Udemy – Building LLM-Based Applications Using Instructor 2024-8

Course Building LLM-Based Applications Using Instructor. This course will teach you how to build programs based on Large Language Models (LLM) using the Python Instructor package. Instructor is a powerful tool that allows you to generate structured output from large language models. You can define your desired output structure and Instructor will automatically manage the internal logic to ensure that you get a response that matches that structure. This course will help you quickly and easily enrich your programs with LLM capabilities without the need for complex knowledge.

What you will learn

• Understanding the Basics of Instructor: You will learn the basic concepts of Instructor and understand how this tool can be useful in developing your applications.
• Developing Structured Output Definitions: You will learn how to define custom output structures for large language models.
• Comparing Instructor with similar libraries like LangChain: You will understand the differences between Instructor and other libraries like LangChain and why Instructor is a better choice for your projects.
• Using Instructor to create LLM-based programs: You will learn how to use Instructor to create LLM-based programs and learn best practices for effectively integrating it into your projects.

Who is this course suitable for?

• Python programmers: especially those interested in expanding their knowledge of building programs based on large language models. This course will help them use their existing Python skills to effectively integrate and manage LLM in their projects.
• Artificial Intelligence Engineers: Artificial Intelligence professionals who want to increase their practical knowledge in applying the LLM to software applications. This course provides hands-on experience and a thorough understanding of how to use the Instructor library to simplify the process of integrating LLM into complex systems.
• Software Developers: Developers looking to add advanced AI capabilities to their applications will benefit from this course. This course provides the tools and knowledge needed to effectively integrate LLM using the Instructor’s library and help them create AI-based solutions.
• Data Scientists and Machine Learning Specialists: People who typically work with data-driven models and are looking to explore LLM’s capabilities in generating structured outputs and automating responses based on large data sets.

Building LLM-Based Applications Using Instructor course specifications

• Publisher:  Udemy
• Lecturer: Franck Stéphane
• Training level: beginner to advanced
• Training duration: 1 hour and 19 minutes
• Number of courses: 8

Course headings

Building LLM-Based Applications Using Instructor prerequisites

• Python Proficiency: Students should possess a basic to intermediate understanding of Python programming, including familiarity with data structures (like lists and dictionaries), control flow (loops and conditional statements), functions, and basic error handling.
• API Interaction: A foundational knowledge of how to interact with APIs using Python, including making HTTP requests and handling JSON data, would be beneficial.
• Understanding of Object-Oriented Programming: Familiarity with object-oriented programming concepts in Python such as classes, objects, inheritance, and polymorphism is recommended as these are often used in structuring complex applications.
• Experience with JSON and Structured Data: Since Instructor deals with defining structured outputs, understanding how to manipulate JSON and other structured data formats will help in effectively using the library.

Course images

Sample video of the course

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