Building Your First Large Language Model (LLM) – A Beginner’s Guide (No Coding Required)
-
Training TypeLive Training
-
CategoryArtificial Intelligence
-
Duration3 Hours
-
Rating4.9/5
Course Introduction
About the Course
AI and Large Language Models (LLMs) are revolutionizing industries, automating workflows, and enhancing productivity across multiple domains. However, the complexity of AI development often discourages non-technical individuals from exploring this field.
This course is designed for beginners with no coding experience and will provide a step-by-step guide on how LLMs work, how they can be built using no-code tools, and how to fine-tune them for specific tasks. By the end of the course, participants will have hands-on experience creating, fine-tuning, and deploying their own LLM using accessible, no-code platforms
Course Objective
Understand what LLMs are and how they work (in simple, non-technical terms)
Learn the difference between open-source and proprietary LLMs
Explore the essential steps involved in building an LLM without coding
Learn how to collect and prepare training data for LLMs
Gain hands-on experience using no-code AI platforms to build an LLM
Fine-tune an LLM for specific tasks such as chatbots and text generation
Deploy their custom-trained LLM for real-world use
Who is the Target Audience?
Non-technical learners – Anyone with no prior coding or AI experience who wants to understand LLMs
Business professionals – Decision-makers looking to integrate AI into their businesses
Content creators & marketers – Individuals exploring AI-driven automation for content generation
Educators & researchers – Those interested in using AI for knowledge sharing and education
AI enthusiasts – Anyone curious about AI and looking for an easy-to-follow introduction
Basic Knowledge
This course is designed to be completely beginner-friendly, and no prior AI or programming knowledge is required. However, having a basic understanding of the following will be beneficial:
Basic Computer Skills – Ability to navigate web-based tools and platforms
General Awareness of AI Concepts (Optional) – Helps in understanding real-world applications
No Coding or Machine Learning Experience Needed – The course uses no-code platforms to simplify LLM creation
Available Batches
Pricing
Require a Different Batch?
Request a Batch For
-
Introduction to AI and Large Language Models
How LLMs are different from traditional AI systems
Real-world applications of LLMs
-
Explanation of training data, tokens, and embeddings
Pre-training vs fine-tuning in simple terms
What makes a model "large"? (Scale, parameters, etc.)
-
Open-source LLMs (e.g., GPT-based, BERT, DeepSeek)
Proprietary LLMs (e.g., ChatGPT, Bard)
Pros and cons of open-source vs proprietary models
-
From scratch vs leveraging existing LLMs (distilled models, pre-trained LLMs)Identifying the purpose of your LLM (e.g., customer support chatbot, text summarizer)
-
What kind of data is used to train LLMs?
Sources of training data (text corpora, documents, etc.)
Importance of clean, diverse, and unbiased data
-
How training happens conceptually (explained visually)
Key components: epochs, loss function, optimization
Cloud-based and automated LLM training solutions (Hugging Face, Google Colab)
-
Introduction to no-code platforms for AI (e.g., Hugging Face AutoTrain, Forefront AI, Runway ML)
Setting up a simple LLM project (guided tutorial)
-
What is fine-tuning?
Uploading your dataset to the platform
Training the LLM and monitoring its performance
-
Evaluating your model’s performance (accuracy, coherence)
Deploying your LLM as a chatbot or API with no-code tools
Use case demo: Creating a simple FAQ bot using your trained LLM