750 Euro/ persoană + TVA

2 zile


Secure ChatGPT

AI (Artificial Intelligence)

In this two-day course, participants will delve into the world of large language models, with a specific focus on ChatGPT. The course covers a wide range of topics, from understanding the fundamental concepts and history of ChatGPT and GPT model family to exploring their applications and limitations, including ChatGPT alternatives.

Participants will learn how to use ChatGPT securely and responsibly in various industries and use cases from translation to software engineering, content creation, sentiment analysis and text summarization. They will understand how prompt engineering works and also work with various APIs for popular tasks.

Preț: 750 Euro/ persoană + TVA

Durată – 2 zile

Format: Online – Live cu instructor sau la sediul clientului

Prerechizite: No prerequisites needed for this course

Certificare: Certificat de absolvire

Audienta :

This Secure ChatGPT course is designed for:

Entrepreneurs and product managers who want to explore business opportunities and innovations related to NLP in various industries.
AI and Machine Learning enthusiasts interested in understanding large language models, specifically ChatGPT, and their practical applications.
Data Scientists and Data Analysts looking to incorporate ChatGPT in their projects and understand the potential risks and limitations.
Software Developers seeking to integrate ChatGPT and its functionalities into their applications securely and responsibly.
Business Analysts and Decision Makers who want to comprehend the potential impact of ChatGPT on their industry and explore its use cases.
Information Security Professionals responsible for ensuring data privacy and secure usage of AI technologies within their organizations.

Plan De Curs

Introduction to main concepts of Large Language Models and ChatGPT.

ChatGPT and GPT model family comparison: history, providers, licensing model, and data protection aspects.

Impact of using ChatGPT in different industries.

Use cases with ChatGPT: translation, code generation and debugging, content creation, summarization, sentiment analysis.

Prompts and prompt engineering in ChatGPT.

Approaches around prompt engineering: Standard, Role, Zero-shot, Few-shot, Chain of Thoughts.

Risks and limitations in using ChatGPT (including data privacy and security aspects).

Use case: A potential architecture for enterprise secure usage of ChatGPT.

Using the OpenAI and Azure Cognitive Services APIs: pros and cons, review of existing models.

Python examples of doing popular tasks using OpenAI API.

Exercise: Implementing a python app that converts meeting notes to summary using ChatGPT API.

How to implement anonymization and masking in Python.

Exercise: Implement an anonymization module in a ChatGPT connection.

Alternatives in using proprietary ChatGPT technology.

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