To enter the everchanging field of artificial intelligence and data science, you need to familiarize yourself with what it takes to become a competitive specialist. In this article we will cover the hard skills, job offers, and internship positions you should pursue to boost your candidacy in the sphere of data and artificial intelligence.
According to the World Economic Forum report on the jobs of tomorrow, artificial intelligence will show one of the biggest increases in numbers of opportunities in 2020-2022. In this series we discuss ways you can enter the job market in the field of your interest with the help of internships, scholarships, and new skills gained through online courses.
The Link between Big Data and Artificial Intelligence
The word “data” can be used in many contexts, meaning facts stored in our memory or videos on a computer. In the context of computer science, data can be in the form of different types of information that is usually formatted in a certain way. You need to interpret data for it to become information.
When we talk about big data, we mean large, diverse sets of information that grow at an increasing rate. Such information can be collected from social media sources and websites that help organizations to understand customer needs. There are characteristics of big data that are described as “Five Vs”: value, variety, volume, veracity, and velocity. These characteristics allow industries – e.g.: eCommerce – to build business models based on the use of big data.
Artificial intelligence or AI is a branch of computer science that oversees the creation of smart machines that can perform tasks that have traditionally required human intelligence. AI and big data greatly complement each other as AI becomes better as it takes in more data. Data requires the use of complicated software in order to be processed; and, thus, machines are much more efficient in analyzing it. Alex Melnichuk, an author at ncube, has provided a succinct explanation of how AI uses big data:
- AI receives data
- AI gets smarter because of the data
- AI requires less human interaction
- AI requires fewer people to run it
- AI feeds new data to itself
Who Are AI Specialists and Data Scientists?
AI specialists program computers to “think”. They may work on creating a computer program to allow computers to recognize faces and fingerprints, solve problems, and interpret information. Data scientists also make value out of data. Such professionals collect information from various sources and analyze it to understand business’s performance or to automate processes within the company.
An AI specialist should have a strong background in programming and fluency in multiple computer languages. Most of senior positions require a Master’s degree in computer science while candidates with a BSc degree are eligible for some entry-level jobs. Here are some of the hard skills that will enrich the skill set of an AI specialist:
- Data Science
- Data Storage Technologies
- Development Tools
- Artificial Intelligence
- Software Development Life Cycle (SDLC)
- Management Consulting
- Web Development
- Digital Literacy
- Scientific Computing
- Computer Networking
To have a better understanding of the requirements and job conditions you will need to consider, let’s have a look at some of the job openings in the field of cloud computing.
Emerging Cloud Comping Jobs
Emerging professions in cloud computing are those that have experienced the most growth over the previous five years. To arrive at these conclusions, LinkedIn and Burning Glass Technologies have tracked the number of job openings posted in digital job boards and the number of professionals who are hired into new opportunities. Here are a few openings in the field:
Additional experience that you gain throughout your studies will demonstrate your work readiness to potential employers. To do that, consider applying for an internship or taking part in a computer science competition. Here is a taste of the opportunities you may look into:
Google offers internships across EMEA in either Software Engineering or Site Reliability Engineering. As a key member of a versatile team, you will design, test, deploy, and maintain software solutions. Applications for 2021 internship opportunities will open in the fall of 2020. Candidates should be currently enrolled in a PhD degree in Computer Science or a related technical field. Coding experience in one of the following programming languages is required: C++, Java, Python or Go.
The Challenge brings together key stakeholders from the mobile industry and universities’ artificial intelligence and data science departments. Teams of 8-12 PhDs/AI researchers and the participating companies will collaborate and model future outcomes enabling better understanding of complex data and associated industry challenges. The Challenge is open to all organisations from across the mobile industry.
Data and AI Additional Learning Priorities
Data scientists at Coursera have looked at the learning activities of individuals employed in emerging professions and have created a list of distinctive priorities for upskilling in those fields. Here are the top courses to take as a supplement for anyone employed in data and AI professions:
In this four-course Specialization, you’ll explore exciting opportunities for AI applications by developing an understanding of how to build and train neural networks. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Additionally, you’ll learn to process text, represent sentences as vectors, and input data to a neural network, all to train AI to create original poetry!
This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. The program consists of nine courses providing you with the latest job-ready skills and techniques including: open source tools and libraries, methodologies, Python, databases, SQL, and more.
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision, and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience in solving real-world problems and will help you to fill the gaps between theory and practice.
This specialization from the University of Michigan introduces learners to data science through the python programming language. This course is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques.
Some positions in the field of artificial intelligence require professionals to have an understanding of complex computer science concepts and a background in psychology or natural sciences, which makes AI a great platform for experimentation and interdisciplinary skill transfer.
Photos: Shutterstock / Photomontage: Martina Advaney
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