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Top 5 Deep Learning Skills for Engineers to Master During a Recession

Every field has some sub-fields. Some are based entirely on application-based knowledge of what already exists whereas others demand extensive research work and hypotheses on novel concepts. One such field that has managed to create an optimum balance between application and the creation of novel ideas is machine learning. However, that's not what we will be discussing today. This article is about a sub-field of machine learning called "deep learning". As per experts, this sub-field primarily deals with neural networks and skills that can help one in keeping up with the expectations of the employers out there. This is very beneficial for those who have an engineering background since there is always a cut-throat competition for jobs there. If one works properly on deep learning, then he/she is bound to unleash ground-breaking and lucrative career opportunities especially at the top American tech-companies of Facebook, Amazon, Apple, Netflix and Google (FAANG) with the help of cybersecurity and programming languages. So, if you are an engineer and you wish to get an edge over others in your field, then you surely need to pay your hands on these five fantastic fields: 

  1. Learn simply with Spark.

Responsible for the dynamic revolution in the field of data sciences, Spark has been enjoying the reputation of being a cutting-edge technological software since its very inception. Apart from being available for free, it is an open-source processing engine that prioritizes speed, accessibility, and analytical capabilities. Heard of Hadoop clusters? Ever wondered what makes your applications run over there? It's none other than Spark. Because of Spark, your applications are able to load one hundred times faster in memory and always ten times faster while operating on disk. Speaking of data analysis, with Spark, you can explore the role of being able to do cluster analysis. It is the process of classifying data into distinct categories based on shared characteristics. This is done in such a way that the things contained within the group share more similarities with one another than they do with the objects contained inside another group. You will have more opportunities available to you, and you will be able to advance your career with FAANG firms. It is one of the recession-proof deep learning skills that every person should have. With that being said, Spark stands out to be one of the recession-proof deep learning skills that every person should have, especially engineers.

Read More: What are the skills that you need for a career in cyber security coding?

  1. Developing software's never gets old. 

Designing and maintaining umpteen systems, providing solutions for triggering problems not only for one but multiple platforms is what the Information Technology (IT) need, eternally. Website development and software development for mobile operating systems are two popular sub-specializations in the field of computer science. On the other side, web developers need to have knowledge of search engine optimization and search engine marketing. UX designers and Android mobile developers are two of the most in-demand professionals in this industry with an exorbitant pay. Under software development, a field of paramount importance is that of programmers. If one wishes to become a programmer, then one needs to have a fluency in the languages used for programming. The specialized knowledge of programming languages is becoming more and more in demand as a result of the constant improvement of technology. It is anticipated that demand for programming as a skill would increase by 22% by the year 2028; hence, a career in programming will provide a wide range of chances in FAANG firms.

  1. We all need somebody who can keep the data safe from the prying eyes of hackers. 

Well, that's true and will always hold true. This has led to the birth of the field of cybersecurity. It involves the collection of technology, processes, and services that are responsible for the protection of networks and devices from assaults that were not anticipated and access that was not authorized. Information security, network security, and vulnerability assessment are three areas of expertise that are necessary for specialists in cybersecurity. Ethical hacking, cybersecurity analysis, and security engineering are all exciting and potentially lucrative career paths in this industry. A promising sub-field of cybersecurity is the signal processing domain. It is yet another highly sought-after ability that firms could look for in specialists. It is possible that it will include techniques such as time-frequency analysis, convolution, Fourier analysis, and others related to deep learning. These methods improve the effectiveness of storage as well as transmission and quality, and they can also identify certain components of a signal from a guest computer. It is one of the recession-proof deep learning skills that every person should have, albeit the engineers. 

  1. Cloud Storage will be eternally-demanded. 

Be it an individual's or a company's, data will always be expanding. Computers in the cloud storing and providing data, programmers, and various other computing resources to users via the internet is the primary function of cloud computing, which is sometimes known as “cloud computing.” The planning, designing, development, and maintenance of cloud computing solutions require the expertise of cloud specialists and cloud engineers. Certification in Amazon Web Services and Microsoft Azure are examples of qualifications in technology that are currently in high demand. Cloud security engineers, data science engineers, cloud architects, and cloud consultants are just some of the job titles that are available in this FAANG industry.

  1. Architectures of Neural Networks

Neural networks are a predetermined set of algorithms that are used to execute deep learning tasks. They constitute a category of models and are essential to the process of deep learning. Understanding how the human brain operates and being able to model and simulate an artificial brain are both made possible by neural networks. It is one of the recession-proof deep learning skills that every person should have.

So, these are fantastic five fields that can help engineers with deep learning.

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