Generative AI and LLMs for Developers - How it Actually Works

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size255.2 MB
  • Uploaded Byfreecoursewb
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  • Last checkedAug. 08th '26
  • Date uploadedAug. 07th '26
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Infohash : 50DE276E2A998DEA04AC0DB822A2BA5F9F704243

Generative AI and LLMs for Developers: How it Actually Works

https://WebToolTip.com

Released 7/2026
With Laurence Moroney
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 1h 38m | Size: 255.2 MB

Explore the essentials of how generative AI really works, from transformers to diffusion models, without the math.

Course details
Generative AI tools like ChatGPT and Stable Diffusion can feel like magic, but under the hood, they follow clear and understandable patterns. In this course, instructor Laurence Moroney shows you how generative AI actually works, without getting lost in heavy math or academic theory. Break down the core building blocks of modern AI systems, including tokens, embeddings, attention, transformers, and diffusion models. Learn how text and images are generated step by step, from predicting the next token to transforming noise into visual content. By the end of this course, you’ll be equipped with a practical mental model for reasoning about how these systems behave, why they make certain mistakes, and how to work with them more effectively. This course is an ideal fit for software developers, engineers, technical product managers, and data professionals.

Skills covered
Large Language Models (LLM), Generative AI, Artificial Intelligence (AI), Artificial Intelligence Foundations

Files:

[ WebToolTip.com ] Generative AI and LLMs for Developers - How it Actually Works
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 01. Introduction
    • 01. Cracking open the generative AI black box.mp4 (3.1 MB)
    • 01. Cracking open the generative AI black box.srt (1.2 KB)
    02. 1. Framing the Landscape
    • 01. What generative actually means.mp4 (9.6 MB)
    • 01. What generative actually means.srt (5.8 KB)
    • 02. A very short history From n-grams to foundation models.mp4 (12.8 MB)
    • 02. A very short history From n-grams to foundation models.srt (7.0 KB)
    03. 2. How Text Becomes Math
    • 01. Tokens Turning text into integers.mp4 (9.3 MB)
    • 01. Tokens Turning text into integers.srt (6.0 KB)
    • 02. Embeddings Giving tokens meaning.mp4 (12.7 MB)
    • 02. Embeddings Giving tokens meaning.srt (6.3 KB)
    • 03. Vector space intuition.mp4 (12.5 MB)
    • 03. Vector space intuition.srt (6.3 KB)
    • 04. Positional encoding Teaching order to a bag of vectors.mp4 (11.7 MB)
    • 04. Positional encoding Teaching order to a bag of vectors.srt (6.6 KB)
    04. 3. Attention and the Transformer
    • 01. The core problem Context-dependent meaning.mp4 (10.4 MB)
    • 01. The core problem Context-dependent meaning.srt (5.9 KB)
    • 02. Attention in plain English.mp4 (13.2 MB)
    • 02. Attention in plain English.srt (7.7 KB)
    • 03. Self-attention Step by step.mp4 (12.5 MB)
    • 03. Self-attention Step by step.srt (6.9 KB)
    • 04. Multihead attention.mp4 (12.2 MB)
    • 04. Multihead attention.srt (6.6 KB)
    • 05. The full transformer block.mp4 (13.4 MB)
    • 05. The full transformer block.srt (8.0 KB)
    05. 4. Training and Generating Text
    • 01. Next-token prediction as a training objective.mp4 (12.7 MB)
    • 01. Next-token prediction as a training objective.srt (6.7 KB)
    • 02. Sampling How a probability distribution becomes text.mp4 (12.0 MB)
    • 02. Sampling How a probability distribution becomes text.srt (7.7 KB)
    • 03. From base model to assistant Fine-tuning and RLHF.mp4 (14.5 MB)
    • 03. From base model to assistant Fine-tuning and RLHF.srt (8.2 KB)
    06. 5. Diffusion Models
    • 01. A different problem Generating images.mp4 (10.5 MB)
    • 01. A different problem Generating images.srt (5.6 KB)
    • 02. The core idea Learn to denoise.mp4 (13.4 MB)
    • 02. The core idea Learn to denoise.srt (7.4 KB)
    • 03. The U-Net The workhorse behind the magic.mp4 (13.3 MB)
    • 03. The U-Net The workhorse behind the magic.srt (8.0 KB)
    • 04. Text-to-image Guiding diffusion with language.mp4 (11.5 MB)
    • 04. Text-to-image Guiding diffusion with language.srt (6.7 KB)
    • 05. Latent diffusion Why Stable Diffusion is fast.mp4 (13.4 MB)
    • 05. Latent diffusion Why Stable Diffusion is fast.srt (7.2 KB)
    07. Conclusion
    • 01. Putting it all together.mp4 (10.1 MB)
    • 01. Putting it all together.srt (6.2 KB)
    • 02. Where to go next.mp4 (10.2 MB)
    • 02. Where to go next.srt (5.5 KB)
    • Bonus Resources.txt (0.1 KB)

Code:

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