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AI Engineering track

Neural Networks

Networks, training loops and the mental model behind learned representations.

6 concepts3 labs
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Concepts

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Work through the concepts in order, or jump to what you need.

1

What a Neural Network Computes

Concept · Hands-on lab included

2

Activation Functions

Concept · Hands-on lab included

3

Backpropagation & Learning

Concept · Hands-on lab included

4

Overfitting & Regularization

Concept · Hands-on lab included

5

Loss Functions

Concept · Hands-on lab included

6

Training Loops & Optimization

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

Browse all labs

Forward Pass in Pure Python

30 min · intermediate · What a Neural Network Computes

Activations and the Vanishing-Gradient Trap

25 min · beginner · Activation Functions

Hand-Roll a Training Step

30 min · intermediate · Training Loops & Optimization

Continue

Next modules

Keep your learning streak going with related modules.

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Python

The Python skills AI engineering builds on — typing, async, packaging and testing.

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APIs

HTTP, REST, auth, rate limits, SDK patterns and API design for AI systems.

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Data Handling

Preparing documents, JSON, embeddings pipelines and data validation for AI.

DevOpsForge - AI Engineering · Neural Networks
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