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Maven Analytics – Intro to Neural Networks & Deep Learning 2025-10

Updated August 10, 2026 263 MB
Maven Analytics – Intro to Neural Networks & Deep Learning 2025-10

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Descriptions

Intro to Neural Networks & Deep Learning, Neural networks and deep learning are the foundation for modern Artificial Intelligence (AI), and key concepts for anyone curious about how tools like ChatGPT, image classifiers, or self-driving cars work. In this course, we’ll break down what neural networks are by introducing simple building blocks like weights, biases, and activation functions. You’ll learn how neural networks are structured using layers of interconnected nodes, and see how data flows through them to make predictions. From there, we’ll walk through the full model training process, including forward passes, loss functions, backpropagation, and gradient descent. Each concept is explained visually and intuitively, with just enough math to understand what’s happening under the hood.

Then, we’ll extend these ideas into the world of deep learning, introducing popular architectures like CNNs, RNNs, LSTMs, and Transformers, and showing how they’re used in real-world applications across computer vision and natural language processing (NLP). If you’re looking for a visual, no-code introduction to neural networks and deep learning, this is the course for you.

What you’ll learn

  • Intro to Neural Networks
  • Logistic Regression: Visually Explained
  • Neural Networks: Visually Explained

Who this course is for

  • Analysts, data scientists, or anyone curious about how AI models like ChatGPT actually work
  • Beginners who want an intuitive, visual introduction to neural networks and deep learning concepts
  • Anyone looking to build a strong conceptual foundation before diving into deep learning code

Specificatoin of Intro to Neural Networks & Deep Learning

Content of Intro to Neural Networks & Deep Learning

Intro to Neural Networks & Deep Learning

Requirements

  • No coding experience required
  • Basic high school math (like formulas for a line, weighted sums, etc.)
  • Some prior machine learning knowledge is helpful, but not necessary — we explain everything step-by-step with clear visuals

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Intro to Neural Networks & Deep Learning

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File size

263 MB