Artificial intelligence has gained a lot of attention online, with its path-breaking innovations taking the front seat across many industries. This has led to the growing demand for Simplilearn’s courses on artificial intelligence as employers look for trained professionals who can add value to their domain. Today, when nine out of ten households use AI-driven devices for running errands and completing tasks, they are contributing to the creation of several jobs across the world. Checkout AlmaBetter’s blog https://www.almabetter.
One of the peak moments when AI broke the internet was when reports of Amazon Alexa laughing, was observed worldwide. AI does come with many viable, unique, and promising career opportunities that can accelerate this digital transformation. However, despite AI being well-accepted in numerous fields, many still aren’t impressed with choosing AI as their career domain. To set the records straight, here’s why AI is more than what it seems on the surface:
- AI Comes From Technological Advancement
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Be it automated, pollution-free cars, or smart chatbots, Artificial Intelligence has replaced the manual labor, time, and cost-involvement of getting things done. Even in the field of IT, Healthcare, eCommerce, Education, high-end AI technology is currently contributing in the form of services and value as a frontline taskforce, be it in the face of a pandemic or otherwise.
- Exponential Demand for Skilled AI professionals
The market is perfect for trained AI, Machine Learning, Data Science, Neural Network engineers, and technicians who can help in building advanced technological tools to contribute towards predicting human behavior that can boost business and eCommerce worldwide.
- Handsomely Paid and Valued
Because of the value these jobs and individuals bring with them to an industry, such opportunities often come with high salaries, and exposure to attract more job seekers. Most importantly, the professionals in this field are often treated as an asset to an enterprise and are often given decision-making roles for their profound insights.
It can be rightly said that AI benefits both companies and the consumers in immeasurable ways, where the former can use it to amp up their research and innovation. Consumers, on the other hand, get value-based services and products that elevate their lifestyle and fulfill their requirements in rare, qualitative ways. But, what exactly does it mean to become an AI specialist? Let’s have a closer look at this.
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What does it mean to be an AI Specialist?
Artificial Intelligence specialists are individuals who are the force behind programming computers that are advanced and have human-like intelligence to carry out tasks in quicker and more effective ways. These professionals collate data, analyze, and then use these drawn insights to make crucial decisions that can help the company to acquire targets seamlessly. The cognitive stimulation that these technicians work on is based on three stages:
- Stage I: Machine Learning
This is the stage at which several intelligent, intricate algorithms define complex systems and clusters that a device needs to process to gain self-awareness on the appropriate response in a scenario. Machine Learning professionals work on such vast, sophisticated modules, programmed intrinsically for industries as they gain knowledge from experience.
- Stage II: Machine Intelligence
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Currently, this is the stage where most of our AI technology is located, where systems learn from their experience, past actions, and false algorithms to make decisions in a scenario. An advanced stage than the last, here the technicians help in improving the cognitive capabilities of a system by identifying shortcomings in a process and rectifying it.
- Stage III: Machine Consciousness
It is the final stage of Artificial Intelligence where a machine (or a system) can make a call to perform actions based on its self-awareness, without requiring any external information input. Today, we’re surrounded by this groundbreaking technology, and an example would be that of Alexa or Siri, who are our digital voice assistants.
Becoming an AI Specialist: Levels
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The pre-requisite of a plausible AI specialist career is to have an interest in coding and mathematics in general like algorithms and calculus. Here’s how you can proceed:
Level I: Treading
This stage requires you to cover the basics of AI principles like linear algebra, statistics, probability. You may also be required to brush up your skills on statistical tests like the chi-square test, Bayes Theorem of probability, etc. Once you’ve taken care of it, you need to make your mind on the programming language you’d like to work in (choices can be maximum two-three languages). Be it JAVA, Python, Red – each of these frameworks come with their distinct functionalities that you need to weigh in before moving forward, and then understand their data structures, regression, machine learning models, and scope. More information you can also find at https://gowithcode.com/top-programming-languages/.
Level II: Diving into AI
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At this stage, you need to understand the concept of neural networks, a framework based on human brain mapping, and how human minds analyze situations. You have to be adept at doing the math required to understand the many layers of such networks and their operation. At this stage, you’d also be made familiar with the Big Data concept, Natural Language Processing, and Deep Learning – from its multilayer perceptrons to optimized and realistic algorithms.
Level III: Finding Balance
This is the final level at which you need to attain expertise in effectively and accurately carrying out tasks based on the concepts learned at the first and second levels, as well as collecting actionable data from them. You also need to learn the usage and scope of optimizing algorithms and functions based on several parameters to reach the optimal solution in respective scenarios. You’d also need to continually perform research and acquire knowledge in the field to make this system sustainable and reliable over time according to the constantly changing parameters and goals.
Conclusion
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To gain a good understanding of AI’s vast and dynamic field, you would require constant hard work, perseverance, consistency, and time. In the coming years, AI’s scope would only grow, opening up even more profitable options based on its value and skills. The key lies in persistence and motivation to prepare yourself for achieving your targets better, gradually with time.
