Rapid Application Development Using Large Language Models (RADLLM)

 

Course Overview

Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities for businesses to streamline their operations, decrease expenses, and increase productivity at scale. Enterprises can also use LLM-powered apps to provide innovative and improved services to clients or strengthen customer relationships. For example, enterprises could provide customer support via AI virtual assistants or use sentiment analysis apps to extract valuable customer insights.

In this course, you’ll gain a strong understanding and practical knowledge of LLM application development by exploring the open-sourced ecosystem, including pretrained LLMs, that can help you get started quickly developing LLM-based applications.

Certifications

Prerequisites

  • Introductory deep learning, with comfort with PyTorch and transfer learning preferred. Content covered by DLI’s Getting Started with Deep Learning or Fundamentals of Deep Learning courses, or similar experience is sufficient.
  • Intermediate Python experience, including object-oriented programming and libraries. Content covered by Python Tutorial (w3schools.com) or similar experience is sufficient.

Course Objectives

By participating in this workshop, you’ll learn how to:

  • Find, pull in, and experiment with the HuggingFace model repository and the associated transformers API
  • Use encoder models for tasks like semantic analysis, embedding, question-answering, and zero-shot classification
  • Use decoder models to generate sequences like code, unbounded answers, and conversations
  • Use state management and composition techniques to guide LLMs for safe, effective, and accurate conversation

Follow On Courses

Prices & Delivery methods

Online Training

Duration
1 day

Price
  • on request
Classroom Training

Duration
1 day

Price
  • on request

Click on town name or "Online Training" to book Schedule

Instructor-led Online Training:   This is an Instructor-Led Online (ILO) course. These sessions are conducted via WebEx in a VoIP environment and require an Internet Connection and headset with microphone connected to your computer or laptop.
This is a FLEX course, which is delivered simultaneously in two modalities. Choose to attend the Instructor-Led Online (ILO) virtual session or Instructor-Led Classroom (ILT) session.

Europe

Germany

This is a FLEX course. Frankfurt Enroll
Online Training Time zone: Central European Time (CET) Enroll
Online Training Time zone: Central European Summer Time (CEST) Enroll

France

Online Training Time zone: Central European Time (CET) Enroll
Online Training Time zone: Central European Time (CET) Enroll
Online Training Time zone: Central European Summer Time (CEST) Enroll