- Basic programming knowledge
Audience
- Technical teams
- AI developers
- Chatbot designers
OpenAI is an artificial intelligence research organization and technology company that aims to ensure that artificial general intelligence (AGI) benefits all of humanity. It develops and promotes AI technologies, including advanced machine learning models and language models, to solve a variety of tasks.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers who wish to advance their skills in creating chatbot flows for retail applications using OpenAI.
By the end of this training, participants will be able to:
- Understand the principles of conversational AI and chatbot flow design.
- Identify user intents and extract entities using NLP techniques.
- Integrate OpenAI-based models with WhatsApp and retail ERP systems.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction
Conversational AI and Chatbot Design Basics
- Overview of conversational AI
- Principles of chatbot flow design
- Retail-specific chatbot use cases
Understanding NLP Concepts
- NLP fundamentals: tokenization, lemmatization, stemming
- Techniques for intent recognition
- Named Entity Recognition (NER) and its importance in retail
OpenAI and Language Models Overview
- Introduction to OpenAI and GPT models
- Use cases for retail chatbot development
- Overview of integrating language models with chatbot platforms
Developing Chatbot Flows Using OpenAI
- Designing a flowchart for common retail scenarios
- Creating prompt templates for intent recognition
- Fine-tuning GPT models for retail-specific intents
Integrating Chatbots with WhatsApp and Working with Pinecone
- Configuring WhatsApp integration for customer queries
- Implementing Pinecone for vector search and semantic search capabilities
Customizing Responses and Enhancing Accuracy
- Techniques for training and fine-tuning OpenAI models
- Using feedback loops to improve intent recognition
- Incorporating contextual understanding and memory
Testing, Evaluation, and Continuous Improvement
- Strategies for testing chatbot flows
- Evaluating performance metrics (accuracy, response time, user satisfaction)
- Iterating on chatbot design for continuous improvement
Summary and Next Steps