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Python, GPT-5.2 & LLMs: Build AI Agents & Reasoning Apps

Name: Python, GPT-5.2 & LLMs: Build AI Agents & Reasoning Apps
Rating: 4.5 (23 reviews)

Master Modern Python, Engineer Autonomous Agents, and Deploy Local LLMs (Llama 4, Gemini 3, o3)

Created byMerle Beazdell

Last updated 1/2026

English

What you'll learn

Master Modern Python: Write clean, professional code using Python advanced features, Iterators, Generators, and Decorators.
Build Autonomous AI Agents: Create AI systems that can plan, execute tools, and reason through complex tasks using GPT-5.2 and Claude Opus 4.5.
Engineer RAG Systems: Build "Retrieval Augmented Generation" apps to let AI chat with your private data without hallucinations.
Deploy Local LLMs: Run open-source models like Llama 4 and DeepSeek V3 locally on your own machine for privacy and zero cost.
Advanced Data Mastery: Fetch, clean, and manipulate massive datasets for AI training using Pandas and Polars.
Concurrent & Async Programming: Master asyncio and multi-threading to build high-performance, non-blocking AI applications.
Object-Oriented Architecture: Implement robust design patterns and inheritance to structure scalable enterprise-grade software.
Reasoning Model Integration: Learn to leverage "Thinking" models (like o3-mini and DeepSeek R1) for complex problem solving.

Course content

8 sections • 61 lectures • 6h 37m total length

Introduction2:16
Master practical Python programming by building data analysis tasks, reading files, and manipulating data structures, then explore object oriented programming, decorators, descriptors, and generators to boost code reuse and concurrency.
Welcome1:17

Introduction9:10
Python - Writing a Project and Debugging9:22
Writing a Python Project - Python Mortgage Calculator7:36
Writing a Python Project - Formatted Input/Output5:38
Python Text Processing and Reading Files6:14
Python - Understanding Python Functions6:59
Python - Designing and Writing Functions in Python - 15:22
Python - Designing and Writing Functions in Python - 25:17
Python - Learn About Python Data Structures - 16:28
Python - Learn About Python Data Structures - 28:41
Read a csv into a data structure, build a portfolio as a list of records, switch from tuples to dictionaries for readability, and encode with json for sharing.
Python - Learn How to Manipulate Data in Python - 14:43
Python - Learn How to Manipulate Data in Python - 28:33
Section Summary6:49

Python Import Statement and Module - 15:33
Python Import Statement and Module - 25:47
Python - Learn How to Write Powerful CSV Parser7:58
Python - Learn How to Make a Package8:51
Python - Learn About Classes6:21
Define a simple Python class called holding with an __init__ method to store name, date, shares, and price, and a cost method to compute total value.
Python - Learn About Attribute Access8:03
Python - Learn About Some Advanced Topics7:06
Discover how to implement alternate constructors with class methods in Python, using a date class to create instances from a string, or today’s date, without hardcoding the class name.
Python - Learn About Inheritance Basics6:55
Python - Writing a Project using Inheritance8:18
Python - Learn Some More Advanced9:21
Python - Learn How to Program More Defensive9:45
Section Summary5:43

Python OOP - Learn How to Create a Container Object5:59
Python OOP - Learn How to Create a Context Manager7:14
Python OOP - Encapsulation in Python5:31
Python OOP - Learn How to Manage Attributes - 15:22
Python OOP - Learn How to Manage Attributes - 24:43
Python OOP - Learn How to Manage Attributes - 36:34
Discover how descriptors replace verbose properties by intercepting dot notation with get and set, enabling type validation and controlled attribute access in Python classes.
Python OOP - Learn How to Manage Attributes - 45:39
Python OOP - Learn About Proxies and Wrappers7:00
Python OOP - Learn How to Use Python Functions6:44

Introduction3:56
Python Advanced Techniques: Learn About Decorators - 15:09
Python Advanced Techniques: Learn About Decorators - 24:31
Python Advanced Techniques: Understanding Decorators with Arguments6:57
Python Advanced Techniques: Learn About Python Class Decorators10:54
Python Advanced Techniques: Learning Python Types and Metaclasses9:17
Writing a Python Project - Learn How to Track Subclasses9:48
Python Advanced Techniques: Using Metaclasses to Fill in Details7:11
Explore how metaclasses fill in class details by inheriting from type, auto apply decorators, and enforcing a Typekit-based attribute system to reduce boilerplate and clarify data models.
Python Advanced Techniques: Learn About Iterators and Generators8:36
Python Advanced Techniques: Writing a Project with Generator Function6:37
Python Advanced Techniques: Learn How to Process Pipelines and Workflows6:47
Learn to create data processing pipelines with Python generators, piping output between functions, filtering for specific stock names, applying type conversions, and detecting negative changes in streaming stock data.
Python Advanced Techniques: Learn About Coroutines3:35
Introduce coroutines by defining async def functions and using await to run them under an event loop. Show that these code routine objects require a runner to execute until complete.
Python Advanced Techniques: Writing a Project with Coroutines8:42
Write a Python echo server with socket, then scale it with threading and asyncio coroutines to handle thousands of concurrent connections efficiently.
Learn More About Coroutines - 15:30
Learn More About Coroutines - 26:42

Foundational Principles of Transformative LLMs4:39
Explore foundational principles of transformative llms, from transformers and tokenization to model structures. Learn to go deep inside and, on top, manage vast applications through project management skills.
Evolutionary Trajectory of Large Language Models8:33
Architectural Insights into Large Language Models8:39
Explore how transformers use tokens and embeddings, compare encoder, decoder, and encoder-decoder designs, and reveal that these systems rely on empirical statistics rather than true intelligence, highlighting prompt design.
Exploring the Impact of Industrial Components in LLMs3:18
Analyzing Layer Interconnectivity and Self-Attention Mechanisms7:16
The Rise of Transformers as Fundamental Models7:07
Explore how transformers underpin modern AI, from prompt design to automated prompts, and assess implications for enterprises and data privacy.
Exploring Cutting-Edge LLMs: ChatGPT, GPT-4, PaLM 2, and Llama 26:04
Customizing LLMs for Specific Tasks: Strategies and Case Studies5:44

Requirements

No Prior Experience Needed: We start from zero. All you need is a computer and enthusiasm!
Internet Access: Required for downloading Python libraries and accessing API keys
Willingness to Experiment: The AI field moves fast—curiosity to try new tools is a plus.

Description

Python, GPT-5.2 & LLMs: From Core Concepts to Advanced AI Engineering

Unlock the Future of Code. Master Python. Command the Agentic Revolution.

In a world driven by "Reasoning Models" and "Autonomous Agents," mere coding proficiency isn't enough. True impact comes from combining architectural mastery with cutting-edge AI. "Python, GPT-5.2 & LLMs" is your launchpad to the forefront of 2026's tech landscape.

Meticulously engineered for ambitious developers, this course elevates your Python prowess to professional standards and empowers you to harness the revolutionary capabilities of GPT-5.2, Gemini 3 Pro, and Llama 4. If you're ready to transcend conventional scripting and build the intelligent systems of tomorrow, your journey begins now.

Forge Your Expertise: From Pythonic Foundations to Architectural Brilliance

We don't just teach syntax; we teach software engineering. You will learn to write code that is clean, efficient, and "Pythonic."

Master Advanced Python: Conquer decorators, generators, and context managers.
Write Indestructible Code: Implement robust error handling and Unit Testing to ensure your apps survive the real world.
Embrace Asynchronous Power: Skillfully manage asyncio and multi-threading—critical skills for building responsive AI applications that handle multiple API calls simultaneously.

Command the AI Revolution: Agents, RAG & Reasoning

The true power of Python today lies in orchestrating Intelligence. We move beyond basic chatbots into the world of AI Engineering.

Unveil Next-Gen LLMs: Understand the architecture behind GPT-5.2 (OpenAI), Gemini 3 (Google), and the open-source powerhouse Llama 4 (Meta).
Build "Thinking" Applications: Learn how to integrate reasoning models (like o3-mini) that can "think" before they speak, solving complex logic puzzles and coding tasks.
Create RAG Pipelines: Stop hallucinations. Teach your AI to read your own PDFs, databases, and emails using Retrieval Augmented Generation (RAG).
Deploy Local & Private AI: Learn to run models like Phi-4 and DeepSeek entirely on your own laptop—no API fees, 100% privacy.

From Concept to Career: Real-World Deployment

Your journey culminates in transforming code into value.

Seamless Deployment: Containerize your agents and deploy them to the cloud.
Future-Proof Skills: Master the "Agentic Workflow"—the new standard where developers act as architects for AI systems that plan and execute their own tasks.

Why This Course Is Your Definitive Advantage

Acquire a Coveted Skill Set: The fusion of Python Software Engineering + AI Agent Development is the #1 skill set employers are hiring for in 2026.
Stay Ahead of the Curve: While others are still learning GPT-4, you will be building with GPT-5.2 and multimodal Llama 4.
Become an Architect: Move beyond being a consumer of API endpoints to become a creator of intelligent systems.

Who this course is for:

Python Developers: Coders who want to upgrade their career by adding "Generative AI" and "LLM Integration" to their resume.
Data Scientists: Professionals looking to leverage "Reasoning Models" to automate complex data analysis.
Entrepreneurs & Indie Hackers: Visionaries who want to build and ship their own AI-powered SaaS products quickly.

Python, GPT-5.2 & LLMs: Build AI Agents & Reasoning Apps

What you'll learn

Explore related topics

Course content

Welcome2 lectures • 4min

Part 1: Getting Started With Python13 lectures • 1hr 31min

Understanding Python Library Functions, Objects, Classes & Inheritance12 lectures • 1hr 30min

Python Programming - Object-Oriented Programming9 lectures • 55min

Python Programming - Learn About Advanced Techniques15 lectures • 1hr 44min

Python Summary1 lecture • 1min

Part 2: Advanced Large Language Model Technologies: Foundations and Applications8 lectures • 51min

Thank You1 lecture • 1min

Requirements

Description

Who this course is for: