Top 5 in-demand AI Skills to boost your career beyond 2023

Companies from all industries have optimized their business operations by leveraging artificial intelligence. Few industries like manufacturing have incorporated it so long ago that there are hardly any jobs left for humans. All the processes are done by robots and automated machines. But in industries such as programming and machine learning, the requirement for AI professionals has shot up tremendously as companies require the most efficient and talented people to apply AI in their business processes and increase productivity. And that is why the AI career is one of the most sought-after career options at the current times. If you are also someone that wants to make a career in AI, then here is a checklist of the most in-demand AI skills in 2023 and beyond.

1. Machine Learning

Machine learning is a core component of AI, and it involves developing algorithms and models that can learn from data and make predictions or decisions based on that data. Machine learning includes 7 key steps: Gathering Data, Preparing that data, choosing a model, Training, Evaluation, Hyperparameter Tuning, and Prediction.

As per Glassdoor, the average salary of a Machine Learning Engineer in the United States is $1, 09,127 per year.  And this is one of the must-have AI skills for students aspiring for a career in the field of AI.

There are many AI certification available from top institutes like Harvard, USAII®, MIT, etc. that empowers students with the latest and trending technologies in machine learning.

2. Natural Language Processing

It is again one of the top AI skills in demand and an NLP Engineer earns around $1,12,123 per year in the United States. Natural Language Processing is a subfield of Artificial Intelligence (AI) that focuses on the interaction between computers and humans using natural language. NLP enables computers to understand, interpret, and generate human language. ChatGPT is one of the most trending AI tools of 2023 that is an example of NLP. NLP has numerous applications in various industries, including chatbots, virtual assistants, sentiment analysis, language translation, and speech recognition.

Having NLP skills in AI involves understanding the various techniques and algorithms used in NLP, as well as being familiar with the tools and frameworks used in the field. This includes knowledge of machine learning algorithms, such as Support Vector Machines (SVMs), Recurrent Neural Networks (RNNs), and Convolutional Neural Networks (CNNs), as well as tools and frameworks such as NLTK, SpaCy, and TensorFlow.

3. Computer Vision

Computer Vision enables computers to interpret and understand the visual world. It involves developing algorithms and techniques that allow computers to recognize, analyze, and interpret images and videos. Object detection and recognition, image segmentation, facial recognition, and image and video classification are a few Computer Vision applications in AI.

For example, AI professionals use computer vision to develop self-driving cars that can recognize and interpret road signs and traffic signals or to develop security systems that can detect and recognize faces.

4. Robotics

Robotics involves combining various technologies, such as sensors, actuators, and control systems, with AI algorithms to enable machines to perceive, reason, and act in the physical world. Some of the applications of robotics in AI include industrial automation, medical robotics, and autonomous vehicles. Having robotics skills in AI involves understanding the various technologies and algorithms used in robotics, as well as being familiar with the tools and frameworks used in the field.

This includes knowledge of control systems, and machine learning algorithms, such as Reinforcement Learning and Deep Learning, as well as tools and frameworks such as ROS (Robot Operating System), OpenCV, and PyTorch.

Robotics is an important AI Skill because it enables machines to interact with the physical world in a natural and intuitive way, which is essential for developing AI solutions that can perform real-world tasks autonomously.

5. Python

Python is a widely used programming language for AI, thanks to its simplicity, ease of use, and vast library of AI-specific frameworks and tools such as TensorFlow, Keras, and PyTorch. Python is used for developing machine learning models, natural language processing, and computer vision applications.

Almost all the artificial intelligence certification that students enroll in to advance their AI career includes Python in their course and exams.

Conclusion

Artificial Intelligence is a highly fascinating field that is disrupting the way we live, work, and interact with technologies. Possessing credible artificial intelligence certification ensures that you have relevant skills and knowledge to demonstrate your expertise in the field of AI. Apart from these technical skills, consider upgrading yourself with the knowledge of R, MATLAB, and some business skills like domain knowledge, communication skills, and project management. And then the ladder to success will look small. So, all the best.