Mastering Prompt Engineering Using LLMs is a practical, hands-on course that teaches how to design effective prompts to get accurate, reliable, and context-aware outputs from large language models. It covers core techniques such as prompt structuring, role prompting, few-shot learning, and iterative refinement, along with real-world use cases across content generation, coding, data analysis, and automation. By the end, learners will be able to systematically craft prompts that improve model performance, reduce ambiguity, and unlock advanced capabilities of modern LLMs.
Dr. Mahendra Kanojia
Author
Dr. Mahendra Kanojia (Ph.D., M.Phil., Computer Science)
Dr. Kanojia is an AI research scientist and academic leader with 18years of experience. He serves as Principal and HOD of Computer Science at Sheth L.U.J. & Sir M.V. College, Mumbai, and founded the e-learning platform rocktheit.com., He specializes in AI, Machine Learning, chatbots, and advanced applications like autonomous oncology. His hands-on, accessible approach to technical training is driven by a single belief: “If humans can, technology can.”
Harshita Kanojia
Instructor Assistant
Ms. Kanojia is an Information Technology specialist from Sheth L.U.J. & Sir M.V. College with a strong focus on Artificial Intelligence, Machine Learning, chatbots, LLM models, and advanced AI applications. She has been actively involved in research for the past two years, has published a research paper, and has earned multiple research titles for her academic contributions. Known for her analytical mindset, innovation-driven approach, and dedication to emerging technologies, she is passionate about building intelligent solutions that create real-world impact.
Chapter 1 : Introduction to Prompt Engineering
Introduction to Prompt Engineering
Lesson 1 of 3 within section Chapter 1 : Introduction to Prompt Engineering .
Lesson 2 of 3 within section Chapter 1 : Introduction to Prompt Engineering .
Lesson 3 of 3 within section Chapter 1 : Introduction to Prompt Engineering .
Chapter 2 : Introduction to Prompt Patterns.
What are Prompt Patterns?
Lesson 1 of 3 within section Chapter 2 : Introduction to Prompt Patterns..
Classification of Prompt Patterns
Lesson 2 of 3 within section Chapter 2 : Introduction to Prompt Patterns..
Lesson 3 of 3 within section Chapter 2 : Introduction to Prompt Patterns..
Chapter 3 : Input Semantics and Output Customization.
Pattern Category: Input Semantics
Lesson 1 of 3 within section Chapter 3 : Input Semantics and Output Customization..
Pattern Category: Output Customization
Lesson 2 of 3 within section Chapter 3 : Input Semantics and Output Customization..
Lesson 3 of 3 within section Chapter 3 : Input Semantics and Output Customization..
Chapter 4 : Error Identification and Prompt Improvement
Pattern Category: Error Identification
Lesson 1 of 3 within section Chapter 4 : Error Identification and Prompt Improvement.
Pattern Category: Prompt Improvement
Lesson 2 of 3 within section Chapter 4 : Error Identification and Prompt Improvement.
Lesson 3 of 3 within section Chapter 4 : Error Identification and Prompt Improvement.
Chapter 5 : Interaction and Context Control
Pattern Category: Interaction
Lesson 1 of 2 within section Chapter 5 : Interaction and Context Control.
Pattern Category: Context Control
Lesson 2 of 2 within section Chapter 5 : Interaction and Context Control.
Chapter 6 : Generative AI Applications
Generative AI Applications
Lesson 1 of 1 within section Chapter 6 : Generative AI Applications .