AIFLX

Library / Artificial Intelligence

The Complete Full Stack AI Engineering Bootcamp

On Udemy

About this course

Welcome to the step by step roadmap to becoming an AI engineer

This course is designed to take you from the very basics to advanced real world AI engineering with a clear learning path. You will not just learn concepts. You will build systems, understand why they work, and learn how different pieces of AI, data, machine learning, deep learning, and LLM engineering connect together in real projects.

Most courses teach tools in isolation. This course teaches you how to connect everything into one complete AI engineering workflow that is used in industry.

In this course you will start from the foundations and gradually move towards advanced AI systems used today.

You will learn

  • Python programming from beginner to advanced concepts for AI work
  • How data is represented using vectors and matrices
  • Data visualization, statistics, and feature engineering techniques
  • SQL and PostgreSQL which every AI engineer must know
  • Supervised machine learning algorithms like regression, SVM, decision tree, and XGBoost using scikit learn
  • Unsupervised learning algorithms like K means and DBSCAN with proper visualization
  • How to build APIs using FastAPI and run AI applications inside Docker containers
  • Data engineering fundamentals with Kafka and Spark architecture and why data engineering is critical in AI projects
  • Build scalable AI engineering pipelines using Azure Databricks, PySpark, Delta Lake, and end to end data workflows
  • Deep learning foundations and the mathematics behind neural networks
  • CNN and how machines process and understand images
  • NLP fundamentals like tokenization, embeddings, and word embeddings
  • Sequence models including RNN, LSTM, and GRU
  • PyTorch from scratch and building ANN, CNN, and RNN models using PyTorch
  • Transformer architecture explained step by step in simple terms
  • LLM engineering, RAG, advanced RAG architecture, LangChain, LangGr

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