Comprehensive Language Model Training
For the remainder of the training, a curriculum has been created with subheadings under LLM Fundamentals, LLM Scientist and LLM Engineer. There are detailed explanations and practical applications under each section. If you want to add more content in this area, you can add more subheadings under each section. For example;
- LLM Fundamentals(4 days): Machine Learning for Python, Data Preprocessing Techniques Fundamentals for Artificial Neural Networks
- LLM Scholar(6 days): Advanced Embodiment Techniques, Reinforcement Learning from Human Feedback Model Evaluation and Comparison Methods
- LLM Engineer(9 days): Application Development and Deployment, Security and Privacy Concerns, Improved Processing and Deployment Methods
Course: Generative AI with Large Language Models (LLM) using Python
When the curriculum of the training is examined, it is clearly seen that it is a structure that aims to equip the participants with the understanding of Generative Artificial Intelligence and practical skills. Focusing specifically on Large Language Models, the course is divided into five modules, each addressing different aspects of LLMs and their implementation using the Python programming language.(5 days)