The Best Employability Skills to Put on Your Resume


    The competition in the job market is growing exponentially every day. The tech industry is a very dynamic market and the demands keep varying with time. Employers are expecting more and more from their employees. In this environment, one has to make sure that he/she should secure a job. The employers look at your resume. First, your resume will give them an overview of the skills you hold. You will move from one role to another, and each of these new roles will require some basic skills to efficiently handle your work. Your employability skills will help you in transitioning from one role to another.

    It is important to have such skills included in your resume, which will compel your potential employers to choose you over others. Your skills will keep you ahead of the crowd providing you with a leading edge in the selection process. As technology advances, the needs of the company change. Also, with every update, the company expects its employees to be updated with the latest knowledge. With the advent of data science, every organization realizes the need to shift to data-driven solutions. This opens a lot of opportunities and scope in relevant areas. The list of employability skills is neverending, but some specific skills will guarantee you a good career. Whether you are looking to start a new career or switch to better opportunities, you can find these free courses online to help you achieve your goal. We discuss those skills in brief as follows:

    Software development

    Software development is a broad term that includes identifying, designing, programming, testing, and fixing errors while developing and deploying an application. A software developer also recommends software upgrades that meet the requirements of the customers. Programming is an important aspect of software development. 

    Many programming languages are used by various companies depending on the applications; you can choose what is best suited to you. If you are a complete beginner, you can start with Python since it is the most preferred programming language for data science and other applications. You can also choose other languages like C, Java, C#, etc. Having fundamental knowledge along with hands-on experience in software development will guarantee you a good job role in the IT industry. 

    AI and Machine Learning

    Artificial Intelligence and Machine learning are not uncommon terms these days. Almost all of us have heard it even in our daily applications. The fact that almost every existing application is data-driven makes AI and ML so popular. In layman’s terms, Artificial Intelligence refers to making machines or devices capable of imitating human behavior. Machine learning is a subset of AI. Machine Learning includes algorithms through which the device uses data to learn something. Data is vast and is generated in tremendous amounts every day. This data has significant and insignificant parts. The useful data can be utilized to gain insights. This data is very useful for a diverse range of applications. 

    We already rely on a lot of features in our daily lives that use machine learning like maps, traffic prediction, weather forecast, advertisement recommendations, etc. It is a revolutionary technology to use the current data and predict future patterns. A lot of other research areas have integrated machine learning. Machine learning is not limited to software or IT applications. It is incorporated in the sports sector, fashion industry, healthcare, stock market, and business, etc. 

    Machine learning and AI offer a huge scope for research and development. A major part of their benefits is still unexplored. These technologies will not fade away anytime sooner in the future. If you are a beginner, you must start with learning machine learning basics. 

    Big Data

    Unstructured, semi-structured, and structured data are generated and collected to feed as an input for machine learning projects, and other advanced analytics projects are known as big data. It is also used for predictive modeling and simulation programs. Although there is no specific volume that equates to big data, the volume of data is generally in terabytes, petabytes, and exabytes collected over time. 

    Big data analytics systems are used by businesses to model their growth, improve their customer services and incur more profit. The demand for handling big data skills is increasing every day. Big data is used in the medical sector to predict the illness and their symptoms better. 

    The finance sector uses it to predict the performance of the market. It is also used in the energy sector to optimize its output and also better to predict drilling sites. It is also used by the government and transportation sectors. Every day the world is moving towards data-driven solutions. With the advent of the Internet of Things (IoT), the big data industry is already growing exponentially. 

    Cloud Computing

    Cloud computing is a 21st-century technology. This technology grew rapidly, and the information technology industry adapted to it. Cloud computing is as interesting as it sounds. Cloud computing is not only significant for businesses but also important for an average person. It lets you store and download files from the internet. It lets you store and access your files on the internet. You can even run programs without needing to install them on your device. 

    Cloud computing opens the door to a vast number of services. For example, Netflix relies on cloud computing to provide content to its customers. Cloud computing provides efficiency and is also cost-effective. It lets you access your content anywhere at any time in the world, thus saving a lot of time. It also offers better security to keep the data safe. Cloud computing is one of the technologies which will be used extensively in the future. With new technologies such as artificial intelligence, machine learning, cloud computing will be an essential frontier to work with.


    With the world rapidly moving towards digitization, an enormous amount of data is produced. This data is used by businesses as well as people for their respective purposes. Among this vast array of data, there are many private data. These private data should be protected so that they cannot be misused by someone. 

    Cybersecurity tools defend the data from cyber-attacks, unauthorized access, and damages. Cyber attacks are increasing day by day, incurring huge amounts of financial and data loss. In this scenario, the companies need to upgrade their security. According to a report by CAGR, the revenue of the cybersecurity services industry is expected to reach about $7.6 billion in 2022. So, the demand for Cybersecurity professionals is stronger than ever. 


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