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Ahmad Varasteh
In this 2-hour project, you'll learn how to fine-tune the GPT-3.5 model using the OpenAI API in Python. You are an AI engineer employed by PulseNet, a telecommunications company that provides internet, television, and phone services. PulseNet operates with a large customer base and manages a substantial volume of daily inquiries, support requests, and product reviews. The company has received numerous complaints from customers, expressing dissatisfaction. PulseNet's objective is to enhance customer satisfaction by analyzing customer complaints more regularly to address and fix issues regarding their services. They require a Large Language model capable of extracting specific details from each complaint, including the topic, problem, and customer dissatisfaction index in real-time. This dissatisfaction index will range between 0 and 100, representing the level of customer anger derived from the complaint text. PulseNet has provided a dataset containing the latest 50 user complaints along with the extracted information in the desired format. Your role as an AI engineer is to use the OpenAI API and Python to fine-tune the GPT-3.5 model and retrain a new large language model (LLM) that is capable of extracting the necessary information from a given customer complaint in the desired format.
Read more
In this 2-hour project, you'll learn how to fine-tune the GPT-3.5 model using the OpenAI API in Python. You are an AI engineer employed by PulseNet, a telecommunications company that provides internet, television, and phone services. PulseNet operates with a large customer base and manages a substantial volume of daily inquiries, support requests, and product reviews. The company has received numerous complaints from customers, expressing dissatisfaction. PulseNet's objective is to enhance customer satisfaction by analyzing customer complaints more regularly to address and fix issues regarding their services. They require a Large Language model capable of extracting specific details from each complaint, including the topic, problem, and customer dissatisfaction index in real-time. This dissatisfaction index will range between 0 and 100, representing the level of customer anger derived from the complaint text. PulseNet has provided a dataset containing the latest 50 user complaints along with the extracted information in the desired format. Your role as an AI engineer is to use the OpenAI API and Python to fine-tune the GPT-3.5 model and retrain a new large language model (LLM) that is capable of extracting the necessary information from a given customer complaint in the desired format.
Read more
In this 2-hour project, you'll learn how to fine-tune the GPT-3.5 model using the OpenAI API in Python. You are an AI engineer employed by PulseNet, a telecommunications company that provides internet, television, and phone services. PulseNet operates with a large customer base and manages a substantial volume of daily inquiries, support requests, and product reviews. The company has received numerous complaints from customers, expressing dissatisfaction. PulseNet's objective is to enhance customer satisfaction by analyzing customer complaints more regularly to address and fix issues regarding their services. They require a Large Language model capable of extracting specific details from each complaint, including the topic, problem, and customer dissatisfaction index in real-time. This dissatisfaction index will range between 0 and 100, representing the level of customer anger derived from the complaint text. PulseNet has provided a dataset containing the latest 50 user complaints along with the extracted information in the desired format. Your role as an AI engineer is to use the OpenAI API and Python to fine-tune the GPT-3.5 model and retrain a new large language model (LLM) that is capable of extracting the necessary information from a given customer complaint in the desired format.
To get the most out of this course, you'll need access to the OpenAI API Key and a basic understanding of data analysis concepts, including data types, and data manipulation, along with some familiarity with Python. This course is for those who are experienced data analysts with at least a basic knowledge of Python and want to explore the exciting applications of generative AI in data analysis.
Register for this course and see more details by visiting:
OpenCourser.com/course/8apjr2/genai
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What's inside
Syllabus
Project Overview
In this 2-hour project, you'll learn how to fine-tune the GPT-3.5 model using the OpenAI API in Python. You are an AI engineer employed by PulseNet, a telecommunications company that provides internet, television, and phone services. PulseNet operates with a large customer base and manages a substantial volume of daily inquiries, support requests, and product reviews. The company has received numerous complaints from customers, expressing dissatisfaction. PulseNet's objective is to enhance customer satisfaction by analyzing customer complaints more regularly to address and fix issues regarding their services. They require a Large Language model capable of extracting specific details from each complaint, including the topic, problem, and customer dissatisfaction index in real-time. This dissatisfaction index will range between 0 and 100, representing the level of customer anger derived from the complaint text. PulseNet has provided a dataset containing the latest 50 user complaints along with the extracted information in the desired format.
Your role as an AI engineer is to use the OpenAI API and Python to fine-tune the GPT-3.5 model and retrain a new large language model (LLM) that is capable of extracting the necessary information from a given customer complaint in the desired format.
To get the most out of this course, you'll need access to the OpenAI API Key and a basic understanding of data analysis concepts, including data types, data manipulation, along with some familiarity with Python. This course is for those who are experienced data analysts with at least a basic knowledge in Python and want to explore the exciting applications of generative AI in data analysis.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Exploitation of GPT 3.5, a state-of-the-art AI language model that achieves human-like text generation and manipulation
Course targeted at those with basic Python knowledge and data analysis concepts seeking to apply generative AI in their work
Data extraction, analysis, and model training from customer complaints to enhance customer satisfaction
Step-by-step guidance on OpenAI API integration and GPT-3.5 model fine-tuning in Python
Prerequisites include basic Python knowledge and familiarity with data analysis techniques
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in GenAI For Business Analysis: Fine-Tuning LLMs with these
activities:
General Data Analysis Concepts
Show steps
Refresh your understanding of the data analysis concepts, data types, and data manipulation techniques used in this course to enhance your fluency in working with data.
Browse courses on
Data Types
Show steps
-
Review lecture notes or textbooks on data analysis concepts
-
Complete online tutorials or exercises on data analysis
-
Practice working with different data types and data manipulation techniques
Review Python Basics
Show steps
Refresh your understanding of Python basics to build a strong foundation for the course.
Browse courses on
Object-Oriented Programming
Show steps
-
Go through your notes or study materials on Python basics.
-
Complete practice questions or exercises to test your understanding.
-
Review online resources, such as tutorials or documentation, to reinforce your knowledge.
GPT-3.5 API Introduction and Overview
Show steps
Review the basics of the GPT-3.5 model to help provide a foundation when working with it throughout the course.
Browse courses on
GPT-3.5
Show steps
-
Visit OpenAI website
-
Read the GPT-3.5 documentation
-
Watch the OpenAI GPT-3.5 tutorial videos
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Python Coding Exercises
Show steps
Practice writing Python code to improve your fluency in the language.
Browse courses on
Python
Show steps
-
Find a set of Python coding exercises.
-
Solve the exercises, referring to the GPT-3.5 model for guidance when needed.
Review 'Natural Language Processing with Python'
Show steps
Reviewing the introductory chapters will help you with the theoretical concepts of NLP prior to taking the course.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Read Chapters 1-3
-
Make notes on key NLP concepts
Fine-tune GPT-3.5 with OpenAI API in Python
Show steps
This activity will help you gain hands-on experience in fine-tuning the GPT-3.5 model using OpenAI API in Python.
Browse courses on
Python
Show steps
-
Set up your OpenAI account
-
Install the OpenAI Python library
-
Load the GPT-3.5 model
-
Fine-tune the GPT-3.5 model
-
Evaluate the fine-tuned model
Peer Review: Fine-tuning GPT-3.5 Models
Show steps
Exchange feedback with your peers to refine your understanding of fine-tuning GPT-3.5 models.
Browse courses on
Peer Review
Show steps
-
Find a peer review group
-
Share your work with your peer review group
-
Provide feedback to your peers' work
-
Incorporate feedback into your own work
-
Repeat the process until you are satisfied with your work
GPT-3.5 Tutorial
Show steps
Create a tutorial explaining the basics of GPT-3.5 and how to use it for text generation tasks.
Browse courses on
Large Language Models
Show steps
-
Gather information about GPT-3.5 and its capabilities.
-
Write the tutorial, providing clear and concise instructions.
-
Test the tutorial to ensure it is easy to follow.
GPT-3.5 Fine-tuning Workshop
Show steps
Attend a workshop to learn more about fine-tuning GPT-3.5 and how to apply it to your projects.
Browse courses on
GPT-3.5
Show steps
-
Search for upcoming GPT-3.5 fine-tuning workshops
-
Register for a workshop
-
Attend the workshop
-
Complete any assignments or exercises
-
Network with other participants
NLP Workshop
Show steps
Attend an NLP workshop to learn advanced techniques for working with text data.
Browse courses on
Natural Language Processing
Show steps
-
Find an NLP workshop that aligns with your interests.
-
Register for the workshop and attend all sessions.
-
Actively participate in discussions and exercises.
Advanced Techniques for Fine-tuning GPT-3.5
Show steps
Explore advanced techniques for fine-tuning GPT-3.5 to enhance its performance on your specific tasks.
Browse courses on
Advanced Techniques
Show steps
-
Identify the specific tasks you want to fine-tune GPT-3.5 for
-
Research advanced fine-tuning techniques
-
Apply the advanced fine-tuning techniques to your GPT-3.5 model
-
Evaluate the performance of your fine-tuned GPT-3.5 model
-
Refine your fine-tuning techniques based on the evaluation results
Contribute to OpenAI GPT-3.5 Ecosystem
Show steps
Contribute to the OpenAI GPT-3.5 ecosystem by reporting bugs, writing documentation, contributing code, or managing community.
Browse courses on
OpenAI
Show steps
-
Explore the OpenAI GPT-3.5 ecosystem
-
Identify areas where you can contribute
-
Start contributing to the OpenAI GPT-3.5 ecosystem
-
Get involved in the OpenAI GPT-3.5 community
-
Stay updated on the latest developments in the OpenAI GPT-3.5 ecosystem
General Data Analysis Concepts
Show steps
Refresh your understanding of the data analysis concepts, data types, and data manipulation techniques used in this course to enhance your fluency in working with data.
Browse courses on
Data Types
Show steps
Show steps
Show steps
- Review lecture notes or textbooks on data analysis concepts
- Complete online tutorials or exercises on data analysis
- Practice working with different data types and data manipulation techniques
Review Python Basics
Show steps
Refresh your understanding of Python basics to build a strong foundation for the course.
Browse courses on
Object-Oriented Programming
Show steps
Show steps
Show steps
- Go through your notes or study materials on Python basics.
- Complete practice questions or exercises to test your understanding.
- Review online resources, such as tutorials or documentation, to reinforce your knowledge.
GPT-3.5 API Introduction and Overview
Show steps
Review the basics of the GPT-3.5 model to help provide a foundation when working with it throughout the course.
Browse courses on
GPT-3.5
Show steps
Show steps
Show steps
- Visit OpenAI website
- Read the GPT-3.5 documentation
- Watch the OpenAI GPT-3.5 tutorial videos
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Python Coding Exercises
Show steps
Practice writing Python code to improve your fluency in the language.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a set of Python coding exercises.
- Solve the exercises, referring to the GPT-3.5 model for guidance when needed.
Review 'Natural Language Processing with Python'
Show steps
Reviewing the introductory chapters will help you with the theoretical concepts of NLP prior to taking the course.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3
- Make notes on key NLP concepts
Fine-tune GPT-3.5 with OpenAI API in Python
Show steps
This activity will help you gain hands-on experience in fine-tuning the GPT-3.5 model using OpenAI API in Python.
Browse courses on
Python
Show steps
Show steps
Show steps
- Set up your OpenAI account
- Install the OpenAI Python library
- Load the GPT-3.5 model
- Fine-tune the GPT-3.5 model
- Evaluate the fine-tuned model
Peer Review: Fine-tuning GPT-3.5 Models
Show steps
Exchange feedback with your peers to refine your understanding of fine-tuning GPT-3.5 models.
Browse courses on
Peer Review
Show steps
Show steps
Show steps
- Find a peer review group
- Share your work with your peer review group
- Provide feedback to your peers' work
- Incorporate feedback into your own work
- Repeat the process until you are satisfied with your work
GPT-3.5 Tutorial
Show steps
Create a tutorial explaining the basics of GPT-3.5 and how to use it for text generation tasks.
Browse courses on
Large Language Models
Show steps
Show steps
Show steps
- Gather information about GPT-3.5 and its capabilities.
- Write the tutorial, providing clear and concise instructions.
- Test the tutorial to ensure it is easy to follow.
GPT-3.5 Fine-tuning Workshop
Show steps
Attend a workshop to learn more about fine-tuning GPT-3.5 and how to apply it to your projects.
Browse courses on
GPT-3.5
Show steps
Show steps
Show steps
- Search for upcoming GPT-3.5 fine-tuning workshops
- Register for a workshop
- Attend the workshop
- Complete any assignments or exercises
- Network with other participants
NLP Workshop
Show steps
Attend an NLP workshop to learn advanced techniques for working with text data.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find an NLP workshop that aligns with your interests.
- Register for the workshop and attend all sessions.
- Actively participate in discussions and exercises.
Advanced Techniques for Fine-tuning GPT-3.5
Show steps
Explore advanced techniques for fine-tuning GPT-3.5 to enhance its performance on your specific tasks.
Browse courses on
Advanced Techniques
Show steps
Show steps
Show steps
- Identify the specific tasks you want to fine-tune GPT-3.5 for
- Research advanced fine-tuning techniques
- Apply the advanced fine-tuning techniques to your GPT-3.5 model
- Evaluate the performance of your fine-tuned GPT-3.5 model
- Refine your fine-tuning techniques based on the evaluation results
Contribute to OpenAI GPT-3.5 Ecosystem
Show steps
Contribute to the OpenAI GPT-3.5 ecosystem by reporting bugs, writing documentation, contributing code, or managing community.
Browse courses on
OpenAI
Show steps
Show steps
Show steps
- Explore the OpenAI GPT-3.5 ecosystem
- Identify areas where you can contribute
- Start contributing to the OpenAI GPT-3.5 ecosystem
- Get involved in the OpenAI GPT-3.5 community
- Stay updated on the latest developments in the OpenAI GPT-3.5 ecosystem
Career center
Learners who complete GenAI For Business Analysis: Fine-Tuning LLMs will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to extract insights that can help businesses make better decisions. This course can help you develop the skills you need to succeed as a Data Analyst, including data analysis, data visualization, and machine learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. This course can help you develop the skills you need to succeed as a Machine Learning Engineer, including machine learning algorithms, natural language processing and deep learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Data Scientist
Data Scientist
Data Scientists analyze data to extract insights and trends that can help businesses make better decisions. This course can help you develop the skills you need to succeed as a Data Scientist, including data analysis, data visualization, and machine learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Business Analyst
Business Analyst
Business Analysts analyze business needs and develop solutions to improve business processes. This course can help you develop the skills you need to succeed as a Business Analyst, including data analysis, data visualization, and machine learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers develop and maintain Natural Language Processing models. This course can help you develop the skills you need to succeed as a Natural Language Processing Engineer, including natural language processing, deep learning, and machine learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help you develop the skills you need to succeed as a Software Engineer, including programming, data structures, and algorithms. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Product Manager
Product Manager
Product Managers develop and manage products. This course can help you develop the skills you need to succeed as a Product Manager, including product management, market research, and customer feedback. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
UX Researcher
UX Researcher
UX Researchers study how users interact with products and services. This course can help you develop the skills you need to succeed as a UX Researcher, including user research, research methods, and data analysis. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze data and make predictions. This course can help you develop the skills you need to succeed as a Quantitative Analyst, including data analysis, machine learning, and financial modeling. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course can help you develop the skills you need to succeed as a Data Engineer, including data engineering, data warehousing, and data visualization. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course can help you develop the skills you need to succeed as a Financial Analyst, including financial analysis, valuation, and portfolio management. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical methods to solve business problems. This course can help you develop the skills you need to succeed as an Operations Research Analyst, including data analysis, optimization, and simulation. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course can help you develop the skills you need to succeed as a Project Manager, including project management, risk management, and stakeholder management. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks. This course can help you develop the skills you need to succeed as a Risk Analyst, including risk management, data analysis, and financial modeling. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, and interpret data to help businesses make better decisions. This course can help you develop the skills you need to succeed as a Business Intelligence Analyst, including data analysis, data visualization, and machine learning. The course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
For more career information including salaries, visit:
OpenCourser.com/course/8apjr2/genai
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
GenAI For Business Analysis: Fine-Tuning LLMs.
Save
Provides a comprehensive overview of generative adversarial networks (GANs), including their theory, architecture, and applications. It is written by the creators of GANs and is considered a foundational text on the subject.
Provides a thorough introduction to deep learning concepts and techniques using Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks, making it a valuable resource for readers who want to dive deeper into deep learning.
Save
Specifically focuses on text mining using R. It covers a wide range of NLP techniques and applications, including text classification, sentiment analysis, and topic modeling, making it a valuable resource for readers who want to apply NLP to text data.
Provides a comprehensive introduction to machine learning concepts and techniques using Python. It covers a wide range of topics, including data preprocessing, model selection, and evaluation, making it a valuable resource for readers who want to build a strong foundation in machine learning.
Provides a comprehensive introduction to machine learning using R. It covers a wide range of topics, including data preprocessing, model selection, and evaluation, making it a valuable resource for readers who want to build machine learning models using R.
Provides a concise and accessible introduction to machine learning concepts and algorithms. It is written in a clear and engaging style and is suitable for readers with little or no prior knowledge of machine learning.
Non-technical introduction to machine learning. It covers the basics of machine learning in a clear and easy-to-understand way, making it a good starting point for readers who are new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8apjr2/genai
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Effort
2 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Ahmad Varasteh
Language
English
Good to know
Exploitation of GPT 3.5, a state-of-the-art AI language model that achieves human-like text generation and manipulation
Course targeted at those with basic Python knowledge and data analysis concepts seeking to apply generative AI in their work
Data extraction, analysis, and model training from customer complaints to enhance customer satisfaction
Step-by-step guidance on OpenAI API integration and GPT-3.5 model fine-tuning in Python
Prerequisites include basic Python knowledge and familiarity with data analysis techniques
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