5 Must-Haves On Your Artificial Intelligence Resume - Great Learning

5 Must-Haves On Your Artificial Intelligence Resume

Robots, self-driving cars, and chatbots have swapped man for machine with artificial intelligence (AI). At the same time, they have created a huge marketplace for a diverse range of job roles with varying skill sets. While traditionally, analytics job roles required applicants with statistics or math background, the increased use of computation and sheer volumes of data now demand technical knowledge. So whether you are an engineer wanting to make your mark in an AI-driven environment, or a data analyst seeking to make a career in AI, you need to have certain core competencies.

These are the top 5 must-haves on your AI resume:

1. Languages – Java, Python, C, and C++

High-level object-oriented programming languages such as Java, Python, C, and C++ are languages navigated by most engineers during the course of their education. However, if you have come to data science from statistics or a non-engineering background, you need to learn these languages basic to AI. At the same time, learning server-side scripting languages such as PHP, ASP, JSP, Ruby or Perl is of immense use.

Learning any or all of these is not very time-consuming. You can easily learn them online, use their libraries to practice projects, or take short certificate courses. At the end of the day, the more languages that feature on your resume, higher the chances of your CV being considered.

2. Artificial Intelligence Competencies

Fuzzy Logic, Neural Networks, Cognitive Computing, Natural Language Processing (NLP), Data Analysis and Search technologies, APIs, enterprise architecture and security architecture; are some technological underpinnings of AI. Learning or mastering any of these will take you a step further towards landing a job role in AI. Each of these tools and technologies has applications in various scenarios or problem-solving. So wait no more. Go ahead and learn these AI skills-sets to score higher in the job application process. As your knowledge is expected to bring value to the company, you are more likely to be selected with these competencies on your resume.

AI jobs require a blend of expertise and skills in programming, data management, technology platforms and business development. However, these traits continue to be in short supply. So developing a balance between these skills in demand and work experience with computer science disciplines; enhances your prospects of getting the AI job you covet.

3. Machine learning

A part of AI, machine learning is increasingly considered indispensable for trends-spotting and iterative self-learning. With every industry applying AI, machine learning expertise is highly sought after. Its wide range of cutting-edge applications, emerging areas of machine learning-as-a-service, and applications overlapping with AI; have made it central to data-driven hiring. A study of machine learning can help you get a good job in companies leveraging machine learning and AI in their business intelligence process.

So look out for an institute in your city that trains you in machine learning, and provides expert help to train you on projects. Your machine learning certification will surely be a feather in your cap and lay the foundations of your AI career graph.

4. Computer Science, Programming Languages, and Coding

Engineers and specialists in AI require technical skills for designing, maintaining and repairing technology and software programs. Understanding your data, open source frameworks, computing platforms, supporting programming languages and coding; ultimately help you prepare for the rapid pace of technological innovation in data-driven insights. For instance, AI platforms like Microsoft Azure require knowledge of cloud, machine learning, and custom R or Python coding, while TensorFlow open source library requires deep knowledge of architecture.

As AI is a way of making the machine or software, intelligent, it is a foregone conclusion that degrees or certifications in computer science disciplines or tools are a plus factor for any AI resume.

5. Physics, Engineering, Robotics

As a student with a science or engineering background, physics, and engineering applications will be the mainstays of your knowledge-base. However, learning AI based add-on courses will strengthen your foundations in math, logic, and engineering. For instance, knowledge of sensors is a sought-after talent for its various applications of AI.

With AI robots being used across industries, like logistics and manufacturing, a short course on robotics enhances your Artificial Intelligence resume. Companies always look for multi-talented multi-functional professionals who can work across technologies and platforms, and grow in sync with the company visions. So the secret here is to look around and understand the industries and businesses implementing AI and the various use cases. Find which among these interests you and set about learning the tools that contribute to your resume, when you apply for the target job role.


While the technical skills on your resume will surely land a good job in Artificial Intelligence, you cannot ignore the supporting written and verbal communication skills that are needed to convey how the AI tools and services are deployed within the business or industrial processes.

So learn the technologies and programs required for an artificial intelligence job role, during your spare hours or over the weekend and build a great resume that takes you places!

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