How To Become An AI Engineer in 2024?

Artificial Intelligence (AI) is reshaping businesses in different industries left and right. With AI, automation is coming to the forefront and even taking the steering wheel for the future. Rising automation means enhanced need for skilled professionals and one such is an AI engineer. Who are they and how to become an AI engineer?

Who Is An AI Engineer?

An AI engineer is a professional with expertise in AI and ML (machine learning) technologies. They design, implement and develop AI models, algorithms and systems to untangle complex business problems. Many tasks that earlier required human knowledge and intelligence can now be done automatically by implementing AI. With passing time, artificial intelligence bots are becoming more human-like.

The AI market size globally is expected to close at $305.9 billion by the end of this year. By 2030, it's projected to touch $738.8 billion, which is more than the combined number expected for app development ($225 billion) and ML ($328 billion).

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How To Become An AI Engineer?

Becoming an AI engineer means earning necessary skills and knowledge. Meeting the educational prerequisites and getting trained are also imperative steps to get started in this journey. Fulfill these pointers to commence a successful trend in this area.

Fulfill Qualification/ Educational Requirements

Since the field of AI is still in its development phase, not a lot of things are fixed. Nonetheless, it's important to belong to a related educational background in the tech space. Bachelor's degree in computer engineering, data science, IT or statistics is the basic requirement.

Gain Essential Technical Skills

As an artificial intelligence engineer, there are certain tech skills that must be earned and polished.

• Programming Skills- Prowess in top programming languages like Python, Java, C++, R, etc. is crucial to build and implement models.
• Spark & Big Data Technologies- Working with big data means having knowledge about its related technologies and tools is a must. Apache Spark, Cassandra, MongoDB and Hadoop are the top ones to learn.
• Probability, Statistics & Linear Algebra- There are different AI models like Naive Bayes, linear discriminant analysis, Hidden Markov models and Gaussian mixture models. To understand and implement them, knowledge of statistics, probability and linear algebra is crucial.
• Algorithms & Frameworks- It's important to understand both ML and deep learning models. To do so, knowledge of frameworks like TensorFlow, PyTorch, Caffe, etc. is needed.

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Gain Essential Soft Skills

There are many essential soft skills that must be learned. These skills are highly basic these days and play an important role even when it comes to passing the interview.

• Communication skills
• Domain expertise
• Problem-solving skills
• Critical thinking
• Teamwork
• Time management
• Business intelligence

AI Engineer Training

As mentioned already in this blog, artificial intelligence is still in its early phases. Despite being around for so long, it's only now that it's growing with no signs of stopping in sight. It's important to take the help of industry professionals to understand its current state and future possibilities, which is only possible with a training course.

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