Prompt Engineering fundamental course | Understanding AI Language Models by Diljeet Singh | Learn Smarter
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics

Grades

Grade 8 Grade 9 Grade 10 Grade 11 Grade 12

Curriculum

CBSE ICSE IB
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Typing
Memory
Math
English Adventures
Knowledge
Understanding AI Language Models

Language models are sophisticated AI systems designed to interpret and generate human language by predicting subsequent words based on context. Large Language Models (LLMs) leverage extensive training data to perform a wide array of language tasks, including text generation and summarization. Despite their capabilities, these models exhibit limitations such as the potential for inaccuracies and a lack of real-time understanding.

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Sections

  • 2

    Understanding Ai Language Models

    This section explains what language models are, how they function, especially large language models (LLMs), their strengths and limitations, and prompt design considerations.

    Learning Practice

  • 2.1

    What Is A Language Model?

    A language model is an AI system designed to understand and generate human language by predicting the next word in a sequence based on context.

    Learning Practice

  • 2.2

    What Is A Large Language Model (Llm)?

    Large Language Models (LLMs) are powerful AI systems designed to generate and understand human language through extensive training on massive datasets.

    Learning Practice

  • 2.3

    How Are These Models Trained?

    Large language models (LLMs) are trained using various approaches, including unsupervised learning and reinforcement learning, involving processes that go from data collection to refinement with human feedback.

    Learning Practice

  • 2.4

    How Do Models ‘understand’ Language?

    This section explains how language models predict text based on patterns learned from data, lacking true understanding like humans.

    Learning Practice

  • 2.5

    Strengths Of Llms

    This section outlines the strengths of large language models (LLMs), including their capabilities in generating text, multilingual support, and adaptability.

    Learning Practice

  • 2.6

    Limitations Of Llms

    This section discusses the key limitations of large language models (LLMs), including hallucination, lack of real-time awareness, and sensitivity to prompt changes.

    Learning Practice

  • 2.7

    Temperature And Top-P Sampling

    This section explains the concepts of temperature and top-p sampling, which are crucial sampling strategies in language model output generation.

    Learning Practice

  • 2.8

    Model Comparisons

    This section compares different AI language models, highlighting their strengths and specific use cases.

    Learning Practice

  • 2.9

    Choosing The Right Model

    This section explores the different language models and offers guidance on when to choose specific models for their unique strengths.

    Learning Practice

  • 2.0

    Learning Objectives

    This section outlines the learning objectives for understanding AI language models, focusing on definitions, training processes, strengths, and limitations.

    Learning Practice

  • 2.2.1

    Examples Of Llms

    This section provides examples of large language models (LLMs) along with a brief overview of their key features and creators.

    Learning Practice

  • 2.3.1

    Step-By-Step Process

    This section outlines the step-by-step training process of Large Language Models (LLMs).

    Learning Practice

  • 2.7.1

    Parameter Description

    Learning

  • 2.8.1

    Feature Comparison

    This section presents a comparison among different AI language models based on their strengths and use cases.

    Learning Practice

  • 2.9.1

    Prompt Engineering Guidelines

    This section provides essential guidelines for effective prompt engineering when working with various AI language models.

    Learning Practice

  • 2.0.0

    Summary

    This section outlines the fundamental aspects of AI language models, including their operation, training methods, strengths, and limitations.

    Learning Practice

References

Chapter 2_ Understanding AI Language Models.pdf

Class Notes

Memorization

What we have learnt

  • A language model is an AI s...
  • Large Language Models like ...
  • LLMs possess strengths such...

Final Test

Revision Tests