Artificial Intelligence (AI) is the intelligence shown by machines or computers. AI research involves the process of programming a computer that is capable of replicating the intelligent behavior shown by human beings. AI-powered machines can learn just like humans and make decisions for themselves. An AI-powered smart and intelligent computer system is capable of understanding complex tasks and executing complex commands. If you are looking to pursue a career in artificial intelligence, you need to learn the in-demand artificial intelligence skills.
There is a great demand for skills required for artificial intelligence in the AI industry. AI companies are looking for individuals who have artificial intelligence skills. Moving forward, businesses will continue to recognize the benefits that AI skills will provide to their organization.
Here are the most in-demand artificial intelligence skills that AI companies are looking for in their organization.
Programming skills
- It is impossible to imagine a career in AI without knowledge of computer programming languages.
- Be it artificial intelligence or any other field, computer programming languages are the mainstay of the software and apps that we use.
- With programming languages, an AI engineer can communicate with the computer by writing code and creating programs.
- An individual who wants to pursue a career in artificial intelligence must have sound knowledge of various programming languages such as Java, JavaScript, C++, R, Python, etc.
Java
It is a commonly used server-side programming language used by developers for AI.
JavaScript
It is a popular programming language used by developers in ML libraries such as TensorFlow.
Python
It is a widely used programming language in both AI and ML. With Python, AI engineers can write complex algorithms with minimal coding.
R
This programming language allows AI professionals to perform statistical computation, numerical analysis, and gather and organize data sets. Both AI and ML involve plenty of data. R is a popular programming language for statistics and complex calculations.
C++
It is a low-level programming language for creating simple AI models. It offers quick execution and less response time.
Frameworks and libraries
Developers involved in creating AI apps have different frameworks and libraries to choose from. They are used for exploring large data sets, performing numerical operations, scientific computing, etc. It is also possible for developers to use the libraries to write code quickly and accurately.
Some of the popular frameworks and libraries include:
- TensorFlow
- Apache Spark
- Seaborn
- NumPy
- Keras
- Matplotlib
One of the most in-demand skills for the future is to have knowledge of different libraries and frameworks, especially the recent ones.
Mathematics and Statistics
AI machines learn from experience and the data sets used in training. Computers and machines need to be programmed to understand and apply logical reasoning. Mathematics involves the study of patterns and correlations between numbers. Statistics involves how to collect, analyze, and interpret data.
Mathematical and statistical concepts for AI
- Probability
- Algebra (basic mathematical operations)
- Linear algebra
- Graphs
- Differential calculus
- Random variables
- Basic statistics
Machine Learning and Deep Learning
- Both machine learning and deep learning are fields of computer science that are growing rapidly.
- Both involve training the computer to interpret data and learn from it without being explicitly programmed.
- Machine Learning allows computers (machines) to mimic human intelligence by learning from experience and adapting to different situations.
- Deep learning is a subset of machine learning based on neural networks that enables more in-depth learning of the machine.
Natural Language Processing (NLP) and computer vision
- NLP involves the use of computers or machines to interpret human language for the purpose of performing certain tasks.
- In the world of AI, NLP is used to perform different tasks such as speed recognition, automatic summarization, text summarization, topic categorization, understanding word meanings, etc.
- Computer vision is a subset of ML that allows computers to process, analyze, and interpret the digital world. Its applications include face recognition, image classification, object detection, and 3D geometry prediction of objects in images.
Data Science and Data Analytics
Data is an integral part of any business or field in today’s world. Data Science and Data Analytics are key artificial intelligence skills that help organizations understand customers and their needs, and make better decisions based on that interpretation and understanding. Data Science finds out large-meaningful correlations in large datasets. Data analytics refers to the examination of data sets to draw valuable conclusions (actionable insights) from large datasets to solve business problems.
Non-tech skills for AI professionals
- Critical thinking
- Love for math and science
- Natural curiosity
- Problem-solving approach
Keeping in mind all the enthusiasm and buzz surrounding AI, the most in-demand skills for the future are crucial to success in this field. Artificial intelligence skills are indispensable to pursuing a career in artificial intelligence. Organizations are looking to utilize AI skills to improve their business operations. Hence, there is a huge demand for artificial intelligence skills in the market. If you have the skills required for artificial intelligence, you will definitely find new opportunities in the market. If you are already in the AI industry, you need to upskill yourself since the skills required for AI jobs are rapidly evolving. For a successful career in artificial intelligence, you need to be aware of the latest AI capabilities, tools, and technologies. If you have knowledge of artificial intelligence skills, you will be in a great position to have a successful career in AI.