Dhivardhana IT Institute
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PromptEngineering&LLMTools:WorkSmarterwithAIModels

Learn to design effective prompts and work with large language models to build AI-powered features and workflows confidently.

Program LevelIntermediate
Time Commitment6 Weeks
Weekly Load10-12 Hrs / Week
Delivery FormatOnline

CourseOverview

Large language models have become core infrastructure for products and workflows , and knowing how to work with them effectively is now a valuable technical skill. This course covers prompt engineering techniques, LLM APIs, and practical patterns for building reliable AI-powered features like chatbots, summarizers, and content generators. You'll practice testing and refining prompts systematically, understanding model limitations, and structuring inputs and outputs for real applications. The course also introduces basic API integration so you can connect LLMs like GPT and Claude to simple applications. By the end, you'll be able to design effective prompts and integrate LLM capabilities into real projects and workflows.

Target Audience

  • Students
  • Working Professionals
  • Career Switchers

Prerequisites

  • Basic Programming Knowledge

Career Outcomes

  • Prompt Engineer
  • AI Developer
  • AI Product Specialist

ProgramStructure

Our instructional format is built to translate academic concepts into production engineering. This course spans 4 Weeks of immersive, online training.

Syllabus & Tests

What You Learn

  • 5 Learning Modules
  • 8+ Practice Quizzes
Real Projects

What You Build

  • 3 Production Projects
  • 10+ Hands-on Labs
  • 5+ Core Case Studies
Career Growth

Job Assistance

  • Industry-Recognized Certification
Mentors & Classes

Live Help & Support

  • 18+ Hours Interactive Lectures
  • Doubt Support

LearningCurriculum

A high-octane roadmap spanning 6 Weeks. Master the stack through production-grade modules.

Module 01

Understanding Large Language Models

Build a technical understanding of how LLMs work and where they're used.

Core Concepts

Transformer Architecture Overview
Tokens & Context Windows
Model Capabilities & Limitations
Popular LLM Providers
Open-Source vs Closed Models
Responsible AI Use

Build Target

Comparative Analysis of Leading LLM APIs

OpenAI APIClaude API

Questions? Chat on WhatsApp

Technologies&Software

Master the industry standard software ecosystem. Build deep expertise in production-tested developer tools.

Programming Languages

Python

Python

Intermediate

Integrate LLM APIs into applications.

AI Tools

OpenAI API

OpenAI API

Intermediate

Build applications powered by GPT models.

Claude API

Claude API

Intermediate

Integrate Claude models into custom applications.

LangChain

LangChain

Advanced

Chain prompts and tools into LLM-powered workflows.

Developer Tools

Git

Git

Fundamentals

Version control prompt templates and application code.

VS Code

VS Code

Fundamentals

Build and test LLM-integrated applications.

PortfolioProjects

Build production-grade systems throughout this track. Every project is designed to mirror real business requirements and establish technical authority in your portfolio.

Mini ProjectBeginner1 Week

Prompt Playground for Text Tasks

Students build a simple web tool for testing different prompts and parameters against an LLM API side by side, learning how temperature, system prompts, and few-shot examples change output. Students finish with a polished, presentable deliverable and a clear narrative of the decisions behind parameter controls for future employers to evaluate.

Core Specifications
  • Side-by-Side Prompt Testing
  • Parameter Controls
  • Output History
  • Few-Shot Examples
Deployment Tech Stack
ReactOpenAI API
GitHub Deployable
Portfolio Feature
Mini ProjectBeginner1 Week

AI Text Classifier via Prompting

A classification tool that uses carefully crafted prompts (rather than model training) to categorize support tickets by topic and urgency, showing how far prompting alone can go. This mirrors how real teams scope similar work, so students leave with both the artifact and a defensible explanation of their zero/few-shot prompting choices.

Core Specifications
  • Ticket Classification
  • Urgency Scoring
  • Prompt Templates
  • Accuracy Report
Deployment Tech Stack
PythonOpenAI API
GitHub Deployable
Portfolio Feature
Guided ProjectIntermediate2 Weeks

Structured Data Extraction Tool

Students build a tool that extracts structured JSON (invoices, resumes, forms) from unstructured text using function-calling and schema-constrained prompts, a widely used LLM tooling pattern. The project is designed to be extended afterward, giving students a natural talking point about schema design during placement interviews.

Core Specifications
  • Schema-Constrained Extraction
  • Function Calling
  • Validation Layer
  • Export to JSON/CSV
Deployment Tech Stack
PythonOpenAI Function Calling
GitHub Deployable
Portfolio Feature
Guided ProjectIntermediate2 Weeks

Multi-Step Prompt Chain for Report Generation

A tool that chains multiple prompts together - outline, draft, critique, revise - to generate polished business reports, teaching students to decompose complex tasks into prompt steps. By the end, students walk away with a working, documented build that clearly demonstrates prompt chaining and llm orchestration to recruiters and interviewers.

Core Specifications
  • Outline Generation
  • Draft & Critique Loop
  • Revision Step
  • Export to Document
Deployment Tech Stack
PythonLangChainOpenAI API
GitHub Deployable
Portfolio Feature
Industry ProjectAdvanced3 Weeks

AI Agent for Automated Customer Support Triage

Students build a tool-using AI agent that reads incoming support tickets, looks up order data, and drafts responses or escalates issues, combining prompting with real tool integrations. The finished build is structured for a portfolio or GitHub profile, giving students a concrete example of ticket triage they can walk through in an interview.

Core Specifications
  • Ticket Triage
  • Tool-Calling Agent
  • Draft Responses
  • Escalation Rules
Deployment Tech Stack
PythonLangChainOpenAI APIREST APIs
GitHub Deployable
Portfolio Feature
Industry ProjectAdvanced2 Weeks

Prompt Injection Testing & Hardening Toolkit

A red-team-style toolkit that tests an LLM application for prompt injection and jailbreak vulnerabilities, then implements guardrails and input sanitization to harden it. Students finish with a polished, presentable deliverable and a clear narrative of the decisions behind guardrail implementation for future employers to evaluate.

Core Specifications
  • Injection Test Suite
  • Guardrail Implementation
  • Input Sanitization
  • Security Report
Deployment Tech Stack
PythonOpenAI API
GitHub Deployable
Portfolio Feature
Capstone ProjectAdvanced4 Weeks

LLM Tooling Capstone: End-to-End AI Workflow Platform

A capstone platform combining structured extraction, prompt chaining, agentic tool use, and prompt-security hardening into one cohesive AI workflow product, suitable as a headline portfolio project for AI engineering roles.

Core Specifications
  • Structured Extraction
  • Multi-Step Prompt Chains
  • Tool-Calling Agent
  • Guardrails & Security
  • Deployed Demo
Deployment Tech Stack
PythonLangChainOpenAI APIDocker
GitHub Deployable
Portfolio Feature
Credential Checked

CareerOutcomes

Specialize in Prompt Engineering for LLM-Powered Products. As more products embed large language models directly into their core features, teams need specialists who understand how to design, test, and refine prompts for reliable, safe outputs. This course covers advanced prompt design and LLM tool integration, preparing learners for specialized technical roles at the forefront of applied AI product development.

Target Job Roles

Prompt Engineer
0–2 Years

Design and test prompts for LLM-powered features and applications.

Salary Outlook: ₹5–9 LPA

LLM Application Developer
1–4 Years

Build applications that integrate LLM APIs into production products.

Salary Outlook: ₹9–16 LPA

Senior AI Product Engineer
4–7 Years

Lead LLM integration strategy and evaluate model performance trade-offs.

Salary Outlook: ₹18–28 LPA

AI Product Lead
8–12 Years

Define AI product strategy and oversee LLM-powered feature roadmaps.

Salary Outlook: ₹30–42 LPA

Top Hiring Industries
AI StartupsProduct CompaniesIT ServicesFinTechEdTech

In-Demand Recruiter Skills

Prompt EngineeringPythonLLM APIsProblem Solving

Industry Credentials

  • Prompt Engineering for Generative AI Certificate

Recruitment Network

GoogleMicrosoftAmazonZohoInfosys

FrequentlyAskedQuestions

Have questions about this program? Review our comprehensive breakdown of curriculum, requirements, and logistics.

Still have questions?

If you cannot find the answer to your query in our FAQ database, our academic advisors are available for direct consultations.

Who should take this Prompt Engineering & LLM Tools course?

This course is for professionals, students, and developers who want to understand how large language models work and how to use them effectively across different practical tasks and tools. This mix of backgrounds is intentional, since the mentor support and project format work well for learners with varied starting experience.

Do I need a technical background to join?

No technical background is required. The course focuses on practical prompting techniques that apply whether you're using AI tools for writing, research, or basic coding tasks. You can always revisit recorded sessions if a particular fundamental needs extra practice before you move ahead.

Is this course suitable for beginners to AI tools?

Yes, the course starts with the basics of how LLMs interpret prompts before moving into more advanced techniques for getting reliable, high-quality outputs. We've seen many students with no prior technical background complete this course successfully with consistent weekly effort.

Will I receive a certificate after completing this course?

Yes, a certificate is issued after completing the modules and exercises, confirming your practical understanding of prompt engineering techniques. This gives you tangible proof of skill that you can reference during technical interviews and portfolio reviews. It's a recognized way to show recruiters you've gone beyond theory and actually shipped working projects during the course.

Is placement assistance included with this short course?

This is a skill-building course rather than a placement-driven program, but prompting skills are increasingly expected across almost every modern job role. Our team works closely with hiring partners to understand what skills they're actually screening for right now. Outcomes vary by individual effort, but the structured support meaningfully improves your chances compared to job hunting alone.

Are hands-on exercises included in the course?

Yes, you'll practice prompting techniques across different real-world use cases, building a practical toolkit you can apply immediately at work. This is one of the areas where hands-on practice makes the biggest difference in how confident you feel afterward. Understanding this well will also make it easier to pick up related tools and concepts down the line.

Is there an internship component in this course?

No, this short-format course doesn't include an internship, since it's focused on quickly building applicable, cross-functional AI skills. Mentors review your work throughout the internship, giving you feedback similar to what you'd get from a manager on the job. It's a meaningful way to show employers you can apply your skills beyond structured coursework.

Can working professionals complete this course easily?

Yes, this course is intentionally short and flexible, designed for busy professionals who want practical LLM skills without a long-term time commitment. Many of our students are working professionals, so the course structure has been refined specifically around this constraint.

Will I learn about different LLM tools, not just one platform?

Yes, the course covers principles that transfer across different LLM tools and platforms, so your skills remain relevant even as specific products change over time. This reflects current industry practice, so the skills you build stay directly relevant to what employers are actually looking for.

Does the course cover techniques like chain-of-thought prompting?

Yes, you'll learn structured prompting techniques including step-by-step reasoning approaches, which significantly improve the quality and reliability of AI-generated responses. We keep this part of the curriculum updated regularly to match how the technology is actually used in the field today.