.

3.            Data Structures and Algorithms: Understanding data structures (e.g. arrays, lists, trees, graphs) and algorithms (e.g. sorting, searching, tree traversal) is crucial for implementing AI solutions efficiently.

4.            Machine Learning: Study the basic concepts of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning.

5.            Neural Networks: Neural networks are a fundamental building block of many AI systems, and a solid understanding of their workings is crucial for developing and training AI models.

6.            Natural Language Processing (NLP): If you are interested in developing AI systems that can understand and generate human language, then NLP is an important area to study.

7.            Deep Learning: Deep learning is a subfield of machine learning that uses artificial neural networks to model complex patterns in data. This is an active area of AI research and has produced some of the most impressive results in the field.

AI is a rapidly evolving field, and staying up-to-date with new developments is important for anyone looking to work in the field. Joining online communities, attending conferences, and participating in AI competitions are all great ways to learn and stay up-to-date with the latest developments.