Python Courses
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AI Engineering in Python
Go from Python fundamentals to deploying production AI systems. You'll work with LLM APIs, build with vector databases, and design RAG architectures along the way.
Junior Data Analyst
Analyze and communicate insights by preparing, querying, and visualizing data with Excel, SQL, and Python to support data-driven decisions.
Data Engineer
Design, build, and automate reliable data pipelines with Python, SQL, and cloud-ready tooling for production workloads.
Data Scientist in Python
Analyze complex datasets and build predictive models by applying statistics and machine learning to deliver end-to-end data science solutions.
Data Analyst in Python
Build end-to-end analytics skills with Python and SQL—cleaning data, visualizing insights, and delivering business answers.
Generative AI Fundamentals in Python
Build Python skills, work with LLM APIs, and automate tasks to create practical AI-powered applications.
Python Fundamentals for Web Development
Build Python foundations, automation, and web-friendly patterns to prepare for backend projects and API integrations.
Machine Learning in Python
Train predictive models in Python, evaluate performance, and apply machine learning to real datasets for insights.
Data Cleaning with Python
Clean, transform, and prepare messy datasets by applying core data cleaning techniques in Python to support reliable analysis.
Probability and Statistics with Python
Apply probability, sampling, and hypothesis testing in Python to make confident, data-driven decisions with practice projects.
APIs and Web Scraping with Python
Collect, clean, and merge data from APIs and websites using Python, requests, and BeautifulSoup for analysis.
Data Analysis and Visualization with Python
Explore, analyze, and visualize real datasets with pandas, NumPy, and Matplotlib to communicate insights confidently.
Beginner Python for Data Analysis
Build foundational Python skills to write, organize, and apply code for analyzing real-world data and supporting data-driven decisions.
Introduction to Retrieval-Augmented Generation (RAG)
Learn to build Retrieval-Augmented Generation (RAG) systems in Python, covering pipeline architecture, prompt design, query expansion, reranking, and debugging common failure modes.
Building AI Apps with FastAPI
Build and deploy an LLM-powered API using FastAPI, Docker, and Docker Compose. From creating HTTP endpoints to running hardened, multi-container stacks.
APIs for AI Applications
Explore APIs with Python to retrieve real-world data for AI-focused analysis and applications.
Intermediate Python for AI Engineering
Advance your Python development skills by using object-oriented programming, list comprehensions and lambda functions, decorators, regular expressions, and error handling in real projects.
Tool Use with LLMs in Python
Learn to build reliable LLM systems with structured outputs, function calling, and tool integration. Move beyond basic prompting to create maintainable workflows using validation, agentic loops, and the Model Context Protocol.