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Prompt Engineering Course in Nepal | Prompt Engineering Training for Everyone
From Basic Prompts to Advanced AI Control
Thousands of students have started their careers after getting certified by Broadway Infosys
Updated On: 14/07/2026
Created On: 05/05/2025
Course Overview
Prompt Engineering has recently emerged among the most in-demand job skills in today's world, driven by AI. The Prompt Engineering training in Nepal at Broadway Infosys will teach you the art of interacting with AI tools like ChatGPT and other large language models. This course will benefit students, practitioners, or business people to extract accurate, creative, and valuable results from AI.
This prompt engineering course gives practical training on writing better prompts, controlling AI responses, working step by step through problems, and applying AI to real-world tasks like content creation, data extraction, or decision-making. It will also deal with some hands-on labs, project work, and usage of AI on an ethical basis.
By the end of this course, you will gain the confidence to use AI tools efficiently and can explore job roles like Prompt Engineer, AI Content Creator, or AI Assistant Developer.
Tools Covered
Some of the major industry-relevant tools you'll work with in this course include:
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ChatGPT
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Claude
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Gemini
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DALL·E
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MidJourney
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VS Code
Students who got hired learning with us
Hear from graduates who have completed our courses.
College/Faculty: Ratna RajyaLaxmi Campus / BCA
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Working At: IME Life Insurance Ltd.
Position: Flutter Intern
College/Faculty: Mahendra Morang Adarsha Multiple Campus (MMAMC) / BCA
Working At: Curiotech Pvt. Ltd
Position: Flutter Intern
College/Faculty: ISMT College / Bsc.IT
Working At: Trilink I.T Solution
Position: Flutter Intern
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Frequently Asked Questions
No prior programming or AI experience is required. Basic computer skills and familiarity with using AI tools such as ChatGPT / Gemini are enough to get started.
Yes. The training starts with the fundamentals of Generative AI, Large Language Models (LLMs), and prompt design before moving into more advanced prompting techniques.
You will learn how to design, test, refine, and optimize prompts for LLMs, along with prompt patterns, structured prompting, context management, AI workflows, and practical AI applications.
Yes. You will learn the fundamentals of LLMs, tokens, context windows, model behavior, inference, and how models interpret and generate responses, helping you write more effective prompts.
You will explore techniques such as Zero-Shot Prompting, Few-Shot Prompting, Chain-of-Thought, Role Prompting, instruction prompting, structured outputs, and prompt chaining.
Yes. You will learn how to design prompts that produce consistent, structured, and task-specific outputs, including formats such as JSON, tables, summaries, and other structured responses.
Yes. You will learn how prompting approaches can be adapted across different LLMs and Generative AI tools, depending on the task, model capabilities, and desired output.
Yes. You will get an introduction to Retrieval-Augmented Generation (RAG), context retrieval, tool use, and AI agent workflows, helping you understand how prompting works in more advanced AI systems.
Yes. The training covers common LLM limitations such as hallucinations, prompt injection, context manipulation, and other prompt-related risks, along with techniques for improving reliability and safety.
Yes. The training emphasizes hands-on learning where you can create, test, compare, and optimize prompts for real-world tasks and workflows.
Yes. You will learn how effective prompting can be integrated into AI-powered workflows, content generation, research, data processing, customer support, and task automation.
The training can introduce how prompt engineering is applied to AI-assisted coding and developer tools, including generating, explaining, debugging, and improving code with AI.
You will be able to design effective prompts, optimize AI responses, work with LLM-based tools, create structured outputs, improve AI workflows, and apply prompt engineering to real-world business and technical tasks.
The training is useful for students, developers, marketers, content creators, designers, business professionals, entrepreneurs, researchers, and working professionals who want to use Generative AI more effectively.
You’ll receive hands-on guidance from trainers throughout the training, including support with prompt design, AI tools, practical exercises, LLM concepts, RAG workflows, and real-world AI applications.
Yes. Depending on your requirements, you can discuss suitable schedules with the training team. One-to-one training and group-based learning options may also be available.
Our course is available in hybrid training mode. You can attend classes in person or join online, whichever works best for you. If you cannot attend in person on a particular day, you can simply join the class online instead.
The course pricing varies depending on the subject and level. For detailed information on the course price, please contact us directly: +977-9841002000 / +977-1-4111849. Our team will be happy to guide you or send us an email at [email protected].
Our syllabus outlines are only the headlines of the major modules. To ensure a complete understanding of the course, we offer free counseling. Also, if you have specific modules in mind, you can customize the course. Send your inquiry today!
Lesson 1: Foundations of Prompt Engineering
- Introduction to large language models and how they work.
- Overview of popular AI platforms and their capabilities.
- The significance of effective communication with AI.
- Setting up accounts on key AI platforms for practice.
- What is Prompt Engineering and why it matters
- How AI processes and interprets prompts
- The relation between prompt quality and response quality
- Basic components of effective prompts
- Writing your first prompt and analyzing your response
- Common mistakes to avoid when crafting prompts
- Testing similar prompts across different AI tools
- Setting up a prompt journal for tracking progress
Lesson 2: Core Prompt Engineering Techniques
- Key principles of prompt structure and clarity
- Techniques for providing sufficient context
- Building specific and precise prompts
- Using delimiters to organize prompt information
- Using clear instructions and specifications
- Implementing formatting for better readability
- Managing token limitations effectively
- Ethical considerations in prompt design
- Iterative prompt refinement techniques
- A/B testing different prompt formulations
- Identifying and fixing problematic prompts
- Creating a personal prompt template library
Lesson 3: Advanced Prompting Strategies
- Generating structured outputs (tables, lists, JSON)
- Customizing output format and style
- Using conditional prompts for dynamic responses
- Constraining responses to meet specific requirements
- Zero-shot prompting for new tasks
- One-shot prompting with single examples
- Few-shot prompting with multiple examples
- When to use each approach for optimal results
- Implementing few-shot prompting for consistent results
- Creating structured output templates
- Developing conditional prompt scenarios
- Comparing effectiveness of different approaches
Lesson 4: Specialized Prompting Methods
- Breaking complex tasks into sequential prompts
- Planning and outlining before execution
- Validating intermediate steps
- Comparing single-step vs. multi-step approaches
- Prompting for explicit reasoning steps
- One-shot chain-of-thought demonstration
- Self-consistency techniques for better accuracy
- Debugging reasoning errors in AI responses
- Building a multi-step problem-solving workflow
- Implementing chain-of-thought for logical tasks
- Creating self-consistency checks for validation
- Developing prompts that request step-by-step solutions
Lesson 5: Practical Applications
- Text summarization techniques
- Content expansion and elaboration
- Translation and multilingual communication
- Tone adjustment and style transformation
- Customer support ticket routing and analysis
- Extracting structured data from unstructured text
- Sentiment analysis through prompt design
- Using prompts for content categorization
- Creating a content creation workflow
- Building an information extraction system
- Developing a sentiment analysis template
- Implementing a question-answering framework
Lesson 6: Ethics in AI
- Ownerships and AI copyright — what’s there to understand
- Addressing legal and ethical concerns
- Do’s and Don’t in GPT’s use
Lesson 7: On-course projects
REQUIREMENTS:
- Design a comprehensive prompt system for personal task management
- Implement techniques for scheduling, note-taking, and information retrieval
- Create reusable templates for daily productivity
REQUIREMENTS:
- Develop prompts for different content formats (blog posts, social media, emails)
- Implement tone and style adjustment capabilities
- Build a system for content summarization and expansion
REQUIREMENTS:
- Design prompts for pros/cons analysis
- Implement frameworks for evaluating options
- Create templates for generating recommendations with reasoning
REQUIREMENTS:
- Students will propose and implement a custom prompt engineering project
- Apply techniques learned throughout the course to solve a real-world problem
- Document the process, challenges, and solutions
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Why Prompt Engineering Training?
Basics to Advanced Control: Start with how AI processes prompts, then progress to chain-of-thought reasoning and multi-step workflows - a clear skill ladder, not scattered tips.
Beyond ChatGPT: Learn techniques that work across ChatGPT, DALL·E, MidJourney, and other AI platforms transferable skills, not tool-specific tricks.
Structured Output Mastery: Get AI to reliably generate tables, JSON, and formatted responses on demand practical control that saves hours of manual cleanup.
Real Hands-On Labs Every Lesson: Practice prompt optimization, A/B testing, and iterative refinement in every module; build a personal prompt template library you can actually reuse.
Real-World Project Portfolio: Build a productivity assistant, content creation suite, and decision support system, practical projects that double as proof of skill.
Taught by Experienced Instructors: Learn from instructors with real hands-on development experience, not just theoretical AI knowledge.
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