A Programmer’s Guide to Creating Successful Career in the AI industry

 The IT industry is among the fastest-growing industries around the globe. In 2026, the market value is projected to be a staggering $1.5 trillion.

In the meantime, Artificial Intelligence (AI) is growing in popularity as well. The newest technology was predicted to earn $22.6 billion by 2020 According to Statista.


So, it is apparent that both these fields are extremely attractive to tech-savvy geniuses.


In this blog I break down the process of pursuing the AI career into distinct sections to understand the steps to becoming an accomplished Artificial Intelligence Engineer.


Read more:- Top react interview questions you must prepare in 2022.


What Is Artificial Intelligence?


Artificial Intelligence technology is both revolutionary and controversial. Because it's very powerful and it is not being explored thoroughly, people are scared of it. They begin making up stories about AI dominating the world and replacing human workers.


AI technology finds application in almost any industry: healthcare, transportation, finance, VR gaming, advertising, manufacturing, and many more.


Read more:- Highly Recommended List Of Top 5 Machine Learning Jobs in 2022 India!

What Does Cloud Storage Have to Do With AI?

In the last few years, we've seen a huge cloud migration. This is due to the cost of cloud storage, environmental concerns, and cybersecurity concerns, companies are moving online services away from traditional servers and moving them to the cloud.


What is the significance of AI significant in this instance? Because AI is the engine behind cloud servers and can learn from the data it holds. In this way, it is able to solve problems before the public even notices, or even anticipate and stop issues from occurring.


Amazon's Alexa and Google Assistant are great examples of how wonderful the merging of cloud technology and AI could be. These features also hint at the future huge trend of similar devices we're likely to see in the near future.


This trend will create a massive need for AI engineers who will manage AI-powered cloud-based systems.


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Where Can I Work in AI? 

That being said The next question to ask will be "Where can you work as an AI expert?" Here are some companies, industries as well as government agencies that are benefiting by AI.

Technology and Computer Science

The quality assurance (QA) testing is an essential service in software development. In the near future, the QA market is predicted to be $49.9 Billion by 2026, which is more than double the value it is currently. Knowing how to use AI or machine learning (ML) to test software and debugging can be profitable.


Healthcare

Healthcare is the area where AI technology has the most promise. In 2019 , alone there were investors pouring more than $4 billion into healthcare AI companies. After the pandemic, desire for healthcare improvement will only increase.

Agriculture

AI systems aid in the production of food by increasing the quality and efficiency of harvest. The year 2020 will see the proportion of AI jobs available in the agriculture sector doubled.


The most common agritech job posts are:

  • Software Engineer

  • UI/UX Specialist

  • Data Analyst

  • AI Specialist

  • Business Development and Sales

  • Digital Content Creator

  • Marketing Communications

  • Finance (Operations and Corporate Finance).


Public Sector

AI algorithms can help scientists at NASA to understand massive amounts of information about the universe. At present, there are more than 150 AI-related jobs available within the NASA Jet Propulsion Laboratory, including Data Scientist Senior Software Engineer, Software Systems Engineer and many more

Marketing

There are many companies that create apps to assist marketers with automatizing their strategies. As you could imagine, the majority are seeking AI engineers.

Technical Skills Required in AI

To become an AI specialist, there's a set of complex skills individuals must have. For starters, technical abilities This is the information is expected of an AI as well as ML engineering engineer must be able to:


  • R, Python, Java, C++

  • Quantitative analysis

  • Business acume

  • Excel

  • SQL

  • Tableau

  • Hadoop, Spark

  • Probability and statistics calculations

  • Reporting and presentation skills

  • Database administration

  • Data analysis

  • Data visualization

  • Extraction and signal processing techniques

Personal Skills 

Apart from having knowledge of the tools and software mentioned above In addition, an AI expert should be:


  • curious

  • creative

  • patient

  • persistent

  • up-to-date with the latest trends

  • a quick learner

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