Artificial intelligence is changing societies and economies. AI enhances the speed, efficiency, and precision of human efforts and is being adopted across several industries. These new technologies are coming up to make the older ones more advanced in nature; hence professionals have to keep up with the new and enhanced AI skills to promote learning, unlearning, and relearning. Tech businesses are transforming their nature of work and pushing the workforce towards the need to acquire the most in-demand AI skills to adapt for future jobs. It is also imperative for tech freshers to keep up with the recent developments in the industry and focus on enhancing their knowledge. In this article, we enlist the top AI skills for 2022 that freshers should learn to make progress in their careers.
• Cloud Computing: Cloud computing refers to storing and accessing computing services, such as databases, software, servers, networking, and analytics over the internet. The main reason cloud computing expertise is so essential is that it intersects with all the crucial tech skills and is currently transforming the landscape of data storage and security in businesses. It is one of the most trending technologies, which makes it crucial for freshers to learn it.
• Data Science and Analytics: Experts predict that the use of data will continue to rise, with or without the intervention of any new technology. Organizations and governments are making the most use of data to make decisions based on facts and trends. Learning how to analyse data is of utmost importance as it is useful for various IT tasks. Monitoring performance data can also help teams find security threats or watch out for inefficiencies in operations.
• Programming: Software development jobs in the AI sector is on the rise. Market analysts predict that software development and programming jobs are expected to rise by 28 million worldwide in the next few years. Increasing demand for various computing software and mobile phone apps is driving this growth. Additionally, coding is also an important skill that AI freshers should hone since there is an increasing demand for automation configuration and operational tasks as network security becomes more complex.
• Data visualization and story-telling: Data visualization is a way to help people understand the significance of data by placing it in a visual context. This skill is generally used by data scientists and analysts but can also be used for various AI operations. The professionals who are experts in this skill understand the different business needs and how to connect different information to the viewers using various data visualization tools.
• Internet of Things (IoT): In simple words, the term IoT encompasses everything connected to the internet. Freshers should learn this skill since the industry is working relentlessly on making IoT devices safer and more efficient. Businesses that have already adopted IoT are already increasing their pace for IoT development, and more businesses are adopting this technology.
• Linear algebra and statistics: Linear algebra and statistics is the building block for machine learning and deep learning. Understanding these concepts at the vector and matrix level will help professionals to deepen their understanding and widen their perspective of a particular ML problem. Furthermore, statistics is the reason behind several developments in AI infrastructure.
• DevOps: DevOps is a set of practices and tools that combine software development and IT operations to shorten a system's development lifecycle. DevOps skills can help in both the IT and development aspects of running an enterprise. Freshers can also enhance their DevOps skills to become DevOps engineers in the future.
• Project Management: A fresher's project management skills can enable their individual teams to provide the right value for their employers. There are plenty of challenges that organizations witness to completing projects within stipulated time and budget. Besides, technical skills employers also seek problem-solving and management skills. AI professionals should also know how to set expectations, resolve conflicts, and communicate effectively.
• AR and VR: Augmented reality and virtual reality are the technologies that bridge the real and the virtual worlds. These technologies enable the users to view information and content visually. Industries like healthcare, retail, travel, automotive, to name a few are developing augmented reality solutions in training various business applications.
• Networking and wireless: According to reports, the number of addresses connected to IP networks will be more than three times the global population by 2023. Network engineers and contributors will continue to remain crucial job roles in the AI sector. To excel in the careers based on this skill, AI freshers need to gain knowledge on all aspects of network technology.
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