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Empowering the Next Generation of AI Innovators with Arm Education

Rachael Horsman
3 minute read time.

Artificial intelligence (AI) is no longer a futuristic concept. It shapes how we live, learn, and work today. As AI tools become more embedded in everyday life, demand for AI skills is growing across industries. AI capabilities, such as building smarter apps, automating routine tasks, or interpreting complex datasets, are now essential for anyone entering the tech workforce and beyond. Learners must understand how AI works. They must also gain the practical skills to apply it meaningfully.

A challenge facing educators right now is how to prepare future generations for this. Technology is evolving too quickly for school curricula to keep up, especially AI. The impact of changing, adapting, or extending a curriculum is significant. Teaching resources, programs of study, and assessments all need to reflect any developments. Teachers themselves need upskilling. Equipment, such as higher-powered computing systems, must also be updated.

This is even more important when you are working with key examination years. (I)GCSEs in year 11 (16-year-olds) in the UK system, or SATs and AP in 11th and 12th grades (17-19-year-olds) in the US system. The results of which help decide the route a learner may follow.

Industry has both a responsibility and an opportunity to step up and support education. Arm is an excellent example of this.

The Arm Education and Academic Engagements Team enables learners to be as informed and engaged as possible in their future careers, particularly in STEM. The team partners with educators worldwide and Arm engineers to create learning content that bridges the gap between curriculum content and current technological activity.

That is why we have developed a new course, Introduction to AI. Now available on both EdX and Coursera. It is a valuable resource for students, educators, and early-career developers alike.

Enrol now on our new free-to-access course, Introduction to AI, on EdX or Coursera

Enroll through EdX Enroll through Coursera

A young woman, talking with images to the right of her of three scatter graphs each showing a a trend line, one with good fit, the other an overfit and an underfit, illustrating the different types of model fitting in machine learning using scatter plots and trend line

A young man, talking with an image to the right of him showing a section of Python code, featuring imports from the TensorFlow and Keras libraries, and a basic model architecture using dense layers.

The course bridges the gap between ‘academic’ computer science and real-world AI application, with a strong focus on practical implementation using Python and common frameworks like PyTorch. The learning is embedded in real-world contexts and encourages hands-on experimentation with code. It doesn’t assume prior expertise in machine learning but builds up key knowledge gradually. Topics covered include:

  • The turbulent history of AI and its evolution into today’s powerful technology  
  • How AI, machine learning, and data science fit together, including their definitions, examples, and interrelationship 
  • Current and potential future applications of AI in various industries 
  • Fundamental machine learning concepts, including classifiers, linear regression, and neural networks 
  • Training, validation, and test data: how to prepare and evaluate machine learning models 
  • Optimizers and loss functions: building blocks for fine-tuning your models 
  • Ethical and social considerations: exploring AI’s benefits, challenges, and the importance of responsible development 
  • Power consumption vs. sustainability: balancing performance and efficiency with environmental impact 
  • Practical frameworks, such as PyTorch, for implementing and training ML models 
  • AI in the cloud and on the edge: deploying AI across diverse platforms and computing environments 

Providing an accessible yet rigorous journey into a field that is transforming everything from healthcare to transportation the course is perfect for learners aiming to strengthen their computer science foundational knowledge. Educators can use this course as a scaffold to introduce AI concepts in the classroom, supplement independent learning, or inspire capstone projects that showcase student creativity and problem-solving.

Arm Education’s courses are used by over 100,000 learners from 160+ countries. Introduction to AI is part of our AI/ML learning pathway a curated suite of courses addressing the full spectrum of learning, from foundational AI and ML literacy to advanced deployment of generative AI workloads on Arm-based platforms. Learn more here.

Visit Arm Education to find out more about our educational courses and resources.

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