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Llama 4: AI Mastering Prompt Engineering
Role Play
Rating: 4.0 out of 5(157 ratings)
16,157 students

Llama 4: AI Mastering Prompt Engineering

Build, optimize, and deploy Llama 4 with prompt engineering techniques using Google Colab and Hugging Face
Last updated 3/2026
English

What you'll learn

  • How Llama 4 works under the hood: architecture, tokenization, and attention
  • How to set up a working Llama 4 environment using Google Colab and Hugging Face
  • How to write powerful prompts—from zero-shot to few-shot examples
  • Techniques to control tone, style, and response length in AI outputs
  • How to troubleshoot prompt errors, repetition, and hallucinations
  • How to compare Llama 4 with GPT-4, Claude, and other leading LLMs
  • How to stay up to date with evolving LLM tools, communities, and research sources

Course content

6 sections20 lectures1h 32m total length
  • What is Llama 4? Model Sizes and Performance Explained3:06

    Learn what makes Llama 4 unique, how its open models differ by size.

  • Inside the Model — Tokenization, Attention, and Training Data3:25

    Discover how Llama 4 processes language—breaking text into tokens, focusing with attention, and learning from massive training data.

  • Llama 4 Multimodal Overview14:52

    Explore Llama 4’s ability to handle both text and image inputs, and understand how multimodal features expand its real-world applications.

  • What is difference of Llama 4 with previous models14:57

    Compare Llama 4 with earlier versions to see what’s improved—architecture, performance, context handling, and multimodal capabilities.

  • Getting Your Own Practical Companion1:40

    In this lesson, you'll get your own AI companion: the book "AI for Business".

  • How to Leave a Review for the Course?1:35

    Your feedback is crucial to me. Please share your thoughts on how I can improve this course for you.

  • How to Study on Udemy?2:15

    In this lesson, we'll walk you through the Udemy interface and show you how to get the most from your studies.

  • Get better educational experience with Udemy's AI Assistant6:13

    Smarter learning starts here and boost your progress with Udemy’s AI Assistant

Requirements

  • For this course you need Basic familiarity with Python (no advanced coding needed)
  • A free Google account to use Google Colab
  • No prior experience with Hugging Face or Llama 4 required—everything is taught step-by-step

Description

This course contains the use of artificial intelligence.

In today’s Generative AI-driven world, staying competitive, creative, and efficient requires more than surface-level tools—it demands a deep understanding of the models shaping our future. This course is built for developers, researchers, educators, and AI enthusiasts who want to master Meta’s Llama 4 model and gain real skills in prompt engineering and inference.

By integrating Llama 4 into your Generative AI workflow, you’ll unlock the ability to run open-weight models in Google Colab, generate high-quality outputs, and apply prompt strategies that maximize accuracy, relevance, and tone—whether you're writing, coding, or analyzing.

This course is designed for both theory and real-world application, delivering value through:

  • Bite-sized lessons optimized for clear learning

  • Step-by-step walkthroughs of setup, prompting, and output analysis

  • Lifetime access with updates for model versions and tooling

  • Actionable examples and guidance for using Generative AI models responsibly and effectively

  • A foundation in IT Fundamentals to support hands-on implementation and understanding

What You’ll Learn in This Course:

  • Set up and run Llama 4 using Hugging Face and Google Colab

  • Understand how tokenization, attention, and model architecture shape Generative AI outputs

  • Write effective zero-shot and few-shot prompts across use cases

  • Control tone, style, and length of LLM responses with precision

  • Troubleshoot misleading or failed outputs with prompt refinement

  • Compare Llama 4 with other Generative AI models like GPT-4, Claude, and Mistral

  • Apply ethical practices to avoid bias and manage hallucinations

  • Use temperature, top-k, and top-p to guide creativity and accuracy

  • Stay current with new model research, tools, and communities

  • Strengthen your command of IT Fundamentals through practical, AI-related examples

Who This Course Is For:

  • Developers and engineers working with open-source LLMs

  • AI enthusiasts, students, and researchers building foundational knowledge

  • Marketers and content creators who want smarter control over outputs

  • Business professionals exploring practical AI integration

  • Anyone interested in understanding Generative AI models and reinforcing their IT Fundamentals

What’s Included:

  • Colab-ready templates with reusable Python code

  • Real-world examples: summarization, content generation, coding

  • Prompt templates for marketing, education, and product use cases

  • Side-by-side comparisons of Llama 4 and proprietary LLMs

  • Certificate of completion to showcase your LLM expertise

Get Started Now!

Mastering Llama 4 isn’t just about copying code—it’s about understanding why it works and how to use it responsibly. This course gives you the theoretical foundation, technical tools, and hands-on practice to work with Llama 4 effectively and ethically.

Enroll today to sharpen your Generative AI skills, reinforce your IT Fundamentals, build smarter language model applications, and take your LLM projects from idea to execution.

Let’s learn more about Llama 4—join the course now!

This course contains a promotion.

Who this course is for:

  • AI enthusiasts and tech learners
  • Machine learning engineers and data scientists
  • Developers building LLM-powered apps
  • Educators creating AI-driven content