This Content Was Updated on 9th July 2020
When we hear the word “Artificial Intelligence”, digital assistants, chatbots, robots, and self-driving cars is what strikes our mind. These are some real examples of artificial intelligence, powerful and interesting. Unlike other technologies, we will continue to see the advancements of AI and ML in 2020 and beyond.
when we hear the word “Artificial Intelligence”, digital assistants, chatbots, robots, and self-driving cars is what strikes our mind. These are some real examples of artificial intelligence, powerful and interesting. Unlike other technologies, we will continue to see the advancements of AI and ML in 2020 and beyond.
There are other technologies that will steadily grow but technologies like deep learning and machine learning will creep on us. Meanwhile, many CEOs believe that AI is going to be bigger than the internet revolution.
Despite the overwhelming AI updates, we’re yet to see companies introducing AI initiatives. AI is here to transform the way we work and live. AI systems can minimize the occurrences of human error.
AI is here to create jobs and not destroy them.
AI Jobs Reality Amid COVID-19
According to Gartner, AI is heralded to create 2.3 million jobs by the end of 2020, leading a net gain of 500,000 potentially new jobs. And in the light of COVID-19 crisis, job opportunities for AI workers are bound to see a sharp rise.
The global economic status is not the same, but AI talents can remain positive.
- According to International Data Corporation (IDC), the number of AI jobs is expected to globally grow 16 percent this year.
- Gartner’s report also mentions 85 percent of AI professionals believe the industry has become more diversified in recent years.
Stating that organizations across all sectors have started to embrace AI and ML, it is evident that professionals skilled in these technologies will be in huge demand beyond 2020.
Will AI be the Next Digital Frontier?
The pandemic has destroyed millions of jobs, yet big giants are expanding the use of AI. A 2017 report by McKinsey predicted that the third of workers in the US will be replaced by automation and robots by 2030. Events like pandemic will certainly change at all timelines. But it is up to humans to decide how they wish to integrate this technology into the world.
2020 is indeed an open door for professionals who are already engaged in AI.
- Gartner says, about 30 percent of all the B2B companies will be employing AI to boost at least one of their sales processes.
- According to Demandbase, 80 percent of B2B marketing executives proclaimed AI will revolutionize the marketing industry by the end of 2020.
- IDC predicts 75 percent of commercial apps will use AI by 2021.
But a survey from O’Reilly states there is a dearth for talent in AI skills and it is the largest barrier to AI adoption. The major concern for the AI crisis is due to the academic and training programs that are not in sync with the current industry trends. Not only do organizations need professionals skilled in AI technologies but they also need employees to be agile and change their skills over time.
A career in artificial intelligence is not one size that fits all.
So, if you’re interested to start a career in artificial intelligence, here’s a guide you could follow today:
Moving further, artificial intelligence is a field of computer science and is sometimes called machine intelligence. In simple terms, AI is a field in computer science that teaches the machine how to understand the human mind and react like humans. AI aims to build machines that can think, behave, and understand the way humans do.
Amidst all the tumult, AI is already paving its way into a stage where it is said that to replace redundant job roles with smart devices and automation. However, we have not reached a stage where machines will take over our everyday life.
As an AI aspirant, you have ample of job opportunities in this field. Some AI job includes machine learning engineer, data scientist, business intelligence developer, research scientists, and AI engineer. Artificial intelligence engineer is one of the most prominent job roles in the AI industry today. As an engineer, it is important to stay informed of tech innovations. So, here’s a look at the responsibilities artificial intelligence has towards engineering.
👉An artificial intelligence engineer has the following responsibilities:
- Research appropriate machine learning algorithms.
- Transforming data science prototypes.
- Based on requirements the AI engineer needs to develop machine learning applications.
- Work closely with electrical engineers and robotics team.
- Run machine learning tests.
- Train systems when required.
- Selection of suitable datasets and data representation techniques.
The responsibilities will vary depending on the level of expertise (fresher or experienced professional). However, these are the overall roles and responsibilities an artificial engineer will be carrying out.
👉A Step by Step Guide to Start a Career as an Artificial Intelligence Engineer
As a Fresher:
- A Bachelor’s degree in the following subjects-
- Computer Science
- Information Technology
- Mathematics and Statistics
Apart from a bachelor’s degree, one must be proficient in analytical skills, problem-solving skills, creative thinking, effective communication, and industry knowledge. These skills can be achievable through online re-skilling or taking up a Master’s degree. However, since artificial intelligence is the ‘buzzword’ of today’s tech world it is advisable to take up online and training programs from accredited institutions.
Ideally, a bachelor’s degree could only help you land an entry-level position.
A Master’s degree -
If you’re looking to get into leadership roles entailing supervision, you need to have a Master’s degree or a Ph.D.
A Master’s degree that offers advanced computer science education with a specialization in artificial intelligence or a Master’s degree in artificial intelligence will allow you to weave your AI career. The master’s program generally focuses on developing professionals. The robust coursework entails around real-world problems and application domains.
A working professional -
For someone in the IT industry, it is important to fine-tune your technical skills. To 🔗become an AI engineer one needs to learn the latest skills and technologies. AI engineers are not just skilled professionals but have in-depth practical and theoretical knowledge. Having a practical approach towards these technologies will help you gain an edge over other competitors. Additional add-on AI certification programs will win you brownie points while seeking jobs in AI.
👉The Skills Required
A road-map towards becoming an AI engineer. AI is an emerging technology; most professionals are opting for AI certifications from some of the best online programs. Professionals looking towards a career in AI must have a closer look at the technical and business skills they need to master.
- Programming languages like R, Python, Java, and C++
Having a knack for coding is one important skill one needs to have as an AI engineer. Being proficient in programming languages like R, Python, Java, and C++ are important. This will help understand concepts like data structures and classes. Learning more than one programming language will always prove as an added advantage since organizations these days are focusing on individuals with multiple skill-set.
- Statistics, Linear Algebra and Calculus
To understand how algorithms and machine learning functions it is important one understands statistics. Gaussian distributions, standard deviation, and mean are going to come up a lot. Solid understanding of probability and models like Naive Bayes, Hidden Markov models, and Gaussian Mixture models is advisable.
Additionally, one needs to be familiar with vectors, matrices, matrix multiplication, and understanding of integrals and derivatives.
- Natural Language Processing
NLP is an important sub-field of artificial intelligence, this enables computers to understand and process human languages. In short, the natural language processing gets the computer closer to a human-level understanding of language.
This covers two major areas of work like linguistics and computer science, there are possibilities one might get to works with audio, video, or text. This is why is essential to have good control and working knowledge in libraries like NLTK and Gensim and techniques such as sentimental analysis, summarization, and word2vec.
- Neural Network Architectures
When tasks get too complex and complicated for humans to code the role of machine learning comes to play. That being said, recent advances in machine learning have enabled computers to do tasks that are too impractical for the human mind to comprehend.
Neural networks have proven to be the precise way of approaching problems like speech recognition, image classification, and translation.
How else can an AI engineer explain the critical events to stakeholders and individuals with no technical know-how without having the non-technical skills? To become a successful AI engineer it is also important to have knowledge in the non-technical field.
- Industry knowledge
In-depth knowledge regarding the industry scenario will prove beneficial for AI professionals working in this field since this will help professionals understand the real-world scenario and the pain points of the industry.
- Communication Skills
Explaining concepts like artificial intelligence and machine learning can be tough if one does not communicate in simple language. Having good communication skills is going to be much easier when one needs to explain such concepts to individuals with very little technical knowledge.
- Critical Thinking
Numbers and data should intrigue AI engineers, they must be able to use this finding and jump to insightful conclusions.
With the emergence of AI, every sector is now looking to implement artificial intelligence making the demand for professionals 2x higher.
Word to the wise
We’re living in a technology-driven era with more professionals looking to upgrade themselves for the new-age tech jobs. You can find many online programs and online training institutes providing AI certification, AI engineer certification and machine learning certification, etc.
Most of the AI certification programs have been well crafted by industry experts. The program provides a lens that helps validate the technical competency of the applicant. It acts as a bridge between someone who does not possess all the skills in AI and the current industry requirements.
Professional certifications are one of the major ways that give an employer the confidence and credibility of the individual they’re looking to hire.
AI is making giant strides, all we need are the rules to catch up with the technology.
Educate yourselves today to map the jobs of tomorrow!