Some indications you’ll be a great fit include:The ability to break down problems into logical parts and generate and test hypothesesWillingness to try out many different solutionsHigh attention to detailBroadly good quantitative skills
- No location available
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Course Report is a great guide to choosing a bootcamp. Be careful to avoid low-quality bootcamps. To find out more, read our interview with an App Academy instructor.
- No location available
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But if that’s not possible, here are some suggestions of places you might start if you want to self-study the basics:3blue1brown’s series on neural networks is a really great place to start for beginners.When I was learning, I used Neural Networks and Deep Learning — it’s an online textbook, good if you’re familiar with the maths, with some helpful exercises as well.You can do online intro courses like fast.ai (focused on practical applications), Full Stack Deep Learning, and the various courses at deeplearning.ai.For more detail, see university courses like MIT’s Introduction to Machine Learning, and NYU’s Deep Learning for even more detail. We’d also recommend Google DeepMind’s lecture series.
- No location available
- artificial intelligence (ai), neural networks, 1resource/course, deep learning,

PyTorch is a very common package used for implementing neural networks, and probably worth learning! When I was first learning about ML, my first neural network was a 3-layer convolutional neural network with L2 regularisation classifying characters from the MNIST database. This is a pretty common first challenge and a good way to learn PyTorch.
- No location available
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Probability: Take a look at MIT’s undergraduate course in probability and random variables.
- No location available
-

We’ve written about some other relevant skill sets:How to get started building research skillsHow to get started building specialist knowledge relevant to a pressing problemHow to get started building skills for communicating ideas
- No location available
-

Some indications you’ll be a great fit include:The ability to break down problems into logical parts and generate and test hypothesesWillingness to try out many different solutionsHigh attention to detailBroadly good quantitative skills
- No location available
-

Course Report is a great guide to choosing a bootcamp. Be careful to avoid low-quality bootcamps. To find out more, read our interview with an App Academy instructor.
- No location available
-

But if that’s not possible, here are some suggestions of places you might start if you want to self-study the basics:3blue1brown’s series on neural networks is a really great place to start for beginners.When I was learning, I used Neural Networks and Deep Learning — it’s an online textbook, good if you’re familiar with the maths, with some helpful exercises as well.You can do online intro courses like fast.ai (focused on practical applications), Full Stack Deep Learning, and the various courses at deeplearning.ai.For more detail, see university courses like MIT’s Introduction to Machine Learning, and NYU’s Deep Learning for even more detail. We’d also recommend Google DeepMind’s lecture series.
- No location available
- artificial intelligence (ai), neural networks, 1resource/course, deep learning,

PyTorch is a very common package used for implementing neural networks, and probably worth learning! When I was first learning about ML, my first neural network was a 3-layer convolutional neural network with L2 regularisation classifying characters from the MNIST database. This is a pretty common first challenge and a good way to learn PyTorch.
- No location available
-

Probability: Take a look at MIT’s undergraduate course in probability and random variables.
- No location available
-

We’ve written about some other relevant skill sets:How to get started building research skillsHow to get started building specialist knowledge relevant to a pressing problemHow to get started building skills for communicating ideas
- No location available
-