We hear a mention of "Artificial Intelligence" and what comes to mind are robots, chatbots and self-driving vehicles, which are, of course, real-life examples of artificial intelligence.
Artificial Intelligence (AI) has been gaining more attention lately and is increasingly being perceived as a viable career option due to the acceptance of AI technology across all industries and the demand for professionals with the right training. In the years to come, AI is bound to be pertinent for all enterprises. Businesses are still exploring what all AI can do, thereby placing every industry in a state of discovery, innovation and insecurity. There are currently very few experts in AI since nobody is able to answer all of the questions. In simple terms, this is the perfect time to join AI.
However, in order to land the job of your dreams in AI, you need to become more valuable to potential hiring managers by proving your knowledge of ML and Deep Learning while at the same time highlighting a specialization in a specific area. This article will give you a fair idea of how to get a job in Artificial Intelligence by projecting your skillset.
Building a Career in AI
Sometimes referred to as machine intelligence, AI is a field in computer science that instructs machines to comprehend the human mind and act just like humans. AI seeks to develop machines that are able to think and can mimic human behavior.
The most popular AI job roles include machine learning engineer, data scientist, business intelligence developer, research scientist as well as AI engineer. Successful AI professionals usually share common traits that help them be successful and grow in their careers. AI requires a logical thinking process, as well as the capability to tackle problems using affordable, efficient solutions. It requires an understanding of technological advances that lead to modern programs that enable businesses to stay in the market. Furthermore, AI specialists need technical abilities to develop and maintain software technology.
Additionally, AI professionals must learn how to communicate highly technical information in a way that other people can comprehend so that they can perform their tasks. This requires excellent communication skills as well as the capability to collaborate well with teammates.
Education Requirements for a Career in AI
Basic math and computer technology backgrounds are the foundation of artificial intelligence jobs. For entry-level positions, you must have at least a Bachelor's degree. Alongside is also the need to be skilled in problem-solving, analytical capabilities, innovative thinking as well as effective communication and the knowledge of the industry.
Managerial or leadership roles typically require doctoral or Master's degrees. A Master's program that provides advanced computer science training with specialization in artificial intelligence, or a Master's degree in artificial intelligence will enable you to build into your AI career. The program is generally focused on the development of professionals. The rigorous curriculum is centered around applications and real-world issues. However, with relevant experience, you could gain a strong foothold even without a Master’s or Ph.D.
For those working in the IT sector, it's crucial to improve your technical capabilities. To be an AI engineer, you must acquire the most up-to-date skills and techniques. AI engineers aren't just experts, they have a deep practical and theoretical understanding. Being able to apply your knowledge in a practical manner to AI technologies can give you an advantage over your competitors. Several other add-on AI certifications will earn you points when applying for job opportunities in AI.
Technical Skill Requirements for a Career in AI
AI is a new technology. Anyone who is considering employment in AI should take a close study of the technological and business knowledge they require to master, such as the following:
Programming languages including R, Python, Java along with C++
Being able to code is a crucial quality one must possess in order to become an AI engineer. Becoming proficient in programming languages such as R, Python, Java as well as C++ are important. This helps you understand concepts such as classes and data structures. The ability to learn more than one programming language is always going to be seen to be a plus since companies these days are focusing on people with a variety of skills.
Statistics, Linear Algebra and Calculus
To fully comprehend how machine learning algorithms perform, it is crucial to be aware of statistics. Gaussian distributions such as standard deviation and mean are sure to be discussed a lot. A solid understanding of probability and models such as Naive Bayes, Hidden Markov models as well as Gaussian Mixture models is advisable. Furthermore, one should be knowledgeable about vectors, matrices, matrix multiplication, as well as the understanding of derivatives and integrals.
Natural Language Processing (NLP)
NLP is a major subfield of artificial intelligence that allows computers to recognize and process human language. In short, natural language processing brings computers closer to human understanding of the language. It encompasses two areas of study such as computer science and linguistics so there is a chance that one could work using audio, video or text. It is therefore essential to be familiar with libraries such as NLTK or Gensim and other techniques like emotional analysis, summarization and word2vec.
Non-technical Skill Requirements for a Career in AI
In order to be an effective AI engineer, it's crucial to be adept in the field of non-technical expertise.
Knowledge of the industry
An in-depth understanding of the business environment will be helpful to AI experts working in this field as it helps professionals comprehend the actual situation and problems that the industry faces.
Communication Skills
The process of explaining concepts such as machine learning and artificial intelligence is difficult for those who cannot communicate using easy terms. Being able to communicate effectively will make it much simpler when trying to explain these concepts to people with limited technical expertise.
Critical Thinking
Data and numbers should entice AI engineers. They must be able to make use of this data to draw an insightful conclusion.
Jobs in AI
Cities with the most AI-related jobs include Seattle, New York and San Francisco. The below-mentioned organizations curate the developments in AI to a great degree.
The social media and tech giant makes use of AI for its Oculus virtual reality products as well as software. With a focus on computer vision, the AI used in Oculus headsets tracks and recognizes camera movements to allow users to interact in the world of virtual reality.
Amazon
The retailer creates natural speech processing software and speech analysis for its Alexa digital assistant. As a conversational AI platform, Alexa learns new speech patterns to adapt to the specific needs of each user.
NASA
The world-renowned space researchers have begun to develop AI systems to process and organize the huge volume of data found within the universe. NASA hopes to develop an instrument to find habitable planets by analyzing the chemical composition of light's wavelengths.
Tesla
Tesla's self-driving program is heavily dependent upon AI advancement and machine learning. The AI is able to process data such as road markings, traffic laws as well as external cameras to see the road ahead and react to the events that occur in real-time.
Ezra
The Ezra AI together with MRI technology helps identify the presence of cancer sooner and more precisely. The AI gives a more accurate 3D visualization of organs inside as well as segments scans of images to aid radiologists in identifying the presence of abnormalities.
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