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Emily McMilin,
Victor Geislinger,
Jason Lin,
and
Erick Galinkin
Udacity's AI Large Language Model course is your gateway to AI mastery. Learn AI text generation techniques and more. Sign up today for innovative AI learning.
Prerequisite details
Read more
Udacity's AI Large Language Model course is your gateway to AI mastery. Learn AI text generation techniques and more. Sign up today for innovative AI learning.
Prerequisite details
Read more
Udacity's AI Large Language Model course is your gateway to AI mastery. Learn AI text generation techniques and more. Sign up today for innovative AI learning.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Generative AI Fluency
- Intermediate Python
- Deep learning
- PyTorch
- Hugging Face
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/jk02g4/large
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What's inside
Syllabus
This lesson covers the types of LLMs, an intuitive understanding of their limitations and capabilities, inference and decoding hyperparameters, and strategies for effective prompt engineering.
Read more
Syllabus
This lesson covers the types of LLMs, an intuitive understanding of their limitations and capabilities, inference and decoding hyperparameters, and strategies for effective prompt engineering.
Read more
This lesson covers the essential Natural Language Processing topics needed to use the latest LLM technology. You will learn the basics of NLP and then dive into text encoding and text generation.
In this lesson, you will open up the black box of transformer architectures and learn about the attention mechanisms and other components that make these powerful models possible.
In this lesson, we will learn how to create a custom Q&A bot powered by OpenAI! Along the way, you'll learn how OpenAI works and how to leverage its powerful language processing capabilities.
In this lesson, you will learn how to construct a relevant, quality dataset for fine-tuning large language models and performing retrieval augmented generation.
For this project, you will use everything you learned in this course to create a custom chatbot using a dataset of your choice.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores current tech, which is standard in indusry
Taught by Emily McMilin, Victor Geislinger, Jason Lin, Erick Galinkin, who are recognized for their work in AI
Develops text generation and inference skills, which are core skills for NLP projects
Builds a strong foundation for beginners in AI and NLP
Teaches modern AI practices, which are foundational for NLP
Requires intermediate knowledge of Python and PyTorch, which may be a barrier for some learners
Save this course
Save Large Language Models (LLMs) & Text Generation to your list so you can find it easily later:
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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 Large Language Models (LLMs) & Text Generation with these
activities:
Review NLP book
Show steps
Strengthens foundational knowledge of NLP concepts and techniques, ensuring a deeper understanding of the subject.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Read chapters 1-3 of the book
-
Complete exercises and assignments from the book
Practice nltk.translate.bleu_score
Show steps
Strengthens foundational knowledge of the NLTK library, ensuring proficiency in leveraging it.
Browse courses on
NLTK Library
Show steps
-
Implement nltk.translate.bleu_score in Python
Complete 50+ guided prompts
Show steps
Reinforces understanding of AI Fluency and how it translates into prompts for generative AI tasks.
Browse courses on
Generative AI
Show steps
-
Complete 50+ guided prompts
Three other activities
Expand to see all activities and additional details
Show all six activities
Build a Q&A chatbot with OpenAI API
Show steps
Provides hands-on experience in building and deploying a practical application using OpenAI API, deepening understanding of NLP applications.
Browse courses on
OpenAI API
Show steps
-
Design the chatbot's architecture and functionality
-
Implement the chatbot using OpenAI API
-
Deploy the chatbot on a platform or website
Present your results from the fine-tuned LLM
Show steps
Provides an opportunity to demonstrate proficiency in fine-tuning LLMs and present findings, enhancing communication skills in a professional setting.
Show steps
-
Fine-tune a LLM on a relevant dataset
-
Evaluate the performance of your fine-tuned LLM
-
Prepare a presentation to showcase your results
Develop a custom chatbot using a dataset of your choice
Show steps
Provides a comprehensive project experience in customizing and deploying a chatbot, solidifying understanding of NLP and ML principles.
Show steps
-
Define the scope and requirements of your chatbot
-
Collect and prepare a dataset for training your chatbot
-
Train and fine-tune your chatbot using NLP and ML techniques
-
Deploy your chatbot on a platform or website
Review NLP book
Show steps
Strengthens foundational knowledge of NLP concepts and techniques, ensuring a deeper understanding of the subject.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 of the book
- Complete exercises and assignments from the book
Practice nltk.translate.bleu_score
Show steps
Strengthens foundational knowledge of the NLTK library, ensuring proficiency in leveraging it.
Browse courses on
NLTK Library
Show steps
Show steps
Show steps
- Implement nltk.translate.bleu_score in Python
Complete 50+ guided prompts
Show steps
Reinforces understanding of AI Fluency and how it translates into prompts for generative AI tasks.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Complete 50+ guided prompts
Three other activities
Expand to see all activities and additional details
Show all six activities
Build a Q&A chatbot with OpenAI API
Show steps
Provides hands-on experience in building and deploying a practical application using OpenAI API, deepening understanding of NLP applications.
Browse courses on
OpenAI API
Show steps
Show steps
Show steps
- Design the chatbot's architecture and functionality
- Implement the chatbot using OpenAI API
- Deploy the chatbot on a platform or website
Present your results from the fine-tuned LLM
Show steps
Provides an opportunity to demonstrate proficiency in fine-tuning LLMs and present findings, enhancing communication skills in a professional setting.
Show steps
Show steps
Show steps
- Fine-tune a LLM on a relevant dataset
- Evaluate the performance of your fine-tuned LLM
- Prepare a presentation to showcase your results
Develop a custom chatbot using a dataset of your choice
Show steps
Provides a comprehensive project experience in customizing and deploying a chatbot, solidifying understanding of NLP and ML principles.
Show steps
Show steps
Show steps
- Define the scope and requirements of your chatbot
- Collect and prepare a dataset for training your chatbot
- Train and fine-tune your chatbot using NLP and ML techniques
- Deploy your chatbot on a platform or website
Career center
Learners who complete Large Language Models (LLMs) & Text Generation will develop knowledge and skills
that may be useful to these careers:
NLP Engineer
NLP Engineer
An NLP Engineer will work with natural language processing on a daily basis. Taking this course would provide foundational knowledge to help an NLP Engineer understand the capabilities of LLMs and how they can be most effectively utilized.
Machine Learning Engineer
Machine Learning Engineer
This course can help a Machine Learning Engineer build a foundation in the use of LLMs. Natural language processing is a common use case for machine learning, and a Machine Learning Engineer who wants to work in this domain will benefit from it immensely.
Data Scientist
Data Scientist
A Data Scientist can use the knowledge and skills learned in this course to build and train machine learning models. A model can make predictions and generate data insights. It can help a Data Scientist understand how to use these models with natural language processing, which is the kind of data they will often work with.
Software Engineer
Software Engineer
A Software Engineer who wants to specialize in natural language processing can take this course to learn foundational skills. LLMs are quickly becoming a dominant force in NLP, and learning to work with them will be a huge boon to a Software Engineer's career.
Data Analyst
Data Analyst
Data Analysts who want to specialize in natural language processing will find this course to be very helpful. LLMs are used for text-related tasks, which Data Analysts often work with.
Product Manager
Product Manager
Product Managers who want to develop products that use natural language processing will benefit heavily from taking this course. LLMs are at the forefront of this field, and this course provides foundational knowledge to work with them.
Technical Writer
Technical Writer
For Technical Writers who want to build a foundation in natural language processing, this course can serve that purpose. This course will teach the fundamentals of LLMs, which are quickly becoming a dominant force in NLP.
Marketing Manager
Marketing Manager
LLMs are used heavily in marketing, so this course can provide a foundational knowledge that can help a Marketing Manager succeed. This course will teach the fundamentals of LLMs, which are quickly becoming a dominant force in their field.
Content Writer
Content Writer
Content Writers who want to use LLMs to enhance their workflow may find this course to be useful. Especially Content Writers who want to work in the domain of natural language processing will benefit from taking this course.
Sales Manager
Sales Manager
LLMs can be used to automate tasks and gain insights that can help Sales Managers succeed. This course will teach the fundamentals of LLMs, which are quickly becoming a dominant force in their field.
Business Analyst
Business Analyst
This course may be helpful for Business Analysts who want to understand how LLMs can be used to improve business outcomes. Natural language processing can often play a role in a business analyst's day-to-day work.
Customer Success Manager
Customer Success Manager
This course may be helpful for Customer Success Managers who want to understand how LLMs can be used to improve customer satisfaction. LLMs can often play a role in a customer success manager's day-to-day work.
Project Manager
Project Manager
This course may be helpful for Project Managers who want to understand how LLMs can be used to improve project outcomes. LLMs can often play a role in a project manager's day-to-day work.
Operations Manager
Operations Manager
This course may be helpful for Operations Managers who want to understand how LLMs can be used to improve operational efficiency. LLMs can often play a role in an operations manager's day-to-day work.
Quality Assurance Analyst
Quality Assurance Analyst
This course may be helpful for Quality Assurance Analysts who want to understand how LLMs can be used to improve software quality. LLMs can often play a role in a quality assurance analyst's day-to-day work.
For more career information including salaries, visit:
OpenCourser.com/course/jk02g4/large
Reading list
We've selected eight 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
Large Language Models (LLMs) & Text Generation.
Comprehensive guide to machine learning. It covers all the foundational concepts and techniques for using machine learning for natural language processing, computer vision, and other applications.
Comprehensive guide to deep learning with Python. It covers all the foundational concepts and techniques for using deep learning for natural language processing, computer vision, and other applications.
Comprehensive guide to machine learning. It covers all the foundational concepts and techniques for using machine learning for natural language processing, computer vision, and other applications.
Practical guide to deep learning with Python. It covers all the foundational concepts and techniques for using deep learning for natural language processing, computer vision, and other applications.
Practical guide to machine learning for programmers. It covers all the foundational concepts and techniques for using machine learning for natural language processing, computer vision, and other applications.
Practical guide to machine learning with Python. It covers all the foundational concepts and techniques for using machine learning for natural language processing, computer vision, and other applications.
Practical guide to machine learning with R. It covers all the foundational concepts and techniques for using machine learning for natural language processing, computer vision, and other applications.
Comprehensive guide to data analysis with Python. It covers all the foundational concepts and techniques for using Python for data cleaning, exploration, and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jk02g4/large
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Effort
4 weeks
Via
Udacity
Instructors
Emily McMilin
Victor Geislinger
Jason Lin
Erick Galinkin
Language
English
Good to know
Explores current tech, which is standard in indusry
Taught by Emily McMilin, Victor Geislinger, Jason Lin, Erick Galinkin, who are recognized for their work in AI
Develops text generation and inference skills, which are core skills for NLP projects
Builds a strong foundation for beginners in AI and NLP
Teaches modern AI practices, which are foundational for NLP
Requires intermediate knowledge of Python and PyTorch, which may be a barrier for some learners
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