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Large Language Model Development Program Overview

Large Language Model Development Program Course Description

Large Language Models (LLMs) are at the core of today’s AI revolution. From conversational assistants and AI copilots to enterprise automation systems, LLMs are transforming industries at scale. This comprehensive LLM Development Program is designed for developers and AI professionals who want to move beyond using APIs and truly understand how to build, fine-tune, optimize, and deploy LLM-powered systems.

In this course, you will explore the internal architecture of transformer-based models, understand tokenization strategies, embeddings, attention mechanisms, scaling laws, and model training principles. Instead of staying at a conceptual level, the program emphasizes practical engineering workflows used in modern AI companies.

You will work with open-source LLMs such as Llama and Mistral, learn fine-tuning techniques including LoRA and PEFT, implement Retrieval-Augmented Generation (RAG) systems, and deploy scalable AI services using APIs and cloud infrastructure.

By the end of this program, you will have the skills required to design, optimize, and deploy enterprise-grade LLM solutions confidently, making you industry-ready for advanced AI roles.

Large Language Model Development Program Course Syllabus

  • Evolution from NLP to LLMs
  • Transformer Architecture Deep Dive
  • Self-Attention & Multi-Head Attention
  • Tokenization Techniques
  • Scaling Laws of LLMs
  • Pre-training Objectives
  • Masked Language Modeling
  • Causal Language Modeling
  • Dataset Preparation & Cleaning
  • Training Infrastructure Overview
  • Supervised Fine-Tuning (SFT)
  • LoRA & QLoRA Techniques
  • PEFT Strategies
  • Instruction Tuning
  • Evaluation & Validation
  • RLHF Concepts
  • Reward Modeling
  • Human Feedback Loops
  • Safety Alignment Techniques
  • Model Bias Mitigation
  • Embeddings & Vector Databases
  • Chunking Strategies
  • Semantic Search
  • Hybrid Search
  • Building Knowledge Assistants
  • API-based Integration
  • Function Calling & Tool Use
  • Context Management
  • Memory Systems
  • Prompt Optimization for LLM Apps
  • Model Compression Techniques
  • Quantization Methods
  • Latency Reduction
  • Inference Optimization
  • Cost Management Strategies
  • Dockerizing LLM Applications
  • Cloud Deployment Strategies
  • Monitoring & Logging
  • Scaling with Load Balancing
  • Production Best Practices
  • Custom Fine-Tuned LLM Project
  • RAG-based Enterprise Chatbot
  • AI Copilot Application
  • End-to-End LLM Deployment

Large Language Model Development Program - Tutorials & Learning Guide

Welcome to the complete learning tutorials for Large Language Model Development Program. These tutorials are designed in simple language with examples, practice questions, and real-world projects to help you master the course step by step.

πŸ“˜ Course Tutorials
πŸ“– Large Language Model Development Program Tutorials & Learning

Understand the basics, scope, and career opportunities in Large Language Model Development Program. Learn why this technology is important and how it is used in real industries.

🎯 Interview Preparation

Most asked interview questions and real-world scenarios from Large Language Model Development Program to help you crack interviews.

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