Description

Connect Python, data analysis and machine learning to the work of building AI applications. The course moves from programming and numerical foundations to SQL, feature engineering, supervised and unsupervised models, and neural-network work with PyTorch.

Application topics include FastAPI, Docker, data pipelines and LLM workflows. The saved syllabus names transformers, RAG, LangChain, LangGraph, agent tools and MCP server/client examples. These sections bring together data preparation, model behaviour and application integration, with projects intended to show how the components fit into an end-to-end system.

What you will learn

Build analysis and modelling workflows with Python, SQL and machine-learning libraries.
Study neural networks, NLP and transformer-based models.
Create AI APIs using FastAPI and Docker.
Explore RAG, agent workflows and MCP integrations.

Course specifications

Publisher: Udemy
Instructors: Aritra Basak
Language: English
Level: All Levels
Duration: 56 hours and 36 minutes
Lecture count: 345
Subtitle: English
Quality: 1080p
Edition: 2026-5

Course topics

Programming AI & Data Development Video Tutorial Artificial intelligence Python SQL Machine learning PyTorch

View course topics

Course topics · Udemy — The Complete Full Stack AI Engineering Bootcamp 2026-5

Prerequisites

No previous AI or machine-learning knowledge is required by the source.
A computer with internet access capable of running Python, VS Code and the required tools.

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