Top 5 Essential Tech Skills You Need to Master in 2021
Feb 11, 2021
The job market is constantly changing and technology is prevalent everywhere. Regardless of the field you’re in, having a lot of tech skills play an essential role your success. It is always a great decision to keep learning and advancing your skills, but there are just so much to learn. How do you know what are the necessary skills for your success? No worries! JobsDecoder will walk you through in how to become successful in these skills.
- Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning are very hot keywords that everyone has encountered at some point in their careers. Today, AI and ML are used in a lot of industries and services. According to Indeed, the number of job postings for tech careers have increased by about 110% in 2016–2019.
To help you understand what you need to learn about AI and ML, here is a list of popular AI tools and Frameworks:
- TensorFlow
- Scikit Learn
- Pytorch
- Keras
TensorFlow
TensorFlow is a free open-source software library for machine learning. It is often used with large-scale datasets and makes it easy to acquire data, to train models and to generate predictions. TensorFlow can also be used to train deep-learning models for handwritten digit classification, image recognition, natural language processing, and more.
Where can I learn how to use TensorFlow?
You can visit TensorFlow Website, or learn using online course platforms such as Coursera, Udacity, edX, etc.
Scikit Learn
Scikit Learn is probably the most well known ML library. It is free, open-source and easy to use. It is an effective tool for Predictive Data Analysis. It is also an expansion of Python libraries-Numpy, Scipy and matplotlib. The library includes a lot of data mining capabilities and calculations.
Where to learn more about Scikit Learn?
Website: Scikit Learn
Pytorch
PyTorch is developed by Facebook’s AI Research Lab. The library is based on Torch library and it is primarily used for Computer Vision and Natural Language Processing.
Where to Learn more about Pytorch?
Pytorch, GitHub
Keras
Keras is an open-source library that uses Python interface. It becomes quite capable when it comes to building high-level neural networks. Keras is often used to solve problems like image recognition.
Where to learn more about Keras?
Keras
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2. Cloud Computing
Cloud computing has become one of the most valuable career skills. There has been a consistent increase in the demand for Cloud Computing. Companies are now turning away from the traditional server infrastructures. Rather, they are building products and services directly in the Cloud to make things cost-efficient.
Popular choices of Cloud Computing platforms include the following:
- Amazon Web Service (AWS)
- Microsoft Azure
- Google Cloud
Amazon Web Service (AWS)
AWS is a Cloud Computing platform offered by Amazon. What is great about AWS is that everything is provided in the form of web services. AWS offers cloud-based products such as compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security and enterprise applications.
Where to learn more about AWS?
AWS
Microsoft Azure
Azure is a very flexible Cloud platform, for the users can run any services or combine the server with other data servers, applications, etc. Azure is quite user-friendly and easy to learn. It comes handy when you need to build, test, or deploy applications through Microsoft-managed data servers.
Where to learn more about Microsoft Azure?
Azure website, Certificate courses
Google Cloud
Google Cloud Platform is another most well known and popular choice for Cloud-based servers. It is a suite of Cloud Computing services that runs on the infrastructures similar to Google products such as Youtube, Google Search, and Gmail. The Cloud provides multi-layered security service to assure users data, products and applications are protected.
Where to learn more about Google Cloud Platform?
Google Cloud Certification
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3. Cybersecurity
Cybersecurity is the practice of protecting systems that requires the use of the internet such as data, hardware and software from cyber attacks. Individuals and businesses focus on cybersecurity to protect information against illegal and unauthorized access to their systems.
The field is gaining more significance and interest because of the society’s growing dependence on computerized systems. Companies need to build their products and services in a secure system simply because there is no shortage of threats out there. Also, it has become a very important job to store sensitive customer/company data into a secure databases, making cybersecurity one of the top skills in demand.
The job market is very bright for Cybersecurity Specialists. According to this Forbes Article, career experts predict that Cybersecurity jobs will grow by 31% through 2029, which is about 8 times faster than the national average job growth of 4%.
Free online Cybersecurity courses:
Sans Cyber Aces, CDSE, Cybrary
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4. Full Stack Development
Full Stack Development refers to a comprehensive development that involves the front-end and back-end work of a web application. The front-end work usually involves the visible parts that the users interact with (graphics, website design, etc.). The back-end work focuses more on infrastructures such as databases, servers, API’s and algorithms for applications. So, a Full Stack developer is capable of doing both front and back end developments.
Full Stack Developers are one of the most desired jobs by companies. According to this Indeed article, Full Stack Developer ranks 2nd in the best jobs of 2020. To begin Full Stack Development, you need to be savvy in these languages:
- JavaScript
- Python (Back-end Developmet)
- HTML / CSS
- PHP
- Databases — SQL, MongoDB (NoSQL), JSON
- Node.js, Angular, React
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5. Data Visualization
Data visualization has been increasing in importance due to the abundance of data. Data visualization is a way to interpret and represent data in a graphical context. It is an efficient way of communication and a great way to help people understand what could be meaningful about the data.
Data visualization is basically a bridge between technical and non-technical roles. What data visualization essentially does is taking the data collected by analysts and translating it into a form anybody can understand.
Tools: Tableau, Power BI, matplotlib, Plotly
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