Building Agentic AI Applications with LLMs
NVIDIA Deep Learning Institute (DLI) · NVIDIA · Updated
AI Tutor Rating
8.6/10
Duration
8 hours instructor-led
Classes
26
Master building agentic AI applications using LLMs with tool use, planning, and multi-step reasoning capabilities.
Building Agentic AI Applications with LLMs is an 8-hour instructor-led course from the NVIDIA Deep Learning Institute (DLI). The course is designed for developers with Python and basic machine learning experience who want to master the construction of AI agents. It covers core concepts like agentic AI architectures, tool use and function calling, multi-step reasoning, and production deployment, culminating in a certificate of completion. This course serves practitioners aiming to move beyond simple LLM prompts to build autonomous, multi-step AI systems.
What you'll learn in Building Agentic AI Applications with LLMs
Our Review of Building Agentic AI Applications with LLMs
The structure of Building Agentic AI Applications with LLMs is logically sequenced, moving from fundamentals to production deployment across four curriculum chapters. The 8-hour, instructor-led format with 26 lectures suggests a dense, workshop-style experience typical of NVIDIA DLI offerings, prioritizing hands-on, guided learning over self-paced exploration. This format is effective for rapidly imparting practical skills but requires a significant time commitment in a single block.
The curriculum and learning outcomes indicate a practitioner-focused course that aims to deliver concrete capabilities. A learner completing this course should be able to design agentic architectures, implement tool-calling for LLMs, construct reasoning chains, and understand deployment considerations. The requirement to contact for pricing places this course in a corporate or institutional training context, which, combined with the NVIDIA DLI certificate, positions it as a high-value credential for professionals seeking vendor-recognized validation of their skills in a cutting-edge domain. The value is tied directly to the quality of NVIDIA's instruction and the market recognition of their certification.
The main limitation for individual learners is the opaque pricing model, which lacks the transparency of a standard online course marketplace. The prerequisites of Python and basic ML experience are non-negotiable; this is not an introductory AI course. The depth suggested by topics like production deployment implies the course is best suited for those already working in or adjacent to ML engineering, looking to specialize in the rapidly evolving area of AI agents.
Pros and cons of Building Agentic AI Applications with LLMs
Pros
- Focuses on the high-demand, advanced skill of building autonomous AI agents with LLMs.
- Structured, instructor-led format from NVIDIA DLI ensures guided, hands-on learning.
- Comprehensive curriculum covers the full lifecycle from design to production deployment.
- NVIDIA DLI certificate provides industry-recognized validation of specialized skills.
- Clear, practical learning outcomes centered on implementation and architecture design.
Things to consider
- Pricing is not transparent and requires direct contact, which may deter individual learners.
- Requires solid Python and basic ML experience, making it inaccessible for beginners.
- The 8-hour instructor-led format is intensive and less flexible than self-paced alternatives.
Who should take Building Agentic AI Applications with LLMs?
This course is best for machine learning engineers, AI developers, and data scientists with foundational Python and ML skills who need to build and deploy production-ready, autonomous AI agent systems. It fits professionals seeking vendor-specific, hands-on training from NVIDIA to implement tool use, planning, and reasoning chains in LLM-based applications.
Course curriculum for Building Agentic AI Applications with LLMs
Building Agentic AI Applications with LLMs at a glance
| Provider | NVIDIA Deep Learning Institute (DLI) |
|---|---|
| Instructor | NVIDIA |
| Level | Intermediate |
| Time to complete | 8 hours instructor-led |
| Pricing | Contact for pricing |
| Certificate | Certificate |
| Prerequisites | Python and basic ML experience |
Fit
Best for
Not ideal for
The bottom line on Building Agentic AI Applications with LLMs
Building Agentic AI Applications with LLMs is a specialized, high-level training course for practitioners ready to implement the next wave of autonomous AI. The NVIDIA DLI's instructor-led format and certificate offer considerable value for teams and individuals funded by their organizations, though the opaque pricing is a hurdle for solo learners. It delivers focused, practical skills in a critical emerging domain.
Building Agentic AI Applications with LLMs: frequently asked questions
What exactly is covered in the Building Agentic AI Applications with LLMs course?
The Building Agentic AI Applications with LLMs course covers Agentic AI Fundamentals, Tool Use and Function Calling, Planning and Reasoning, and Production Deployment. It teaches how to design agentic architectures, implement tool use, build reasoning chains, and deploy systems.
What experience do I need before taking this NVIDIA DLI agentic AI course?
You need Python programming experience and a basic understanding of machine learning concepts. This prerequisite is essential as the course focuses on building and deploying advanced AI agent systems, not introductory AI theory.
How much does the Building Agentic AI Applications with LLMs course cost and is there a certificate?
Pricing for Building Agentic AI Applications with LLMs requires contacting NVIDIA, as it is not listed publicly. The course does offer a certificate of completion from the NVIDIA Deep Learning Institute upon finishing the 8-hour program.
How does this instructor-led NVIDIA course compare to self-paced online AI agent tutorials?
Compared to self-paced tutorials, this NVIDIA DLI course offers structured, instructor-led training with a recognized certificate. It provides guided, hands-on learning focused on production deployment, which is often missing from free or asynchronous resources.
How can I get the most value from the Building Agentic AI Applications with LLMs course?
To get the most value, ensure you meet the Python and basic ML prerequisites beforehand. Actively engage with the 8-hour instructor-led sessions and hands-on exercises, focusing on applying the concepts of tool use and reasoning to your own project ideas.