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How To Start a Career In Artificial Intelligence In 2019? A Step by Step Guide

artificial intelligence, machine learning, programming languages, r programming language, python

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, terrifying yet interesting. Unlike other technologies, we will continue to see the advancements of AI and ML in 2019 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.

Stating that organizations across all sectors are embracing AI and ML, it is evident that professionals skilled in these technologies will be in huge demand over the coming years. But according to a survey from O’Reilly, there is a dearth for talent in AI skills and is the largest barrier to AI adoption. The major concern for 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 who can change their skills over time.

A career in artificial intelligence is not one size that fits all. So, if you’re looking to start a career in artificial intelligence, here’s a guide that you need to 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. The aim of AI is to build machines that can think, behave, and understand the way humans do. Learn more at artificiell intelligens.

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 artificial engineer. Artificial intelligence engineer is one of the most prominent job role 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
    • Finance
    • Economics

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.

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.

The Skills Required

A roadmap 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.

Technical Skills

  • 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 is 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. Which 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 to of approaching problems like speech recognition, image classification, and translation.

Non-Technical Skills

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

Having 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 conclusions that are insightful.

With the emergence of AI, every sector is now looking to implement artificial intelligence making the demand for professionals 2x higher. Additionally, with more professionals looking to upgrade themselves for the new-age tech jobs, there are many online programs and online training institutes that are providing AI certification, AI engineer certification and machine learning certification etc.

Based on the learning level and the requirements that best suit the candidate, one can learn and get certified from any one of the resources below:

  • Simplilearn

This course offers a broad understanding of the fundamentals of artificial intelligence. The course focuses on skills like ML, AI concepts, TensorFlow, and programming languages required for designing intelligent agents.

  • Artificial Intelligence Board of America – ARTIBA

The credentials offered by this program is designed to certify professionals having skills like cognitive ability and machine learning intelligence. The resources and learning coursework is proven to be the most credible and authentic across industries worldwide. The AI certification taken from this resource is considered trustworthy with a higher probability of job opportunities. 

  • MIT – Artificial Intelligence

MIT has partnered with an e-learning platform GetSmarter to come up with an understanding of how AI is and the impact it will have on businesses. They follow a similar pattern to the certificate offered by MIT Fintech.

Sohel Ather

Author Bio: Sohel Ather is a Senior Software Engineer and a content writer by passion, He enjoys exploring the latest software development technologies and taking on new challenges. 



More on this topic: Some Game-Changing Database Trends to Expect in 2019


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