AI jobs trends to Watchout in 2021
Increasingly, businesses are moving to artificial intelligence and machine learning. These technologies are proving to be the go-to technologies for businesses to improve business efficiency and productivity. Banking, public safety, healthcare, and nearly every other sector is either in the planning or implementing phase of artificial intelligence.
The reliance on artificial intelligence and related technologies among companies is increasing. According to an IDC report, three – quarters of commercial enterprise applications could lean on AI by next year. Another Analytics Insight report projects more than 20 million available jobs in artificial intelligence by 2023.
Growing demand for AI professionals
As businesses increasingly realize the need for AI and AI-powered applications at work, the demand for AI professionals is increasing. Given the transformational nature of AI and ML, specialists equipped with the right skills and knowledge will find themselves with job opportunities in a wide range of industries. What’s more, a global skills gap in technologies means qualified applicants can expect good salaries and a strong bargaining position.
In 2021, there will be growing opportunities for AI and ML specialists in public safety, banking, fintech, and healthcare, says Gus Walker, Director of Product at Veritone. These industries have the money to invest and see the investment pay off fast, Gus adds.
Further, the pandemic has caused industries to step back and see how AI and ML can help them rebuild or adjust to the new normal. Data collection and preparation and data analytics could become the most in-demand skills while hiring for artificial intelligence.
Companies increasingly require individuals who can identify correct training data and annotate data accurately. Businesses need talent data that can maintain growing training sets and analyze the data to create targeted datasets for customized model generation.
This will require professionals familiar with algorithm tuning and training. The ideal candidate will also have experience in AI operations and DevOps to successfully set up datasets and continuous integration and deployment pipelines to keep algorithms updated.
As digitalization is becoming more prominent, unstructured and structured data is becoming readily available, which further calls for AI professionals. Businesses need someone who can maintain production deployments throughout.
Skills for AI
The skills required for artificial intelligence and machine learning vary between extremes. First – the technical developer who takes the desired outcome and builds an algorithm or a series of steps to execute a task in a repeatable format. Second, a business analyst who identifies and understands what a business needs and see the vision to automate it. Consequently, you will find individuals who have the right balance between developer skills and business analyst skills.
These skills are high in demand. Organizations are starting to understand how AI and ML can create a positive impact on these technologies.
Unlike other technologies where technical proficiency is required more. Artificial intelligence requires both technical proficiency and an understanding of the business. Someone who has high technical capabilities as well as understands the business side will be successful. Candidates who maintain a balance between the two skills are preferred candidates among businesses.
As companies are maturing, they are finding themselves in need of full-time employees who are well-versed with AI and ML tools. Companies need a group of professionals that have diverse skills to stay up to date on different offerings and have the ability to implement those skills in a practical situation. Process mining, for instance, is an area where businesses plan to invest heavily. It involves utilizing A. I and ML to identify business processes that have a pattern. These processes can be further streamlined and automated. In the absence of an AI tool, a business analyst would never be able to identify a pattern without an AI tool.
Learning Artificial Intelligence
Artificial intelligence courses and certifications are the primary means to learn the skills required for artificial intelligence engineers. The following are a few prominent certifications.
- AIETM (Artificial Intelligence Engineer) – This certification is offered by the Artificial Intelligence Board of America (ARTiBA). This certification equips you with the technical skills required to build intelligent systems. Taking this certification equips you with the knowledge of supervised and non-supervised machine learning, neural networks, natural language processing, reinforced learning, and more.
- IBM AI Engineering Professional Certificate – This certification equips you with ML algorithms and prepares you to build ML models using SciKit and SciPy. You also learn to deploy models on Apache Spark. Further, you will learn supervised, unsupervised, and reinforced learning. Deep learning is an essential part of this AI certification. You will learn to build and deploy deep learning models using Keras, Pytorch, and Tensor Flow.
- Stanford’s machine learning by Coursera-This AI certification course is created by Andrew NG, a renowned engineer with experience in heading AI projects at top corporates including Google, Microsoft, Baidu, etc. This certification program equips you with deep learning, machine learning, and all other skills required to kick start a career in AI.