Free Course Download100% Free Direct MP4 LinksFrontend MastersAI, Machine Learning & Data Science2025-1 Edition

Download Hard Parts of AI: Neural Networks Course for Free

Download the complete Hard Parts of AI: Neural Networks video course for free with high-definition MP4 video lectures, project exercise archives, and step-by-step masterclasses. Learn offline at your own pace with zero paywalls or recurring subscriptions.

21Lectures

27.7Total Hours

5164.8MB Total Size

MP4 / 1080p HD

Instructor: Senior Industry Specialist

English

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Frontend Masters – Hard Parts of AI Neural Networks 2025-1_Materials.zip

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All Video Lectures Available to Download21 Videos

Direct high-speed MP4 downloads for every chapter.

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Introduction

MP4 HD37m•80.78 MB

Stream

Refund-Request-Filtering

MP4 HD1h 30m•259.88 MB

Stream

Creating-the-Data-Converter

MP4 HD1h 30m•272.64 MB

Stream

Applying-the-Data-Converter

MP4 HD1h 30m•253.98 MB

Stream

Challenges-in-Creating-a-Production-Model

MP4 HD1h 30m•379.35 MB

Stream

Boundaries-in-a-Decision-Model

MP4 HD1h 30m•388.93 MB

Stream

Neural-Network-Data

MP4 HD1h 30m•244.63 MB

Stream

Validating-Pixel-Data-Neural-Network

MP4 HD1h 30m•204.68 MB

Stream

Inferring-Using-the-Pixel-Data-Model

MP4 HD1h 30m•312.08 MB

Stream

Training-a-Pixel-Data-Model

MP4 HD1h 30m•362.26 MB

Stream

Improve-Accuracy-of-Model

MP4 HD1h 12m•158.67 MB

Stream

Learning-Multipliers-with-Larger-Sample

MP4 HD1h 30m•337.57 MB

Stream

Applying-All-Weight-Changes

MP4 HD1h 6m•146.21 MB

Stream

Applying-Gradient-Descent

MP4 HD1h 26m•189.17 MB

Stream

Sigmoid-Function

MP4 HD1h 30m•366.49 MB

Stream

Validating-Weight-Accuracy

MP4 HD1h 30m•383.37 MB

Stream

Preprocessing-Sample-Data

MP4 HD52m•113.67 MB

Stream

Combining-Models

MP4 HD36m•79.15 MB

Stream

Extending-the-Principles-of-Machine-Learning

MP4 HD1h 5m•142.45 MB

Stream

Developing-a-Production-Model

MP4 HD1h 30m•317.92 MB

Stream

Wrapping-Up

MP4 HD1h 18m•170.80 MB

Stream

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What You'll Master in this Free Download Course

How to use a basic understanding of models involved to make informed judgments in the software engineering profession

How to use data science and ML to build products using classical models that do not use neural networks

Principles behind neural networks (the main tool of deep learning) – data representation, weights and activations, gradient descent and backpropagation

Artificial Intelligence for the modern full-stack engineer

How LLMs are guided to generate text through pre-training and fine-tuning, and how to interact with LLMs in the most effective and efficient way

And…

About this Free Download Course

AI for Software Engineers is a practical knowledge course on Artificial Intelligence (AI) and its applications in software development published by FrontendMasters Online Academy. AI for Software Engineers is an advanced course designed to equip developers with a practical knowledge of Artificial Intelligence (AI) and its applications in software development. This course bridges the gap between AI and engineering by providing a deep understanding of core AI concepts, machine learning algorithms, and their integration into software projects. You will learn the nature of data, probability, training, and prediction in machine learning. You will then explore how to implement these principles in neural networks used in deep learning, including the core concepts of gradient descent and back propagation.You will then explore the how and why of using Large Language Models (LLMs) by understanding notation, embeddings, self-attention, pre-training, and fine-tuning, as well as the heuristics required to deliver reliable models. By understanding the basics of the tools involved, you can make informed judgments about how to integrate ML/AI models, communicate it within your teams, and gain a valuable edge in technical interviews.

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