LLMs with Google Cloud and Python from Udemy

Unlock the Hidden Potential of Large Language Models with this Google Cloud Course.

Step into the transformative realm of language models and learn how to harness their expansive potential with Google Cloud and Python. This in-depth Udemy course offers a perfect fusion of theoretical insights and practical skills.

About the Course:

The course kicks off with a solid foundation in Large Language Models, helping students understand their complexity and functioning. As you delve into the main modules, you will become proficient in using the Google Cloud platform, effortlessly navigating the Generative AI Studio, comprehending its pricing, and selecting the best model for your needs. The course also delves into effective methods for Zero, One, and Few Shot Prompting, offering a comprehensive learning journey.

We then explore the nuances of the Vertex AI Python You'll learn about everything from token limits to temperature settings and sophisticated stop sequences in great detail.

A highlight of this course is the practical labs, where students can create various tools, such as an advanced Customer Service Chatbot and a state-of-the-art Translation and Summarization AI Bot. These labs go beyond coding, applying theoretical knowledge to tangible, real-world applications.

The course also ventures into the captivating area of prompt engineering. Students will learn to craft effective prompts for tasks like summarization and extraction. In addition, you'll explore text embeddings, learning about context injection in prompts and boosting model accuracy with similarity searches.

By the end of the course, students will have the skills to customize their models in the Google Cloud Console, tailoring them to their specific objectives.

Who Should Enroll?

This course is ideal for AI enthusiasts looking to broaden their knowledge, developers who want to integrate advanced language models into their projects seamlessly, and anyone fascinated by the wonders of Google Cloud and Python in AI.

Your Future Is Here.

Begin a journey that combines deep theoretical knowledge with practical expertise. With its expert-led instruction and structured modules, this course is a guiding light for those passionate about the wonders of language models.

Decide today and shape your future.

What's inside

Learning objectives

Gain a comprehensive understanding of how large language models function, along with their core components and mechanisms.
Master the setup and utilization of large language models on the google cloud platform, including understanding the pricing structure and model options.
Develop the ability to effectively use vertex ai's python llm api, understanding and implementing various parameters like token limit, temperature, and more.
Acquire practical skills in designing and developing a customer service chatbot using generative ai, ensuring it meets industry standards.

Delve into the nuances of coding models, from generating prompts to ensuring accurate code completions, enhancing your skill set as a developer.
Understand the art and science of prompt engineering, learning to structure, ideate, and transform prompts for tasks such as summarization, classification, extr
Learn advanced techniques in text-embedding and context injection, gaining proficiency in similarity searches and context-based prompting.
Enhance your ability to fine-tune models using the google cloud console, ensuring optimal performance and outcomes for specific tasks and applications.

Gain a comprehensive understanding of how large language models function, along with their core components and mechanisms.
Master the setup and utilization of large language models on the google cloud platform, including understanding the pricing structure and model options.
Develop the ability to effectively use vertex ai's python llm api, understanding and implementing various parameters like token limit, temperature, and more.
Acquire practical skills in designing and developing a customer service chatbot using generative ai, ensuring it meets industry standards.
Delve into the nuances of coding models, from generating prompts to ensuring accurate code completions, enhancing your skill set as a developer.
Understand the art and science of prompt engineering, learning to structure, ideate, and transform prompts for tasks such as summarization, classification, extr
Learn advanced techniques in text-embedding and context injection, gaining proficiency in similarity searches and context-based prompting.
Enhance your ability to fine-tune models using the google cloud console, ensuring optimal performance and outcomes for specific tasks and applications.

Syllabus

Let's get an overview of the course!

Course FAQs and Notebooks

Course Curriculum Overview

How Large Language Models Work

Let's explore LLMs in Google Cloud Console

Google Cloud Account Set-Up

First Prompt in Generative AI Studio

Understanding Pricing and Model Options

Zero, One, and Few Shot Prompting

Let's help you create the connection for Google Cloud and Python!

Set-up and First API Call

Parameters: Token Limit

Parameters: Temperature

Parameters: Top-K and Top-P

Parameters: Stop Sequences

One and Few Shot Prompts- Text and Chat Models

Let's explore how to create a simple customer service Chatbot that has extra context information about a company!

Lab Code Along - Customer Service Chatbot

Let's explore how to take advantage of models trained for code completion!

Link for Code Models Overview

Understanding Coding Models

Code Prompts

Code Chats

Code Completion

Let's create an assistant that can automatically help interact with a database without the need to know code!

Lab Code Along - Natural Language Database AI Assistant

Let's discover different tasks and prompt formats to help the LLM achieve your desired output!

Prompt Engineering Overview

Structuring and Separating Prompt Parts

Summarization Tasks

Classification Tasks

Extraction Tasks

Ideation and Expansion Tasks

Translation

Transformation - Tones and Formats Tasks

Understanding Model Hallucination

Let's create an AI bot that can translate a foreign newspaper article and then summarize it for us!

Lab: Translation and Summarization Customer Support Bot

Let's discover how to use text embeddings to quickly insert context for question answering!

Overview of Text Embedding

Context Injection into Prompt

Similarity of Text Embeddings

Text Embedding Context injection and Similarity Search

Let's explore custom tuning foundational models on our own data sets!

Introduction to Custom Tuning

Link for Next Lecture

Custom Tuning Example

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides an in-depth examination of foundational concepts and implementation of Large Language Models with Google Cloud and Python

Focuses on the practical application of LLMs through hands-on labs, including building a chatbot and an AI bot for translation and summarization

Leverages the latest advancements in Google Cloud, empowering learners to stay at the forefront of technological progress in AI

Emphasizes prompt engineering, empowering learners to craft effective prompts for various tasks, enhancing model accuracy

Suitable for AI enthusiasts, developers, and anyone interested in integrating advanced language models into their projects

Recommended for learners with a foundational understanding of Python and AI concepts

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 LLMs with Google Cloud and Python with these activities:

Review basic language model concepts

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Refine your understanding of the fundamental principles and components of language models to build a strong foundation for the course.

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Review readings and materials on language model theory
Complete practice exercises on core language model concepts

Practice using the Vertex AI Python LLM API

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Strengthen your proficiency in using the Vertex AI Python LLM API through repetitive exercises, solidifying your understanding of its functionality.

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Find a set of practice exercises or coding challenges
Code the solutions to the practice exercises
Test your code and debug any errors
Review your solutions and identify areas for improvement

Develop a simple chatbot using LLM APIs

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Apply your understanding of Google Cloud's LLM APIs to create a practical chatbot application, reinforcing your hands-on skills.

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Choose a specific domain or purpose for your chatbot
Design the chatbot's conversational flow
Integrate the Google Cloud LLM API into your chatbot
Train and test your chatbot using real-world data
Deploy and monitor your chatbot

Three other activities

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Attend a meetup or conference on LLMs

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Connect with other professionals and enthusiasts in the field of LLMs, exchange knowledge, and stay abreast of the latest trends and developments.

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Research upcoming meetups or conferences related to LLMs
Register and attend the event
Engage with other attendees, ask questions, and share your own insights

Write a blog post summarizing key course concepts

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Consolidate your learning by creating a comprehensive blog post that synthesizes the main ideas and takeaways from the course.

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Outline the key concepts and topics covered in the course
Research and gather additional information to support your explanations
Write a clear and engaging blog post that presents the course concepts in a logical and accessible way
Proofread and edit your blog post for clarity and accuracy
Publish your blog post and share it with others

Explore advanced techniques for prompt engineering

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Enhance your ability to craft effective prompts for various tasks, optimizing your interactions with LLMs for improved results.

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Identify online tutorials and resources on prompt engineering
Follow step-by-step instructions to implement different prompt engineering techniques
Experiment with prompt variations to observe their impact on LLM responses
Attend expert-led webinars or workshops on advanced prompt engineering

Career center

Learners who complete LLMs with Google Cloud and Python will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Scientist

Natural Language Processing Scientists are responsible for developing and deploying natural language processing models. This course can help Natural Language Processing Scientists by providing them with the skills and knowledge necessary to use Google Cloud and Python to build better natural language processing models.

See salaries and explore the career path for Natural Language Processing Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for developing and deploying machine learning models. This course can help Machine Learning Engineers by providing them with the skills and knowledge necessary to use Google Cloud and Python to build effective language models.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists are responsible for developing and deploying data science models. This course can help Data Scientists by providing them with the skills and knowledge necessary to use Google Cloud and Python to build better data science models.

See salaries and explore the career path for Data Scientist

Artificial Intelligence Engineer

Artificial Intelligence Engineers are responsible for developing and deploying artificial intelligence models. This course can help Artificial Intelligence Engineers by providing them with the skills and knowledge necessary to use Google Cloud and Python to build more effective and efficient artificial intelligence models.

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Back-End Developer

Back-End Developers are responsible for designing and developing the back-end of websites and applications. This course can help Back-End Developers by providing them with the skills and knowledge necessary to use Google Cloud and Python to design and develop more effective and efficient back-ends.

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Data Analyst

Data Analysts are responsible for understanding and interpreting large volumes of data, and providing actionable insights to help businesses make better decisions. This course can help Data Analysts by providing them with the skills and knowledge necessary to use Google Cloud and Python to analyze and interpret data more effectively.

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Software Engineer

Software Engineers are responsible for developing and maintaining software applications. This course can help Software Engineers by providing them with the skills and knowledge necessary to use Google Cloud and Python to build more effective and efficient software applications.

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Front-End Developer

Front-End Developers are responsible for designing and developing the front-end of websites and applications. This course can help Front-End Developers by providing them with the skills and knowledge necessary to use Google Cloud and Python to design and develop more effective and efficient front-ends.

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Technical Writer

Technical Writers are responsible for writing and editing technical documents. This course can help Technical Writers by providing them with the skills and knowledge necessary to use Google Cloud and Python to write and edit more effective technical documents.

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Business Analyst

Business Analysts are responsible for analyzing and understanding business processes. This course can help Business Analysts by providing them with the skills and knowledge necessary to use Google Cloud and Python to analyze and understand business processes more effectively.

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Product Manager

Product Managers are responsible for planning and developing products. This course can help Product Managers by providing them with the skills and knowledge necessary to use Google Cloud and Python to plan and develop better products.

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UX Designer

UX Designers are responsible for designing and evaluating user interfaces. This course can help UX Designers by providing them with the skills and knowledge necessary to use Google Cloud and Python to design and evaluate more effective user interfaces.

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Information Architect

Information Architects are responsible for designing and managing information systems. This course can help Information Architects by providing them with the skills and knowledge necessary to use Google Cloud and Python to design more effective and efficient information systems.

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Research Scientist

Research Scientists are responsible for conducting research in a variety of fields. This course can help Research Scientists by providing them with the skills and knowledge necessary to use Google Cloud and Python to conduct more effective research.

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Project Manager

Project Managers are responsible for planning and managing projects. This course can help Project Managers by providing them with the skills and knowledge necessary to use Google Cloud and Python to plan and manage projects more effectively.

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