Data & AI Training

LLM Applications

Name: LLM Applications
Availability: InStock

Build production minded apps on large language models: APIs, RAG pipelines, vector databases, tool calling, evaluation, cost control and deployment.

IntermediateAI & DataSoftware Development

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At a glance

CategoryData & AI Training
LevelIntermediate
Curriculum6 modules, 4 project ideas
InstituteAIIT Roorkee, Roorkee

Course Overview

About this course

Large language models become most useful when they are built into applications with the right data, tools and checks. This course teaches the engineering side of generative AI.

You design and build LLM powered applications with Python: model APIs, structured outputs, retrieval augmented generation with vector databases, function and tool calling, conversation memory, evaluation pipelines, latency and cost management, security risks such as prompt injection, and deployment behind a web interface.

Learning Objectives

By the end of LLM Applications, learners should be able to:

Integrate LLM APIs into Python applications
Build RAG pipelines with embeddings and vector databases
Use tool calling to connect models to functions and data
Evaluate LLM features with test sets and metrics
Deploy an LLM application with sensible security and cost controls

Topics Covered

01LLM engineering basics

Model APIs and parameters
Structured output
Choosing a model

02Retrieval augmented generation

Embeddings
Vector databases
Chunking, ranking and citations

03Tools and memory

Function calling
Conversation state
External APIs

04Frameworks and architecture

Orchestration libraries
When to avoid frameworks
Application architecture

05Evaluation and safety

Test sets and metrics
Prompt injection and data leakage
Guardrails

06Shipping

FastAPI backend
Simple web front end
Logging, latency and cost monitoring

Topic order and depth may be adjusted for the batch, format and learner level.

Practical Learning

Every module pairs explanation with hands-on work. Typical practical activities in this course:

RAG pipeline build over a document collection

Tool calling exercises with real APIs

Red team exercises against your own app

Evaluation dashboard build

Representative Projects

Projects are chosen with mentors based on your level and interests. Examples include:

Knowledge base assistant with cited answers
Resume screening helper with structured output
Data question answering app over a SQL database
Deployed LLM app with evaluation report

Who Should Join

Python developers
Data science and ML learners
Full stack developers adding AI features
Final year students building AI projects

Prerequisites

Python programming
Basic understanding of APIs and JSON
Generative AI or Prompt Engineering basics recommended

Learning Format

This course can be offered in the following formats, depending on the batch:

Short-Term Courses
Long-Term Courses
Certification-Oriented Programs
Weekend Programs
Workshops
Live Project Training
Internship Programs

Ask the team for current batch timings and the formats open for LLM Applications.

Career Relevance

Skills from this course are relevant to roles and directions such as:

LLM Application Developer
AI Engineer
Generative AI Developer
Backend Developer with AI specialisation

Career relevance describes where these skills are commonly used. It is not a promise of employment. Learners can use AIIT Roorkee's placement assistance for career preparation support.

FAQs

What is RAG?

Retrieval augmented generation gives a language model relevant information from your own documents or databases at the time of a question, so answers can be grounded in that material and cite sources.

Do I need to train my own model?

No. Most LLM applications use existing models through APIs or open models. The course focuses on building reliable applications around them.

How is this different from the AI Agents course?

LLM Applications covers the core engineering of model powered features such as RAG and tool calling. AI Agents focuses on systems that plan and carry out multi step tasks.

What is the duration and schedule of this course?

Duration, batch timings and format are shared when you enquire, because they depend on whether you choose a short-term, long-term, weekend or training format. Contact the team by phone, WhatsApp or email for current batches.

Is placement assistance available?

Learners can use AIIT Roorkee's placement assistance, which includes career counselling, CV preparation, LinkedIn development, interview preparation and mock interviews. Placement assistance is career preparation support and does not constitute a guarantee of employment or placement.

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