NVIDIA Triton Inference Server
High-Performance Model Serving at Scale with Triton Inference Server
In this course, you will: Set up and configure Triton Inference Server with Docker and Kubernetes; Structure the model repository for TensorFlow, PyTorch, ONNX, and TensorRT models; Configure dynamic batching and concurrent execution for throughput optimization.

30+
Hours
8
Modules
14
Topics
4.7
Rating
Beginner-Friendly
Level
New
Batches weekly
About NVIDIA Triton Inference Server
High-Performance Model Serving at Scale with Triton Inference Server
In this course, you will: Set up and configure Triton Inference Server with Docker and Kubernetes; Structure the model repository for TensorFlow, PyTorch, ONNX, and TensorRT models; Configure dynamic batching and concurrent execution for throughput optimization.
What This Training Covers
The NVIDIA Triton Inference Server programme at Tutorsbot spans 30+ hours across 8 structured modules. Every module is built around hands-on projects and real-world scenarios — not slide-heavy theory. Your instructor walks you through each concept with live demonstrations, code reviews, and practical exercises so you can apply what you learn from day one. The curriculum is aligned with current Technology Training industry expectations and hiring patterns.
Enrollment & Training Quality
NVIDIA Triton Inference Server is available in 2 flexible learning modes — choose online live classes, classroom, hybrid, self-paced, or one-on-one depending on your schedule. Every batch is limited in size to ensure each learner receives personal attention, code-level feedback, and doubt resolution. Career support and certification are included with every enrolment. Tutorsbot instructors are working professionals who teach from delivery experience, and the training standard stays consistent across all modes and batches.
Course Curriculum
8 modules · 14 topics · 30 hrs
01Triton Architecture and Setup
7 topics
Triton Architecture and Setup
7 topics
- Triton Inference Server architecture — Protocol, backends, scheduler, and metrics
- Docker-based Triton setup — NVIDIA GPU Cloud container and driver requirements
- Model repository structure — Folder layout, model versions, and config.pbtxt
- Supported backends — TensorFlow, PyTorch, ONNX Runtime, TensorRT, Python, DALI
- HTTP and gRPC protocols — REST and protobuf endpoints for inference
- Health and readiness endpoints — Liveness, readiness, and server metadata API
- Triton on Kubernetes — Helm chart deployment and persistent volume mount
02Model Repository Configuration
7 topics
Model Repository Configuration
7 topics
- Model configuration file — config.pbtxt input/output tensor specs and shapes
- Platform and backend selection — Setting platform for each model format
- Dynamic shapes — Specifying variable-length inputs with -1 dimension
- Model versioning — Deploying multiple versions and version control policies
- Model warm-up — Pre-loading models and running burn-in requests at startup
- Model state control — Loading, reloading, and unloading models at runtime
- Cloud model stores — Loading models directly from S3 and GCS repositories
Batching and Scheduling
Topics included
5 more modules available
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Enrol in This Course
All prices inclusive of 18% GST. Same curriculum & certification across all formats. Updated Aug 2026.
Online Live
Live instructor-led sessions from anywhere, with recordings for catch-up.
GST ₹2,288 included
EMI from ₹2,500/mo
or
What You Get After Completion
Every graduate receives a verified certificate, a portfolio of real projects, and dedicated career support.
Verified Certificate
Digitally signed with a permanent shareable link — not just for attendance.
LinkedIn-importable·Permanent URL·PDF download
Project Portfolio
Real, deployable projects reviewed by your instructor — ready for interviews.
Instructor-reviewed·GitHub-hosted·Interview-ready
Career Support
Résumé review, mock interviews, LinkedIn guidance, and employer introductions.
1-on-1 coaching·Mock interviews·Employer connect
Meet Your Instructor
Every NVIDIA Triton Inference Server batch is led by a practitioner who teaches from production experience, not textbooks.
Industry Expert
Senior Technology Professional
Senior professionals with substantial hands-on delivery experience at top companies, bringing real-world projects, industry insights, and best practices.
How We Teach
- Concepts start with a real problem so theory lands in context
- Projects reviewed the way a senior colleague reviews pull requests
- Every topic includes the kind of questions you'll face in interviews
Hire NVIDIA Triton Inference Server Talent from Tutorsbot
Companies hiring NVIDIA Triton Inference Server talent from Tutorsbot receive pre-assessed profiles backed by project work, instructor review, and interview-ready candidates who can explain what they built and why.
Why hire from us
Project repositories with documented technical decisions
Assessment outcomes backed by instructor context
Candidate readiness shaped by interview-style practice
Project-based portfolios available
Frequently Asked Questions
Everything you need to know about NVIDIA Triton Inference Server, answered by our training experts
1Who should take NVIDIA Triton Inference Server?
2Does NVIDIA Triton Inference Server include a certificate?
3Is placement support included with NVIDIA Triton Inference Server?
4How long does NVIDIA Triton Inference Server take to complete?
5What is the mode of delivery for NVIDIA Triton Inference Server?
6Can I get a free demo class for NVIDIA Triton Inference Server?
7What kind of projects will I work on in NVIDIA Triton Inference Server?
8What if I miss a class?
9Is NVIDIA Triton Inference Server worth it for experienced professionals?
10What is the refund policy for NVIDIA Triton Inference Server?
11Do you offer corporate or group training?
12How are the instructors selected at Tutorsbot?
13Will I get lifetime access to NVIDIA Triton Inference Server materials?
14Can I switch between batch timings?
15What support do I get after completing the course?
Still have questions?
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