Top 5 Desired Skills For Artificial Intelligence Jobs in 2020

The demand for advanced tech skills is rising in every organization and industry. As we are becoming a digitized society, the need for Artificial Intelligence (AI) professionals has also sky-rocketed. More and more companies are investing in recruiting and nurturing those who fit the AI skills bill, to remain a part of the global competitive market.


Educational Background for Artificial Intelligence Jobs

If you belong to the computer, technology, or mathematics educational field in school, then foraying into AI will not be a difficult transition. You should have in-depth knowledge about probability, statistics, calculus, algorithms, etc. in mathematics. Along with that, you should know about bayesian networking, graphical modelling, neural nets, robotics and engineering, programming languages and coding, etc.

For jobs at an entry-level, the requirements are limited to a bachelor’s degree, but leadership roles require master’s or doctoral degrees. You could also pursue an AI specialization or an AI certificate program if you’re short on time to acquire any educational qualifications.


Skills Required for Artificial Intelligence Jobs

As an AI professional, the skill set you carry with yourself will make all the difference in getting hired. Here are the top 10 AI skills that you should possess for the best opportunities.



  • Machine Learning


Machine learning(ML) is a subdivision of artificial intelligence. In ML, you learn to study algorithms and statistical models that computer systems are using to perform a particular task. In ML, the system functions without explicit instructions. Instead, it relies on patterns and inferences. Machine Learning also has three separate focus areas.

1. Supervised Learning – As the name suggests, in supervised learning training datasets are spoon-fed to the system. Supervised learning algorithms then analyze this data and produce an inferred function. This solution can be used to map further data sets.

2. Unsupervised Learning – In unsupervised learning, the data given to the system is unstructured. The purpose of unsupervised learning is that the machine will have to learn without supervision.

3. Reinforcement Learning – With the help of reinforcement learning, an algorithm can determine the idealistic result expected in a specific context. It is through a process of trials and fails that the algorithm improves itself depending on the interaction with the incoming data.

Applications of Machine Learning as an AI skill

  • It is used for online fraud detection.
  • Read medical diagnosis patterns.
  • Improves cybersecurity.



  • Python


Python is an advantageous and robust programming language that is based on Object-Oriented Programming. It focuses on Rapid Action Development (RAD), hence it is a favourite choice for developers. It can be used to design mobile application projects or web application projects. One of the vital qualities of Python is that it has very few keywords, a clearly defined syntax, and a simple structure. Thus, it is easy to maintain and can be integrated with any other programming language like Java, C, or C++.

Python maintains the same interface on all platforms, thus can be used on a variety of them.


Applications of Python as an AI skill

  • It is used for prediction.
  • Aids in Heuristic classification.
  • Improves security surveillance.



  • Java 


Java is one of the most popular programming languages with the feature of public-key encryption. It is considered to be an object-oriented, general-purpose programming language that works on multiple platforms. A significant part of its syntax finds its roots in C and C++. Java is quite powerful, fast, and secure at the same time. Another feature of multithreading in Java allows written programs to perform different tasks simultaneously. Debugging is also quite comfortable in this programming language. Moreover, Java focuses on compile-time error checking, ensuring the elimination of error-prone situations.


Applications of Java as an AI skill

  • Ease in designing chatbots
  • Allows data-filtering
  • Has Natural-Language processing



  • Data Science


Data science is closely linked to data mining and big data. It is an interdisciplinary field that uses scientific processes and algorithms to make sense of data in different forms. Knowledge of data science allows AI to spot patterns and trends from structured and unstructured data more efficiently.

Having a good grasp of data science is essential to develop data products in any organization. This means algorithms have to be developed, tested, refined, and technically deployed into the production systems as well.

Applications of Data Science as an AI skill

  • Enhanced Speech Recognition
  • Contributes in Development of Virtual Assistants
  • Supports Robotic Process Automation (RPA)



  • R Language

R is a programming language and environment for statistical computing and graphics. It specializes as a statistical software useful for data analysis, data visualization, and well suited for statistics in general. Another benefit of working with R is that it provides graphical tools for data analysis, which is very useful in monitoring user experience on social media. Having said that, R, too, supports object-oriented programming but not as preferred over Python. R is a multi-paradigm, dynamically-typed, scripting, procedural, and interpreted language. It has data storage and an excellent data-handling facility as well.

Applications of R as an AI skill

  • Improved Offline Experiences
  • Secure Social Media
  • Finer Email communications


Since the development of artificial intelligence from its early stages in the 1950s to today, AI is constantly growing to improve and advance the quality of life across multiple sectors and industries. Some of the most sought after AI jobs are that of Machine Learning Engineers, Artificial Intelligence Developer, Research Scientists, Algorithm Specialists, etc.

Artificial Intelligence has paved the way for the exceptional quality of accuracy with the help of neural networks. The skills mentioned above are core to the development of AI-based projects. So if you’re someone who enjoys translating digital information into meaningful human experiences with the help of technology, this might just be ‘the field’ for your interests!


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