AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
LLM Application Development
Build useful applications powered by large language models, retrieval and APIs.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
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Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Create practical LLM applications using APIs, retrieval, structured output, evaluation and deployment patterns.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
LLM Application DeveloperAI EngineerRAG DeveloperAI Backend Developer
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You can build with Python and APIs
You want reliable structured model output
You need retrieval, evaluation and deployment patterns
YOUR LEARNING ARC
From guided foundation to finished work.
API layer
Requests, structured output, streaming and cost.
Application
Tools, state, retrieval and interfaces.
Evaluation
Test quality, safety and failure cases.
Deployment
Store, observe and run the application.
INDUSTRY TASKS
Practise the work, not only the tool.
- Build a structured extraction service
- Create a cited RAG application
- Evaluate and deploy an LLM feature
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Build dependable LLM API features
A service with validated outputs, retries and usage records.
02
Ground responses in approved knowledge
A cited RAG application with refusal behaviour.
03
Evaluate quality and safety
A repeatable test set and repaired failure cases.
04
Deploy an application for real users
A working product with monitoring and technical documentation.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
5 learning modules
Build reliable LLM-powered applications using APIs, structured outputs, retrieval, evaluation and production delivery patterns.
LLM APIs and application foundations
Understand the request-response layer, model choices and cost-quality trade-offs behind an LLM feature.
CORE TOPICS
- Python API clients and environment setup
- Messages, tokens, context and model selection
- Streaming, retries and rate limits
- Privacy, cost and logging fundamentals
GUIDED PRACTICE
Build a small application that handles model requests, failures and usage records.
MODULE DELIVERABLE
Documented LLM API service
Structured output, tools and application state
Move from free-form chat to dependable features that interact with software.
CORE TOPICS
- Schemas and validated structured output
- Function calling and tool definitions
- Conversation state and persistence
- Guardrails and deterministic fallbacks
GUIDED PRACTICE
Create an extraction or action feature that validates every model response before use.
MODULE DELIVERABLE
Structured LLM application feature
Retrieval-augmented generation
Ground responses in approved documents and make the supporting evidence visible.
CORE TOPICS
- Document ingestion and chunking
- Embeddings and vector search
- Retrieval, reranking and citations
- Access control and unsupported-answer handling
GUIDED PRACTICE
Build a cited document assistant and test questions it should answer and decline.
MODULE DELIVERABLE
Grounded RAG application
Evaluation, safety and quality engineering
Test behaviour systematically across expected, difficult and unsafe requests.
CORE TOPICS
- Evaluation datasets and scoring rubrics
- Accuracy, relevance and citation checks
- Prompt injection and data boundary tests
- Latency, cost and regression testing
GUIDED PRACTICE
Run an evaluation suite, identify failure clusters and improve the weakest cases.
MODULE DELIVERABLE
LLM evaluation and safety report
Interface, deployment and production capstone
Package the model feature into a usable product with monitoring and operating notes.
CORE TOPICS
- Web interfaces and API architecture
- Authentication and user-level limits
- Deployment, observability and feedback
- Documentation and portfolio presentation
GUIDED PRACTICE
Deploy a complete LLM application and present its architecture, evidence, risks and maintenance plan.
MODULE DELIVERABLE
Deployed LLM product capstone
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
Guided practice brief
Plan, produce, test and present a finished piece with trainer feedback.
Individual application
Plan, produce, test and present a finished piece with trainer feedback.
Workflow build
Plan, produce, test and present a finished piece with trainer feedback.
Industry-style assignment
Plan, produce, test and present a finished piece with trainer feedback.
Quality review
Plan, produce, test and present a finished piece with trainer feedback.
Final capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
PythonOpenAI APILangChainVector DB
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
Which programming language is used?
Python is the main language, with web interface examples where useful.
＋Are RAG and evaluation included?
Yes. Both are part of the applied course flow.
＋Do I need API experience?
Basic REST API knowledge is expected; an advisor can suggest preparation if needed.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online. Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. Weekday, weekend and selected fast-track schedules are available.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.