Home Live Courses Large Language Model (LLM)
Video Course Beginner Data Science

Large Language Model (LLM)

Large Language Model (LLM) A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand, generate, and process human language. It is trained on massive amounts of text data using techniques from Natural Language

5 0 enrolled 5 (1 reviews) 2 views
Large Language Model (LLM)
FREE no payment required
Access Free
5 duration
50 modules
6 assignments
6 study notes
Certificate of Completion
Lifetime Access
0
Enrolled
50
Modules
0
Videos
5
Rating

About This Course

A Large Language Model (LLM) is a type of artificial intelligence designed to understand, interpret, and generate human language in a highly natural and meaningful way. It is built using deep learning techniques, particularly neural networks called transformers, and is trained on vast amounts of text data such as books, websites, articles, and conversations. LLMs are a core part of Natural Language Processing, which focuses on enabling machines to communicate like humans. By analyzing patterns in language, these models learn grammar, context, reasoning, and even some level of world knowledge. LLMs work by predicting the next word in a sequence based on the previous words, allowing them to generate coherent sentences, paragraphs, and even entire documents. Advanced models developed by organizations like OpenAI use billions or even trillions of parameters (internal values) to improve accuracy and understanding. This makes them capable of handling complex tasks such as answering questions, writing essays, generating code, translating languages, summarizing large texts, and assisting in conversations. These models are widely used in applications like chatbots, virtual assistants, content creation tools, customer support systems, and educational platforms. For example, they can help students learn concepts, assist developers in coding, or automate responses in businesses. Despite their power, LLMs have limitations—they may sometimes produce incorrect or biased information, as they rely on patterns in training data rather than true understanding. Overall, Large Language Models represent a major advancement in artificial intelligence, making human-computer interaction more intuitive and efficient while playing a crucial role in the future of technology and automation.

What You'll Learn

Understand the fundamentals of Large Language Models (LLMs) and their role in AI.
Learn the basics of Natural Language Processing and how machines process human language.
Understand how LLMs are trained using large datasets and deep learning techniques.
Learn about transformer architecture and how it improves language understanding.
Gain knowledge of text generation, summarization, translation, and question answering.
Understand real-world applications of LLMs in chatbots, education, and automation.
Learn how to interact with LLMs effectively using prompts (prompt engineering basics).

Course Curriculum

50 modules • 12 total items

1

Prompt Injection

Malicious Input Designed to Manipulate an AI Model Into Ignoring Instructions or Revealing Sensitive Data.

2 items
2

Prompt Injection

Malicious Input Designed to Manipulate an AI Model Into Ignoring Instructions or Revealing Sensitive Data.

3

Prompt Injection

Malicious Input Designed to Manipulate an AI Model Into Ignoring Instructions or Revealing Sensitive Data.

4

Prompt Injection

Malicious Input Designed to Manipulate an AI Model Into Ignoring Instructions or Revealing Sensitive Data.

5

Prompt Injection

Malicious Input Designed to Manipulate an AI Model Into Ignoring Instructions or Revealing Sensitive Data.

6

Sensitive Information Disclosure

Exposure of Confidential Data (like Passwords, API keys, or Personal info) Through insecure AI Responses.

2 items
7

Sensitive Information Disclosure

Exposure of Confidential Data (like Passwords, API keys, or Personal info) Through insecure AI Responses.

8

Sensitive Information Disclosure

Exposure of Confidential Data (like Passwords, API keys, or Personal info) Through insecure AI Responses.

9

Sensitive Information Disclosure

Exposure of Confidential Data (like Passwords, API keys, or Personal info) Through insecure AI Responses.

10

Sensitive Information Disclosure

Exposure of Confidential Data (like Passwords, API keys, or Personal info) Through insecure AI Responses.

11

Supply Chain

Risks Arising From Third-Party Tools, Libraries, or APIs that can introduce Vulnerabilities into AI Systems.

2 items
12

Supply Chain

Risks Arising From Third-Party Tools, Libraries, or APIs that can introduce Vulnerabilities into AI Systems.

13

Supply Chain

Risks Arising From Third-Party Tools, Libraries, or APIs that can introduce Vulnerabilities into AI Systems.

14

Supply Chain

Risks Arising From Third-Party Tools, Libraries, or APIs that can introduce Vulnerabilities into AI Systems.

15

Supply Chain

Risks Arising From Third-Party Tools, Libraries, or APIs that can introduce Vulnerabilities into AI Systems.

16

Data and Model Poisoning

Attacks Where Training Data or Models are Tampered With to Produce Biased or Harmful Outputs.

2 items
17

Data and Model Poisoning

Attacks Where Training Data or Models are Tampered With to Produce Biased or Harmful Outputs.

18

Data and Model Poisoning

Attacks Where Training Data or Models are Tampered With to Produce Biased or Harmful Outputs.

19

Data and Model Poisoning

Attacks Where Training Data or Models are Tampered With to Produce Biased or Harmful Outputs.

20

Data and Model Poisoning

Attacks Where Training Data or Models are Tampered With to Produce Biased or Harmful Outputs.

21

Improper Output Handling

Failure to Validate or Sanitize AI Outputs, Leading to Security Risks Like Code Injection or Misinformation.

2 items
22

Improper Output Handling

Failure to Validate or Sanitize AI Outputs, Leading to Security Risks Like Code Injection or Misinformation.

23

Improper Output Handling

Failure to Validate or Sanitize AI Outputs, Leading to Security Risks Like Code Injection or Misinformation.

24

Improper Output Handling

Failure to Validate or Sanitize AI Outputs, Leading to Security Risks Like Code Injection or Misinformation.

25

Improper Output Handling

Failure to Validate or Sanitize AI Outputs, Leading to Security Risks Like Code Injection or Misinformation.

26

Excessive Agency

Granting AI Systems too Much Autonomy, Allowing Them to Perform Actions Beyond Intended Permissions.

2 items
27

Excessive Agency

Granting AI Systems too Much Autonomy, Allowing Them to Perform Actions Beyond Intended Permissions.

28

Excessive Agency

Granting AI Systems too Much Autonomy, Allowing Them to Perform Actions Beyond Intended Permissions.

29

Excessive Agency

Granting AI Systems too Much Autonomy, Allowing Them to Perform Actions Beyond Intended Permissions.

30

Excessive Agency

Granting AI Systems too Much Autonomy, Allowing Them to Perform Actions Beyond Intended Permissions.

31

System Prompt Leakage

Accidental Exposure of Hidden System Instructions That Guide AI Behavior.

32

System Prompt Leakage

Accidental Exposure of Hidden System Instructions That Guide AI Behavior.

33

System Prompt Leakage

Accidental Exposure of Hidden System Instructions That Guide AI Behavior.

34

System Prompt Leakage

Accidental Exposure of Hidden System Instructions That Guide AI Behavior.

35

System Prompt Leakage

Accidental Exposure of Hidden System Instructions That Guide AI Behavior.

36

Vector and Embedding Weaknesses

Exploiting Flaws in Vector Databases or Embeddings to Retrieve or Manipulate Sensitive Information.

37

Vector and Embedding Weaknesses

Exploiting Flaws in Vector Databases or Embeddings to Retrieve or Manipulate Sensitive Information.

38

Vector and Embedding Weaknesses

Exploiting Flaws in Vector Databases or Embeddings to Retrieve or Manipulate Sensitive Information.

39

Vector and Embedding Weaknesses

Exploiting Flaws in Vector Databases or Embeddings to Retrieve or Manipulate Sensitive Information.

40

Vector and Embedding Weaknesses

Exploiting Flaws in Vector Databases or Embeddings to Retrieve or Manipulate Sensitive Information.

41

Misinformation

Generation of Incorrect or Misleading Information That Appears Credible.

42

Misinformation

Generation of Incorrect or Misleading Information That Appears Credible.

43

Misinformation

Generation of Incorrect or Misleading Information That Appears Credible.

44

Misinformation

Generation of Incorrect or Misleading Information That Appears Credible.

45

Misinformation

Generation of Incorrect or Misleading Information That Appears Credible.

46

Unbounded Consumption

Lack of Limits on AI Usage (API Calls, Tokens, etc.), Leading to Resource Exhaustion or High Costs.

47

Unbounded Consumption

Lack of Limits on AI Usage (API Calls, Tokens, etc.), Leading to Resource Exhaustion or High Costs.

48

Unbounded Consumption

Lack of Limits on AI Usage (API Calls, Tokens, etc.), Leading to Resource Exhaustion or High Costs.

49

Unbounded Consumption

Lack of Limits on AI Usage (API Calls, Tokens, etc.), Leading to Resource Exhaustion or High Costs.

50

Unbounded Consumption

Lack of Limits on AI Usage (API Calls, Tokens, etc.), Leading to Resource Exhaustion or High Costs.

Prerequisites

Basic understanding of computers and programming concepts
Familiarity with a programming language like Python
Knowledge of fundamental mathematics (algebra, probability, basic statistics)
Understanding of machine learning basics
Introductory knowledge of Natural Language Processing
Awareness of how data is used to train AI models

Requirements

Requirements for Learning Large Language Models (LLMs)
Computer/Laptop** (8–16 GB RAM recommended, good CPU/GPU preferred)
Programming Language – Python
Libraries & Frameworks – TensorFlow, PyTorch, Transformers (Hugging Face)
Development Environment – Jupyter Notebook / Google Colab
Internet Connection** (for datasets, APIs, and cloud tools)
Study Materials (AI/ML courses, NLP tutorials, documentation)
Datasets (text data for training and testing models)
Optional Cloud Resources (GPU services like AWS, Google Cloud for heavy models)

Student Reviews

5
1 reviews
N

Niharika

18 Jun 2026

good

Ready to Start Learning?

Join 0+ students already learning Large Language Model (LLM)

Get Free Access Browse More Courses