Prompt Engineering Mastery

5.0

(2)

13 Enrolled

ehtada

Course Content

Introduction to Prompt Engineering and LLMs
What is a prompt? Anatomy of an LLM prompt-response cycle Types of models (open vs. closed source) Temperature, top-k, top-p sampling

Introduction to Prompt Engineering and Large Language Models (LLMs)

00:00

Foundations of Effective Prompting
Instructions vs. questions Prompt length and structure Direct vs. few-shot prompting

Few-Shot and Zero-Shot Prompting
Demonstrating intent with examples Pattern completion with few-shot prompts Designing reusable prompt templates

Chain-of-Thought and Step-by-Step Reasoning
Chain-of-thought (CoT) prompting techniques Decomposing complex queries Step-by-step breakdowns for math, logic, and multi-part questions

Prompt Patterns & Templates for Various Use Cases
Templates for: content creation, coding, customer support, research assistance, education Role prompting (e.g., “Act as a...”) Input-output formatting

Evaluation and Iteration of Prompts
Prompt testing frameworks Human vs. model evaluation Prompt debugging and iteration

Advanced Prompt Engineering Techniques
Prompt chaining and memory Programmatic prompting (LangChain, OpenAI functions, JSON mode) Tools like AutoGPT, LangGraph, and Function Calling

Instructors

ehtada

0.0

1581 Students

2 Courses

Feedback

5.0

Total 2 Ratings

100%

Reviews (2)

NF

noor fatima

6 months ago

it was very good.
NS

Nayab sabir

7 months ago

it was amazing

Free

Level Intermediate
Total Enrolled 13
Last Updated July 10, 2025

Prompt Engineering Mastery

Course Content

Introduction to Prompt Engineering and LLMs
What is a prompt? Anatomy of an LLM prompt-response cycle Types of models (open vs. closed source) Temperature, top-k, top-p sampling

Introduction to Prompt Engineering and Large Language Models (LLMs)

Foundations of Effective Prompting
Instructions vs. questions Prompt length and structure Direct vs. few-shot prompting

Foundations of Effective Prompting

Few-Shot and Zero-Shot Prompting
Demonstrating intent with examples Pattern completion with few-shot prompts Designing reusable prompt templates

Few-Shot and Zero-Shot Prompting

Chain-of-Thought and Step-by-Step Reasoning
Chain-of-thought (CoT) prompting techniques Decomposing complex queries Step-by-step breakdowns for math, logic, and multi-part questions

Chain-of-Thought and Step-by-Step Reasoning

Prompt Patterns & Templates for Various Use Cases
Templates for: content creation, coding, customer support, research assistance, education Role prompting (e.g., “Act as a...”) Input-output formatting

Prompt Patterns & Templates for Various Use Cases

Evaluation and Iteration of Prompts
Prompt testing frameworks Human vs. model evaluation Prompt debugging and iteration

Evaluation and Iteration of Prompts

Advanced Prompt Engineering Techniques
Prompt chaining and memory Programmatic prompting (LangChain, OpenAI functions, JSON mode) Tools like AutoGPT, LangGraph, and Function Calling

Advanced Prompt Engineering Techniques

Instructors

ehtada

noor fatima

Nayab sabir

Quick Links

Get in Touch

Prompt Engineering Mastery

Course Content

Introduction to Prompt Engineering and LLMs What is a prompt? Anatomy of an LLM prompt-response cycle Types of models (open vs. closed source) Temperature, top-k, top-p sampling

Introduction to Prompt Engineering and Large Language Models (LLMs)

Foundations of Effective Prompting Instructions vs. questions Prompt length and structure Direct vs. few-shot prompting

Foundations of Effective Prompting

Few-Shot and Zero-Shot Prompting Demonstrating intent with examples Pattern completion with few-shot prompts Designing reusable prompt templates

Few-Shot and Zero-Shot Prompting

Chain-of-Thought and Step-by-Step Reasoning Chain-of-thought (CoT) prompting techniques Decomposing complex queries Step-by-step breakdowns for math, logic, and multi-part questions

Chain-of-Thought and Step-by-Step Reasoning

Prompt Patterns & Templates for Various Use Cases Templates for: content creation, coding, customer support, research assistance, education Role prompting (e.g., “Act as a...”) Input-output formatting

Prompt Patterns & Templates for Various Use Cases

Evaluation and Iteration of Prompts Prompt testing frameworks Human vs. model evaluation Prompt debugging and iteration

Evaluation and Iteration of Prompts

Advanced Prompt Engineering Techniques Prompt chaining and memory Programmatic prompting (LangChain, OpenAI functions, JSON mode) Tools like AutoGPT, LangGraph, and Function Calling

Advanced Prompt Engineering Techniques

Instructors

ehtada

Feedback

Reviews (2)

noor fatima

Nayab sabir

Quick Links

Get in Touch

Introduction to Prompt Engineering and LLMs
What is a prompt? Anatomy of an LLM prompt-response cycle Types of models (open vs. closed source) Temperature, top-k, top-p sampling

Foundations of Effective Prompting
Instructions vs. questions Prompt length and structure Direct vs. few-shot prompting

Few-Shot and Zero-Shot Prompting
Demonstrating intent with examples Pattern completion with few-shot prompts Designing reusable prompt templates

Chain-of-Thought and Step-by-Step Reasoning
Chain-of-thought (CoT) prompting techniques Decomposing complex queries Step-by-step breakdowns for math, logic, and multi-part questions

Prompt Patterns & Templates for Various Use Cases
Templates for: content creation, coding, customer support, research assistance, education Role prompting (e.g., “Act as a...”) Input-output formatting

Evaluation and Iteration of Prompts
Prompt testing frameworks Human vs. model evaluation Prompt debugging and iteration

Advanced Prompt Engineering Techniques
Prompt chaining and memory Programmatic prompting (LangChain, OpenAI functions, JSON mode) Tools like AutoGPT, LangGraph, and Function Calling