Intermediate Python and Large Language Models

Description

Intermediate Python Language Models

Intermediate Python Language Models is the ideal course for developers and data scientists aiming to advance their Python programming skills and harness the power of Large Language Models (LLMs) effectively. This course bridges the gap between intermediate Python proficiency and real-world LLM applications.

Course Description

Are you ready to take your Python skills beyond the basics? This course dives deep into intermediate-level Python techniques such as list comprehensions, decorators, generators, and advanced object-oriented programming. You’ll then explore how these concepts apply to working with powerful language models like OpenAI’s GPT series, Meta’s LLaMA, and HuggingFace Transformers.

Throughout the course, you’ll build hands-on projects that integrate Python logic with LLM-powered tasks such as text generation, summarization, sentiment analysis, prompt engineering, and chat agents. As you progress, you’ll gain confidence in designing Python applications that communicate effectively with APIs and produce human-like output.

Explore These Valuable Resources:

• OpenAI API Documentation
• HuggingFace Transformers Documentation
• LangChain Python Library

What You’ll Learn

• Intermediate Python constructs: list comprehensions, decorators, and generators
• Handling APIs using requests, asyncio, and data parsing
• Integration with OpenAI, HuggingFace, and other LLM providers
• Building prompt templates and response chains
• Creating real-world applications powered by LLMs

Requirements

• Basic knowledge of Python (variables, loops, functions)
• Familiarity with JSON and API concepts
• Access to Python 3.8+ installed on your system

About the Publication

This training was developed by expert machine learning engineers and educators with years of experience building production-level AI systems. The course reflects practical knowledge and is constantly updated to reflect the latest trends in LLM development and deployment.

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