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Prompt Engineering with LLaMA-2 (NVIDIA) Course Overview

Prompt Engineering with LLaMA-2 (NVIDIA) Course Overview

Unlock the potential of LLaMA-2 with Koenig Solutions' Prompt Engineering with LLaMA-2 (NVIDIA) course. Designed for Python developers familiar with large language models like ChatGPT, this 4-hour course will enhance your ability to craft precise prompts and manage LLMs programmatically.

By the end of this course, you will be able to:

- Create precise prompts to align LLM behavior with your goals
- Edit powerful system messages effectively
- Utilize one-to-many shot prompt engineering
- Develop chatbot functionality incorporating prompt-response history

Practical exercises include building an AI-powered document analyst and an AI assistant, ideal for tasks like generating marketing copy and customer support.

Take this course and elevate your AI prompt engineering skills!

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Course Prerequisites

Minimum Required Prerequisites for Prompt Engineering with LLaMA-2 (NVIDIA) Course:


  1. Basic proficiency in Python programming.
  2. Familiarity with interacting with large language models, such as using ChatGPT.
  3. Understanding of fundamental machine learning concepts is beneficial but not mandatory.

Target Audience for Prompt Engineering with LLaMA-2 (NVIDIA)

Introduction:
Unlock advanced skills in prompt engineering with the LLaMA-2 model through Koenig Solutions' 4-hour course, perfect for Python developers enhancing their proficiency in interacting with large language models.


Target Audience and Job Roles:


  • Python Developers with basic experience in LLMs
  • Data Scientists
  • AI Researchers
  • Machine Learning Engineers
  • Software Developers
  • NLP Engineers
  • AI Product Managers
  • Technical Consultants
  • Freelance AI Developers
  • Digital Assistants Developers
  • AI Solutions Architects
  • Educators in AI/ML fields


Learning Objectives - What you will Learn in this Prompt Engineering with LLaMA-2 (NVIDIA)?

Introduction: Unleash the power of LLaMA-2 with prompt engineering in this 4-hour course designed for Python developers. Learn to precisely guide LLM behavior to perform tasks such as document analysis, text generation, and AI assistance.

Learning Objectives and Outcomes:

  • Iteratively write precise prompts to bring LLM behavior in line with your intentions.
  • Leverage editing the powerful system message.
  • Guide LLMs with one-to-many shot prompt engineering.
  • Incorporate prompt-response history into the LLM context to create chatbot behavior.
  • Familiarize yourself with the transformers pipeline and LLaMA-2 models.
  • Perform few-shot learning for tasks like product review analysis.
  • Build AI-powered tools for generative tasks, such as a marketing copy generator.
  • Enable sampling and control the temperature of the model's generation to create unique AI personalities.
  • Develop chatbot functionality capable of retaining conversation history.
  • Work with a model's token limits to develop practical AI assistants.

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