Understanding the Fundamental Principles of Large Language Models (LLMs)

Name: Understanding the Fundamental Principles of Large Language Models (LLMs)
Price: 99000 KRW

Explains the basic principles of large language models like ChatGPT, focusing on theory.

(3.5) 2 reviews

44 learners

arigaram

llm

llm성능평가및튜닝

chatgpt

생성형ai

NLP

gpt

ChatGPT

LLM

What you will learn!

Fundamental Principles of Large Language Models (LLM)
LLM Development Process

🧭Change History

September 27, 2025
- "Section 17. 'Understanding the Complete LLM Development Process' Advanced", "
  I have significantly expanded and reorganized the lesson outline for Section 18. 'Understanding the Complete LLM Development Process' Hands-on Practice (Python + Google Colab). I am preparing lecture content that aligns with the new outline.
September 18, 2025
- I added the precautions to the detailed introduction page.
- I have revised the table of contents for "Section 10, 'Transformer Architecture' Hands-on Practice." I am preparing lecture content that aligns with the new table of contents.
- I have revised the table of contents for "Section 16, Understanding the Complete LLM Development Process." Accordingly, I am deleting the existing lectures and preparing new lecture content that aligns with the new table of contents.
September 1, 2025
- I have categorized all classes with bullet points as [Basic], [Advanced], and [Practice]. The existing [Supplementary] classes correspond to [Advanced] classes, so I have labeled them with the '[Advanced]' bullet point.
- To reduce confusion and make the learning process easier to understandI divided all sections into general sections (sections that include [Basic] classes or [Advanced] classes), advanced sections (sections that only include [Advanced] classes), and practice sections (sections that only include [Practice] classes).
- By reducing the possibility of confusion in this way, we have made all classes that were changed to private status on August 22, 2025, public again.
August 31, 2025
- I have released the practice table of contents for Sections 1 through 10. I plan to release the content gradually over time.
- I have re-released the table of contents for the [Supplementary] and [Advanced] classes from Section 1 to Section 10. This is to help students understand the connection with the practical exercise curriculum.
August 22, 2025
- We have changed the lessons in the [Advanced] and [Supplementary] courses that are not yet completed to private status. We plan to make each section public as they are completed in the future. This measure is to reduce confusion among students, so we would appreciate your understanding.
August 17, 2025
- We are currently adding advanced course classes and dividing classes with long lecture times. Therefore, the section numbers in the course materials and the section numbers shown in the table of contents may differ.

🔥 Course Features

"Today's learning becomes tomorrow's competitive edge! The most practical courses to build AI expertise that will shine even 10 years from now."
"Worth more than 100,000 won? No. It's an investment in AI capabilities that will protect your career even 10 years from now."
"Stop with superficial knowledge! Through bonus lectures, you can learn deep into LLM technology."
"It's different from other courses. It covers everything from the latest research trends to future AI."
"Grow as an AI expert while developing responsible AI development capabilities! Learn ethics, regulations, and safety all at once."

After taking the course

You will be able to clearly explain the fundamentals of the technology based on a deep understanding of the definition and characteristics of generative artificial intelligence, as well as the principles of language models.
You can understand the entire LLM development process from data collection to preprocessing, model selection, training, evaluation, and maintenance.
You will be able to understand the process of creating language models in a theory-focused manner, enabling you to solve specific problems using pre-training, transfer learning, fine-tuning, and RLHF (Reinforcement Learning from Human Feedback) technologies.

Pre-enrollment Reference Information

Practice Environment

Since this is a theory-focused lecture, no separate practice environment is required.
[Added Content] However, if you want to practice on your own with the content from the additional practical lessons, you can prepare Google Colab. Google Colab can be used for free immediately if you have a Google account (however, in special cases among the practice content, server performance provided only in paid plans may be required).

Learning Materials

I am attaching the lecture materials in PDF file format.

Prerequisites and Important Notes

Having background knowledge in natural language processing, artificial intelligence, deep learning, and reinforcement learning will help you better understand the content.
[Added Content] If you want to practice on your own with the content from the added practical classes, it would be very helpful to know Python programming and machine learning/deep learning programming.

Recommended for
these people

Who is this course right for?

Someone wishing to learn LLM principles with a theoretical focus.
Those who want to understand the LLM creation process

Need to know before starting?

Deep Learning
Reinforcement Learning
Natural Language Processing

Hello
This is

413

Learners

Reviews

Answers

4.7

Rating

Courses

IT가 취미이자 직업인 사람입니다.

다양한 저술, 번역, 자문, 개발, 강의 경력이 있습니다.

Curriculum

All

196 lectures ∙ (26hr 29min)

Course Materials:

Lecture resources

Section 1. Understanding Generative Artificial Intelligence

2 lectures ∙ (34min)

Section 2. 'Understanding Generative AI' Advanced

3 lectures ∙ (1hr 27min)

Section 3. 'Understanding Generative AI' Practice

3 lectures ∙ (2hr 26min)

6. [Practice] Lesson 3-1. Prompt-based Text Generation (GPT-2)
52:55
7. [Practice] Lesson 3-2. Text Summarization Practice (Using Pegasus, T5)
49:05
8. [Practice] Lesson 3-3. Simple Image Generation Experience (Stable Diffusion Mini Version)
44:34

Section 4. Deep Understanding of Language Model Principles

4 lectures ∙ (1hr 35min)

Section 5. 'Deep Understanding of Language Model Principles' Practice

3 lectures ∙ (2hr 8min)

Section 6. Autoregressive Model vs. Self-Attention Model

6 lectures ∙ (1hr 20min)

Section 7. 'Autoregressive Models vs. Self-Attention Models' Advanced

5 lectures ∙ (2hr 40min)

Section 8. (Scheduled) 'Autoregressive Model vs. Self-Attention Model' Practice

3 lectures

Section 9. Transformer architecture

5 lectures ∙ (1hr 20min)

Section 10. (Scheduled) 'Transformer Architecture' Hands-on Practice

14 lectures

Section 11. Comparison of Open-Source LLM and Closed-Source LLM

6 lectures ∙ (44min)

Section 12. (Scheduled) 'Comparison of Open-Source LLM and Closed-Source LLM' Hands-on Practice

3 lectures

Section 13. Understanding Basic Concepts Related to LLM Training

3 lectures ∙ (1hr 24min)

Section 14. 'Understanding Basic Concepts Related to LLM Training' Advanced

3 lectures ∙ (1hr 53min)

Section 15. (Scheduled) 'Understanding Basic Concepts Related to LLM Training' Hands-on Practice

3 lectures

Section 16. (Publishing in Progress) Understanding the Complete Process of LLM Development (Note: Previous lectures have been deleted.)

12 lectures ∙ (3hr 9min)

Section 17. (Publishing in progress) 'Understanding the Complete LLM Development Process' Advanced

22 lectures

Section 18. (Scheduled) 'Understanding the Complete LLM Development Process' Hands-on Practice (Python + Google Colab)

23 lectures

Section 19. Detailed LLM Training Process

6 lectures ∙ (1hr 35min)

Section 20. (Scheduled) 'LLM Training Process Details' Advanced

3 lectures

Section 21. (Scheduled) 'LLM Training Process Details' Hands-on Practice

3 lectures

Section 22. LLM Evaluation Methods

4 lectures ∙ (1hr 18min)

Section 23. (Scheduled) 'LLM Evaluation Methods' Advanced

3 lectures

Section 24. (Scheduled) 'LLM Evaluation Methods' Hands-on Practice

3 lectures

Section 25. LLM Lightweight Optimization

5 lectures ∙ (2hr 21min)

Section 26. (Scheduled) 'LLM Optimization' Advanced

3 lectures

Section 27. (Scheduled) 'LLM Optimization' Hands-on Practice

4 lectures

Section 28. (Scheduled) Ethical Considerations and Responsible AI for LLMs

3 lectures

Section 29. (Scheduled) 'Ethical Considerations of LLMs and Responsible AI' Hands-on Practice

3 lectures

Section 30. (Scheduled) LLM Applications and Deployment Strategies

3 lectures

Section 31. (Scheduled) 'LLM Application and Deployment Strategy' Hands-on Practice

3 lectures

Section 32. Current State of Latest LLM Technology

4 lectures ∙ (27min)

Section 33. (Scheduled) 'Latest LLM Technology Status' Hands-on Practice

3 lectures

Section 34. (Scheduled) Latest LLM Research Trends and Future Prospects

4 lectures

Section 35. (Scheduled) 'Latest LLM Research Trends and Future Prospects' Hands-on Workshop

4 lectures

Section 36. (Scheduled) Practical Applications of Generative Artificial Intelligence

3 lectures

Section 37. (Scheduled) 'Practical Application of Generative AI' Workshop

3 lectures

Section 38. (Scheduled) Guide to Small-Scale Practice and Project-Based Learning Methods

3 lectures

Section 39. (Scheduled) 'Guide to Small-Scale Practice and Project-Based Learning Methods' Practice

3 lectures

Published:

Last updated:

Reviews

All

2 reviews

3.5

2 reviews

khkwon
Reviews 3
∙
Average Rating 4.7
5
61% enrolled
- arigaram
  Instructor
  Thank you.
dbdusgur95
Reviews 1
∙
Average Rating 2.0
Edited
2
100% enrolled
.
- arigaram
  Instructor
  Thank you.

$77.00

arigaram's other courses

Check out other courses by the instructor!

Breaking Down Secure Coding

arigaram

This lecture is designed for understanding even if you have no prior knowledge of what Secure Coding (Security Coding) is. After covering basic security coding concepts, it focuses on web service security. This was a special lecture presented under the auspices of OO University. It presents over 160 source codes with rich comments, pinpointing core topics and techniques immediately applicable in practice.

Basic

security training, Penetration Testing, security

Breaking Down Secure Coding

arigaram

Prompt Patterns for Developers (Vibe Coding)

arigaram

Now is the era of development using AI. To create better, more accurate code and documents by better utilizing AI, methods are needed, so we propose suitable ones.

Basic

prompt engineering

Prompt Patterns for Developers (Vibe Coding)

arigaram

(For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

arigaram

Describes the need for LLM, its technical background, and basic concepts.

Beginner

NLP, gpt, AI

(For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

arigaram

History and Development of LLMs

arigaram

Describes in detail the various language models developed from the inception of Natural Language Processing technology to the process leading up to the latest LLM models.

Beginner

NLP, RNN, self-attention

History and Development of LLMs

arigaram

Complete Mastery of Prompt Engineering

arigaram

This course is a systematic learning process for prompt engineering, which is a core technology for effectively utilizing large language models (LLMs) or generative artificial intelligence. It covers a wide range of topics from basic theory to practical techniques, as well as the latest application cases and security/ethical issues, providing practical help to LLM-based service developers, data scientists, and AI planners alike.

Intermediate

prompt engineering

Complete Mastery of Prompt Engineering

arigaram

(For Planners) Service Design for LLM Applications

arigaram

You can learn the concepts and methods of 'service design' necessary when planning applications or web services based on LLMs, a type of generative artificial intelligence (generative AI).

Beginner

LLM, Generative AI

(For Planners) Service Design for LLM Applications

arigaram

AI-Based Full-Stack Development Practical Track for Beginners (Junior Level) - Master in One Day

arigaram

This enables junior developers to understand the entire development process from planning to code writing, deployment, and validation by using artificial intelligence as a development tool, allowing them to survive and thrive in the AI era by acquiring the full-spectrum capabilities needed.

Basic

Prototyping, crud

AI-Based Full-Stack Development Practical Track for Beginners (Junior Level) - Master in One Day

arigaram

Problem Statement: Basic Capabilities for Reducing 'Development Waste'

arigaram

Problematization (문제화) is a term also translated as problem posing, problem framing, problem setting, or problem definition. This concept involves questioning known facts (like requests or common sense) from a new perspective, defining the problem, and devising methods to solve it. Problematization should be the starting point for all development, yet it remains insufficiently discussed within the field. Performing projects or developing programs is, in essence, planning to solve problems. This means they are related to problematization. To solve a problem, it must first be clearly defined. However, problems are mostly presented as vague requests. Therefore, the ability to transform vague requests into clear problems is essential to reduce unnecessary 'development waste,' facilitate smooth collaboration, and accurately grasp users' true needs. This lecture helps train 'the thinking of problem construction' through practical examples and tools.

Beginner

Team Collaboration Tool, soft skills, Business Problem Solving

Problem Statement: Basic Capabilities for Reducing 'Development Waste'

arigaram

Cognitive Load Management Technology Breaking Through the Limits of RAG Performance

arigaram

What should be done when building a generative AI or LLM-based RAG (Retrieval-Augmented Generation) system, but the desired performance isn't achieved and there's no suitable solution? This lecture presents methods to improve RAG performance based on Cognitive Load theory. Through this lecture, you will understand the limitations of LLM context windows and learn how to effectively manage cognitive load in RAG systems. It is a practical-level theoretical lecture covering Chunk size and structure design, high-quality Chunk generation techniques, dynamic optimization, performance evaluation, and practical techniques.

Intermediate

AI, ChatGPT, LLM

Cognitive Load Management Technology Breaking Through the Limits of RAG Performance

arigaram

Java Naming

arigaram

"One name change, code transformed." "The key to readable code, 'naming for readability,' summarized from principles to examples." "Easy-to-read names begin collaboration."

Basic

naming-conventions, naming, renaming

Java Naming

arigaram

A Quick Overview of C Language

arigaram

You can quickly understand C language's basic concepts and grammar.

Beginner

C, Embedded

A Quick Overview of C Language

arigaram

Clean Coding: Learning Good Code Writing Techniques Through Cooking Analogies

arigaram

👨‍🍳 Like cooking code, neatly and deliciously! 『Clean Coding』 is a code cooking class for chef-like developers, where they joyfully learn clean coding through a cooking analogy. 🍽️

Basic

Team Collaboration Tool, Coding Test, Refactoring

Clean Coding: Learning Good Code Writing Techniques Through Cooking Analogies

arigaram

Creating an AI Judge with CrewAI and LLM

arigaram

We create an AI judge by combining CrewAI, facilitating LLM-based multi-agent technology, with knowledge graphs and inference systems.

Intermediate

AI, LLM, AI Agent

Creating an AI Judge with CrewAI and LLM

arigaram

(For Planners) Understanding Methods for Collecting and Analyzing User Requirements for LLM Applications

arigaram

We will examine methods for collecting and analyzing user requirements to plan LLM services.

Beginner

Project Management (PM), Service Planning, AI

(For Planners) Understanding Methods for Collecting and Analyzing User Requirements for LLM Applications

arigaram

(For Planners) Limitations and Future Prospects of LLMs

arigaram

We explore the limitations of LLMs, methods to overcome them, and the latest research topics.

Beginner

NLP, Service Planning, Content Planning

(For Planners) Limitations and Future Prospects of LLMs

arigaram

(For Planners) LLM Application Service Case Analysis

arigaram

Let's explore the types of applications or web services that can be built using LLMs.

Beginner

NLP, Service Planning, Content Planning

(For Planners) LLM Application Service Case Analysis

arigaram

Similar courses

Explore other courses in the same field!

(For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

arigaram

Describes the need for LLM, its technical background, and basic concepts.

Beginner

NLP, gpt, AI

(For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

arigaram

First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction

HappyAI

"LoRA-based lightweight fine-tuning: Your first step to creating a customized LLM!" This course is an introductory hands-on lecture designed so that even those encountering LLMs for the first time can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading models → applying data → training → comparing results. In a short time, you'll directly experience the flow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, gaining an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

Beginner

Deep Learning(DL), NLP, AI

First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction

HappyAI

How does artificial intelligence think and learn? Complete mastery of machine learning

momo7777322031

Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

Beginner

Machine Learning(ML), Deep Learning(DL), AI

How does artificial intelligence think and learn? Complete mastery of machine learning

momo7777322031

(For Planners) Limitations and Future Prospects of LLMs

arigaram

We explore the limitations of LLMs, methods to overcome them, and the latest research topics.

Beginner

NLP, Service Planning, Content Planning

(For Planners) Limitations and Future Prospects of LLMs

arigaram

Looking at the birth and development process of artificial intelligence reveals the principles of AI.

aidercollege

AI is not a technology that suddenly appeared. To properly see AI's present and future, you must understand 70 years of challenges and failures. 👉 "The moment you understand AI history, you can see both its principles and future together." Start right now!

Beginner

Machine Learning(ML), Deep Learning(DL), Reinforcement Learning(RL)

Looking at the birth and development process of artificial intelligence reveals the principles of AI.

aidercollege

(For Planners) LLM Application Service Case Analysis

arigaram

Let's explore the types of applications or web services that can be built using LLMs.

Beginner

NLP, Service Planning, Content Planning

(For Planners) LLM Application Service Case Analysis

arigaram

Anyone Can Easily Learn Generative AI (Basics)

aitutorlab

If you have a vague curiosity about generative AI but don't know where to start, this course is the perfect answer. It's structured to explain the core principles of AI technology clearly and concisely, allowing anyone to quickly grasp the essence. We'll go beyond simply knowing 'what it is' to deeply explore why it works that way and how to utilize it effectively. This course will serve as the most reliable starting point to help you confidently and proactively leverage technology in the rapidly changing AI era.

Beginner

ChatGPT, gemini, AI

Anyone Can Easily Learn Generative AI (Basics)

aitutorlab

Artificial Intelligence Anyone Can Understand for All Office Workers

jin0choi1216

An introductory AI lecture tailored for those new to AI! Key concepts, from data to generative AI, are simply explained. The goal is practical understanding, enabling you to question and explain AI, not build it.

Beginner

Machine Learning(ML), Deep Learning(DL), Recommendation System

Artificial Intelligence Anyone Can Understand for All Office Workers

jin0choi1216

Understanding the Latest Big Data and Artificial Intelligence Trends

YoungJea Oh

Navigate the data ocean, explore AI's future. This course explores the vast tech currents of Big Data and AI, examining their innovation in our lives and work.

Beginner

AI, Big Data

Understanding the Latest Big Data and Artificial Intelligence Trends

YoungJea Oh

In the era of generative AI, ethics is not a choice but survival.

aidercollege

ChatGPT and generative AI have deeply penetrated into our work and daily lives. From deepfakes, hacking, copyright infringement, Naver Whale Bot, to ethics in digital workplaces... The changes AI brings are not just technological issues. Right now, at this very moment, ethical issues are already occurring within the AI you're using. This course focuses on learning about the ethical issues that have exploded with the emergence of generative AI through real-world case studies.

Beginner

Machine Learning(ML), Business Productivity, AI

In the era of generative AI, ethics is not a choice but survival.

aidercollege

Creating Custom LLMs: From Basic RAG Concepts to Multimodal·Agent Practice for Beginners

HappyAI

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

Beginner

Python, vector-database, LLM

Creating Custom LLMs: From Basic RAG Concepts to Multimodal·Agent Practice for Beginners

HappyAI

ISTQB AI Testing - Learn Best Practices and Prepare for the Exam

edu

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will comprehensively learn everything from establishing AI-based system test strategies to designing and executing test cases, and even methods for utilizing AI to support testing. This course is conducted based on ISTQB's AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

Beginner

ISTQB, Software Test, AI

ISTQB AI Testing - Learn Best Practices and Prepare for the Exam

edu

Learn LLM and GPT Basics in 1 Hour

Essential

This course explains the basic concepts of LLM and GPT in an easy-to-understand way for everyone. Students can directly use the GPT API to create chatbots and run them on the web using Streamlit. By experiencing everything from basics to hands-on practice, you can solidly establish your first steps in AI utilization.

Basic

Python, AI, ChatGPT

Learn LLM and GPT Basics in 1 Hour

Essential

From deep learning to the latest AI, see the flow of technology, data, and key figures at a glance!

aidercollege

AI is not just a simple technology, but was born from people's questions and the flow of the times. Understanding this flow allows you to connect with any new technology without fear. 👉 "The moment you learn AI's roots through stories, you'll see the context." Start now!

Beginner

Machine Learning(ML), Deep Learning(DL), Big Data

From deep learning to the latest AI, see the flow of technology, data, and key figures at a glance!

aidercollege

AI-Driven Practical Implementation Strategies for Manufacturing Industry (Electronics/Semiconductor Sector)

88888

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

Beginner

AI, Big Data, Generative AI

AI-Driven Practical Implementation Strategies for Manufacturing Industry (Electronics/Semiconductor Sector)

88888

High-Quality AI Video All-in-One Class: Midjourney & Runway (25+a Scene Production)

Dong Ah K

Create high-quality AI videos with Midjourney&Runway. Director Kim Dong-ah, who collaborated with Samsung, will personally guide you step-by-step through the AI video production process based on a virtual brand.

Intermediate

Video Production, AI, Midjourney

High-Quality AI Video All-in-One Class: Midjourney & Runway (25+a Scene Production)

Dong Ah K

Time series data processing using Python and deep learning

YoungJea Oh

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

Intermediate

AI, python3, Deep Learning(DL)

Time series data processing using Python and deep learning

YoungJea Oh

Understanding PyTorch at a Glance with Code_Project Edition

onepm

The PyTorch_Project Edition, understood instantly with code, implements practical deep learning projects using image, video, and NLP data, understanding model structure and flow through code-centric learning over theory.

Intermediate

Deep Learning(DL), AI

Understanding PyTorch at a Glance with Code_Project Edition

onepm

Preparing for AI Graduate School A-Z: From Spec Preparation to Contacting Professors, Application Documents, and Interviews

epoch

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

Beginner

AI, Interview

Preparing for AI Graduate School A-Z: From Spec Preparation to Contacting Professors, Application Documents, and Interviews

epoch

Deep Learning CNN Complete Guide - Pytorch Version

dooleyz3525

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

Basic

Deep Learning(DL), PyTorch, Computer Vision(CV)

Deep Learning CNN Complete Guide - Pytorch Version

dooleyz3525

Understanding the Fundamental Principles of Large Language Models (LLMs)

What you will learn!

🧭Precautions

🧭Change History

🧠 Understanding the Fundamental Principles of Large Language Models (LLM): From Practical Applications of Generative AI to Cutting-Edge Research Trends

👥 Recommended for these people

🔥 Course Features

🧑‍💻 Explanation Method

After taking the course

Pre-enrollment Reference Information

Practice Environment

Learning Materials

Prerequisites and Important Notes

🧭 Now is the time to start

Recommended for
these people

Hello
This is

Curriculum

Reviews

arigaram's other courses

Similar courses

Understanding the Fundamental Principles of Large Language Models (LLMs)

What you will learn!

🧭Precautions

🧭Change History

🧠 Understanding the Fundamental Principles of Large Language Models (LLM): From Practical Applications of Generative AI to Cutting-Edge Research Trends

👥 Recommended for these people

🔥 Course Features

🧑‍💻 Explanation Method

After taking the course

Pre-enrollment Reference Information

Practice Environment

Learning Materials

Prerequisites and Important Notes

🧭 Now is the time to start

Recommended for these people

HelloThis is .css-1q3zd4q{text-decoration-line:underline;text-underline-position:under;text-underline-offset:1px;}

Curriculum

Reviews

arigaram's other courses

Similar courses

Recommended for
these people

Hello
This is