Career Spotlight: AI Engineer [VIDEO]

Written by Coursera Staff • Updated on

Imagine shaping the future of technology. That's the power of an AI Engineer - the brilliant minds behind self-driving cars, personalized recommendations, and so much more!


[Thumbnail] Career Spotlight: AI Engineer

Imagine being at the forefront of technological innovation — that's the world of an AI engineer. These modern-day wizards develop the tools and systems that bring artificial intelligence to life in the real world.

As an AI engineer, you’ll build intelligent applications using machine learning techniques like training algorithms with data to mimic human reasoning and decision-making. From personalizing streaming services to powering self-driving cars, the possibilities are endless.

With AI projected to contribute over $15 trillion to the global economy by 2030, the demand for AI talent is skyrocketing. This fast-growing field offers an average salary over $115,000 in the US alone.  

So if you’re a problem solver with a passion for coding and analytics, a career as an AI engineer could be your calling. Gain skills in programming, data frameworks, and algorithms through online courses, and get ready to shape the future of intelligent technology.

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IBM AI Engineering

Get job-ready as an AI engineer . Build the AI engineering skills and practical experience you need to catch the eye of an employer in less than 4 months. Power up your resume!

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Skills you'll build:

Machine Learning, PyTorch (Machine Learning Library), Generative AI, Supervised Learning, Data Science, Reinforcement Learning, Regression Analysis, Data Manipulation, Natural Language Processing, Image Analysis, Tensorflow, Large Language Modeling, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Generative AI Agents, Prompt Engineering, Unsupervised Learning, Applied Machine Learning, Deep Learning, Python Programming, User Interface (UI), Data Import/Export, Application Development, Data Processing, Database Management Systems, Data Storage Technologies, Artificial Neural Networks, Network Architecture, Machine Learning Methods, Network Model, Computer Vision, Dimensionality Reduction, Classification And Regression Tree (CART), Machine Learning Algorithms, Feature Engineering, Predictive Modeling, Statistical Analysis, Verification And Validation, Scientific Visualization, Probability & Statistics, Statistical Methods, Data Ethics, Semantic Web, Text Mining, Data Pipelines, Artificial Intelligence, Performance Tuning, Time Series Analysis and Forecasting, Artificial Intelligence and Machine Learning (AI/ML), Probability Distribution, ChatGPT, OpenAI

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