LLM (Large Language Models) Training in Ontario

LLM (Large Language Models) Training in Ontario, Canada

Participants will explore the fundamentals of natural language processing (NLP), prompting techniques, fine-tuning concepts, and deployment.

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LLM (Large Language Models) Training is a professional training program delivered by ProgNXT in Ontario, Canada. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this LLM (Large Language Models) Training course with hands-on, instructor-led sessions. This training offers a comprehensive introduction to large language models (LLMs), covering how they work, their capabilities, use cases, and...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: VTH53
14 Hrs
Last Updated: April 2026

Course Rating5/5

This training offers a comprehensive introduction to large language models (LLMs), covering how they work, their capabilities, use cases, and responsible application. Through practical exercises, participants will explore the fundamentals of natural language processing (NLP), prompting techniques, fine-tuning concepts, and deployment considerations for LLM-based applications.

Welcome to the official LLM (Large Language Models) Training certification program in Ontario, Canada. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic understanding of Python programming

Familiarity with concepts of machine learning or NLP (helpful but not mandatory)

Interest in generative AI, language models, or conversational interfaces

By the end of this training, participants will:

Grasp foundational knowledge of how LLMs work
Use prompt-based interaction for a range of language tasks
Understand trade-offs between open and closed models
Be prepared to integrate LLMs into small-scale apps or prototypes
Recognize the importance of responsible AI usage and evaluation

Understanding the core architecture and function of LLMs
Applying prompting techniques for various tasks
Evaluating LLM capabilities, limitations, and biases
Exploring LLM applications using open-source tools
Designing basic LLM-powered workflows or prototypes

How transformers and LLMs process language
Prompt design and prompt engineering
Evaluating LLM outputs for correctness and bias
Use of LLMs for summarization, generation, classification, and Q&A
Exploring open-source models and APIs

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

CONCEPTS, ARCHITECTURE, AND PROMPTING

Introduction to LLMs and NLP Evolution

What are LLMs and how they differ from traditional NLP

The rise of transformer architecture (BERT, GPT, T5, etc.)

Overview of key LLMs: GPT-4, LLaMA, Claude, Mistral, etc.

LLM Internals Simplified

Tokenization, embeddings, attention mechanism

Pre-training vs. fine-tuning vs. in-context learning

Model size, training data, and inference basics

Prompting Essentials

Zero-shot, one-shot, and few-shot prompting

Prompt formatting and temperature/top-k settings

Chain-of-thought prompting and role prompting

APPLICATIONS, OPEN-SOURCE TOOLS, AND ETHICS

LLM Use Cases and Design Patterns

LLMs for summarization, content generation, Q&A, and chatbots

RAG (Retrieval-Augmented Generation) and prompt chaining concepts

Fine-tuning vs. prompt engineering trade-offs

Working with LLM APIs and Open-Source Models

Using Hugging Face Transformers and pre-trained models

Calling LLM APIs using Python (OpenAI, Cohere, etc.)

Hosting local models with tools like LangChain, LlamaIndex, or Ollama

Evaluation, Limitations, and Ethics

Hallucinations, bias, and safety concerns

Responsible use of LLMs in production

Output evaluation metrics and human-in-the-loop feedback

Summary discussion, future trends, and next learning steps

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on:
Daily quizzes, mock questions and query resolution. Participation in hands-on exercises and labs. Performance in the final review and hands-on exercises will be evaluated.
ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

LLM (Large Language Models) Training Events in ontario

Online Events

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More Upcoming Session Dates

October 2026

📍 Ontario, Canada

27th Oct 2026→28th Oct 2026

🌐 Online Instructor-Led

27th Oct 2026→28th Oct 2026

November 2026

📍 Ontario, Canada

6th Nov 2026→7th Nov 2026

🌐 Online Instructor-Led

7th Nov 2026→8th Nov 2026

🌐 Online Instructor-Led

21st Nov 2026→22nd Nov 2026

📍 Ontario, Canada

28th Nov 2026→29th Nov 2026

December 2026

📍 Ontario, Canada

3rd Dec 2026→4th Dec 2026

🌐 Online Instructor-Led

4th Dec 2026→5th Dec 2026

📍 Ontario, Canada

18th Dec 2026→19th Dec 2026

🌐 Online Instructor-Led

22nd Dec 2026→23rd Dec 2026

Events for other courses in Ontario, Canada

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LLM (Large Language Models) Training in Ontario