As the demand for people with advanced technical skills is rising, many companies are putting more resources into recruiting, hiring, and nurturing the right talent to remain in global competition. This means that employees willing to spend time developing technical skills will have the upper hand in landing some of the most demanding roles in the tech industry. But the world of technology is changing fast, so the industry’s demanding technologies are changing all the time.In this article, you can learn which tech skills are the most beneficial to learn today to increase your demand in the tech industry and also to help you level up as an employee.
Artificial Intelligence (AI) and Machine Learning (ML) are two very hot buzzwords that have become synonymous with innovation. Today, AI and ML are used in a vast number of services and tools.According to LinkedIn 2020 Emerging Jobs Report, hiring growth for the role of Artificial Intelligence Specialist has increased by 74% annually in the last 4 years.According to Indeed’s best jobs of 2019 study, Machine Learning Engineer job openings increased by 344% between 2015 and 2018. Also, according to Indeed, the current average salary of a Machine Learning Engineer is $140,502 per year in the United States.Skills such as TensorFlow, Python, Java, R, and Natural Language Processing are skills that you should learn today to improve your chances of getting hired for an AI or ML job as these skills now have the highest demand.Learning to build chatbots is also one of the most in-demand skills that come under AI and ML. You must have noticed that AI deals with customer service interactions and queries on many websites and that chatbots pop up when you visit these websites. AI-operated chatbots are being deployed extensively by several major industries.Due to the current popularity, IT employees who started learning AI and ML themselves are sure to earn the highest salaries and demand in 2021.
Cloud computing jobs are on the rise because more and more companies are switching from the traditional server infrastructure to cloud solutions. Many AI and ML services are also provided by cloud platforms.According to Indeed, Cloud Computing job openings in the USA increased by 107% between 2016 and 2019.Amazon Web Services (AWS) is currently the leading cloud service provider on the market. So learning AWS before 2021 will be very useful to improve your demand as an IT professional.AWS-certified IT professionals earn more than their non-certified counterparts. It is one of the most profitable skills IT employees can learn to level up their tech career as AWS certified developers earning an average of $130,272 (the highest of all certifications in the United States and Canada). The current average salary of an AWS Could Solution Architect in the United States is $139,055.Some other most in-demand cloud skills are Microsoft Azure, Docker, DevOps, and Kubernetes**.**Cloud Engineers will likely continue to have a long-term need across the technology industry as more companies move to cloud platforms.
It’s very important for any company that collects sensitive customer information or deals with sensitive data of its own, to keep their networks secure. Almost every major company today stores customer and company data in databases, making cybersecurity one of the top technology trends in 2020 and beyond.Cybersecurity Specialist job position has a 30% annual growth rate in the US, according to LinkedIn 2020 Emerging Jobs Report. Cloud security experts also have a high demand due to the growing number of cloud services.Cybersecurity, Information Security, Network Security, and **Vulnerability Assessment **are the best skills to learn to land a job as a Cybersecurity Specialist. You also need a good knowledge of the basics of programming languages.6 out of 15 top-paying IT certifications focus on security, so learning IT security isn’t going to be a waste even if you’re an IT professional.The cybersecurity labor crunch is expected to reach 3.5 million unfilled jobs by 2021. So the demand for security professionals will be extremely high in 2021.
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Big Data has become the buzzword today in the world of technology. All top business strategic decisions are taken based on Big Data and Data Sciences technologies. This has contributed to increasing demand for Big Data engineers in India and is expected to soar up in the coming years.
There has been tremendous growth in the tools and techniques around Big Data and other related fields. Big Data has become the answer to using and analysing real-time data. In today’s competitive business work, no company can survive without Big Data.
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If you are looking to learn Java, you may be wondering where to start. Which technologies should you focus on? Whether you are new to the language, a middle-level learner, or already using Java at work, this article explores the essentials that you need to know.
Learning a programming language is a technological process that requires serious preparation. Otherwise, you can easily “choke” on the learning process itself.
I work for a company that created an interactive Java online course. From time to time, our graduates tell us about what they are required to know in interviews, and also about what technologies they use in their work. Based on these surveys, a shortlist of such technologies can be compiled.
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Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.
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Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community — What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.
The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.
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You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club.
Before we dive into the machine learning world, you should take a step back and think, what is stopping you from getting started? If you think about it, most of the time, we presuppose things about ourselves and assume that to be true without question.
The most normal presumption that we make about ourselves is that we need to have prior knowledge before getting started. Get a degree, complete a course, or have a good understanding of a particular subject.
The truth is that most of the time, this is a lie, the prior knowledge you think you need is most of the time not required or is so big that even experts from the field don’t fully understand it. The Seek of this prior knowledge is a trap that will make you run in circles, which leads us to the next presumption.
The perfect condition, you can’t wait for the ideal environment or situation to get started, things will never be 100% ready, try and fail, then try again. It takes a lot of time to get good at machine learning; you won’t learn all at once and especially at the beginning.
Instead of trying to acknowledge everything before getting started, do a little bit every day; you can make significant progress by creating small things every day for a considerable amount of time. The perfect condition will never exist, do it in your path, be consistent with it, and the results will come.
After you start making little progress every day, you probably will end up having a struggle with something or failing to achieve your goal at a certain point. This feeling is tough; it’s hard to see yourself not making any progress, not having any sense of gratification, and then still not give up.
Machine learning is hard, it might take you a few weeks, months or even years to see progress in a certain point but isn’t any harder than any other technical skill, it requires repetition and dedication to get where you want, you need to test it, make a mistake and learn from i
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