What will you in Intro to Large Language Models (LLMs) Course
Understand the fundamentals of Large Language Models (LLMs) like GPT.
Explore how LLMs are trained, fine-tuned, and deployed.
Learn key concepts such as embeddings, tokenization, and transfer learning.
Examine real-world use cases for LLMs in text generation, coding, and analysis.
Get introduced to ethical, bias, and safety considerations in working with LLMs.
Program Overview
Module 1: Introduction to LLMs
⏳ 30 minutes
What are Large Language Models and why they matter.
Evolution from NLP to modern LLMs.
Module 2: Architecture and Core Concepts
⏳ 45 minutes
Transformer architecture, attention mechanisms, and tokenization.
Understanding embeddings and model sizes.
Module 3: Training and Fine-Tuning LLMs
⏳ 60 minutes
Pre-training vs. fine-tuning explained.
Role of datasets and hyperparameters in LLM performance.
Module 4: Using LLMs in Real-World Applications
⏳ 60 minutes
Applications in content creation, summarization, translation, and code generation.
Integrating LLMs into business and software workflows.
Module 5: Limitations, Ethics & Safety
⏳ 45 minutes
Bias in language models and mitigation strategies.
Responsible deployment and usage best practices.
Module 6: Future Trends in LLMs
⏳ 30 minutes
Open-source models, multimodality, and the next wave of LLM development.
Career paths and skill sets for working with LLMs.
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Job Outlook
High Demand: LLMs are central to roles in AI product development, NLP, and GenAI.
Career Advancement: Useful for aspiring ML engineers, AI researchers, and tech consultants.
Salary Potential: $100K–$200K+ in roles involving LLMs and GenAI solutions.
Freelance Opportunities: Building and fine-tuning LLM-powered applications or advising on AI integration.
Specification: Intro to Large Language Models (LLMs)
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