The global revenue of artificial intelligence (AI) software in 2022 was forecasted to reach $62.5 billion, experiencing a 21.3% increase from the previous year, according to a Gartner report. This shows no sign of slowing in coming years as AI becomes increasingly ingrained across industries. As such, the demand for skilled professionals in AI will continue to rise. In fact, the global AI market is expected to rise to £360 billion by 2028! But what AI skills do you need to land your dream job and make your mark in the booming industry?
What are AI skills?
AI skills refer to the competencies and knowledge required to develop, implement, and manage artificial intelligence systems and applications. Thes skills encompass programming, machine learning, data analytics, maths, ethical considerations, and more. These are essential skills required for professionals working in the field of AI, or even those who use AI on a daily basis within their role.
10 Top AI skills to learn
- Programming languages
- Data modelling and analytics
- Machine learning and deep learning
- Libraries and frameworks
- Mathematics and statistics
- Natural Language Processing (NLP)
- Critical thinking
- AI ethics
1. Programming languages
Proficiency in programming languages, such as Python, R, and Julia, is essential for AI professionals. These languages serve as the building blocks for AI development, facilitating the creation of algorithms, data manipulation, and the implementation of AI models. If you’re interested in learning how to code, there are plenty of AI roles at your fingertips, such as Machine Learning Engineering, AI Software Development, Data Science, and much more!
Python has been identified as the most in-demand programming language for AI. Learn more about all the reasons you should learn Python!
2. Data modelling and analytics
As AI continues to grow and play an increasingly pivotal role in various industries, the demand for data modelling is surging. A deep understanding of data modelling and analytics is crucial as AI algorithms rely heavily on high-quality, structured data for effective learning and decision-making. This AI skill involves the collection, cleaning, and interpretation of data, enabling organisations to make data-driven decisions and construct accurate AI models. Proficiency in tools like SQL and data visualisation platforms is also vital.
3. Machine learning and deep learning
Machine learning constitutes a substantial domain within the AI landscape, encompassing the majority of AI software and initiatives. Projections indicate that this market is poised for significant expansion, with anticipated growth from approximately $140 billion to nearly $2 trillion by the year 2030. These figures are a clear indication that professionals in this area are set to be one of the most in-demand in the coming years. So, a mastery of machine learning techniques, including supervised and unsupervised learning, as well as deep learning, like neural networks, is essential. These techniques underpin the development of AI systems that can learn from data, make predictions, and solve complex problems.
4. Libraries and frameworks
Familiarity with AI libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras streamlines AI model development and deployment. These tools offer pre-built functions and structures that expedite the development process and ensure the efficient implementation of AI solutions. With many businesses looking to prioritise efficiency, and libraries and frameworks being essential for this, candidates who possess these skills will be highly desirable,
5. Mathematics and statistics
Mathematics and statistics are not just in-demand skills but are fundamental to problem-solving, innovation, and success in AI-related positions.
A strong foundation in mathematics and statistics is fundamental to understanding and optimising AI algorithms. Concepts like linear algebra, calculus, and probability theory are crucial for grasping the inner workings of AI models and for making informed decisions during model development.
6. Natural Language Processing (NLP)
The Natural Language Processing (NLP) market is anticipated to experience substantial expansion, with its global market size forecasted to increase from $24.10 billion in 2023 to a remarkable $112.28 billion by 2030. Proficiency in Natural Language Processing (NLP) techniques is vital for building applications that can understand, interpret, and interact with human language. This includes sentiment analysis, named entity recognition, and the development of chatbots and virtual assistants, among other applications.
Landing a job in AI is not all about your technical or ‘hard’ skills. In fact, soft skills are just as important. For example, AI professionals encounter unique challenges and uncertainties during model development. Problem-solving skills are crucial for identifying and addressing these issues, adapting to changing circumstances, and optimising AI systems to perform effectively in real-world scenarios.
8. Critical thinking
Critical thinking skills are indispensable in the AI field. Professionals must critically assess AI models for biases, fairness, and ethical considerations. They also use critical thinking to make informed decisions about model selection, feature engineering, and hyperparameter tuning to ensure the best AI performance.
According to Pearson, critical thinking is actually one of the most sought-after skills across employers in all industries. So, whether you’re looking to get started in AI or any other field, critical thinking should be on your radar!
Creativity is not just a skill for ‘creative’ fields. In fact, creativity plays a significant role in AI, enabling professionals to devise innovative solutions and explore novel applications. AI experts often need to think outside the box to create unique AI-driven products, services, or experiences that solve complex problems and meet the evolving needs of industries and society.
Since new AI advancements are always taking place, when working in an AI role, creativity is valuable for pushing the boundaries of what AI can achieve, solving unique AI-related problems, and staying at the forefront of technological advancements in artificial intelligence. Creativity is key for businesses that want to stay ahead of the game!
10. AI ethics
As ethical concerns surrounding AI continue to grow, understanding AI ethics is paramount. AI professionals must consider the ethical implications of their work, including issues related to bias, fairness, transparency, and privacy. Ensuring responsible and unbiased AI development and deployment is not just a technical concern but a moral and societal obligation in the AI industry.
AI skills are the linchpin of innovation and progress in the ever-evolving world of artificial intelligence. Making your entrance into a career in AI means contributing to the reshaping of industries as we know it, and improving the lives of many. Don’t get left behind - there couldn’t be a better time than now to start developing your AI skills!
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