🤖 AI & Machine Learning — Full Curriculum

Course only for IT professionals who want to be updated with Claude AI and n8n latest technology. Best for them. Master AI from fundamentals to production with LLMs, neural networks, computer vision, NLP, RAG systems and MLOps.

🧠 AI Fundamentals

4 topics

What is AI?

AI vs ML vs DL · History of AI

4 topics

Python for AI

NumPy mastery · Pandas for data

4 topics

Mathematics for AI

Linear algebra · Probability & stats

4 topics

Data Preprocessing

Data cleaning · Feature engineering

4 topics

ML Algorithms Overview

Supervised learning · Unsupervised learning

📊 Classical ML

4 topics

Regression

Linear regression · Polynomial regression

4 topics

Classification

Logistic regression · Decision trees

4 topics

Clustering

K-Means · DBSCAN

4 topics

Model Evaluation

Confusion matrix · ROC-AUC

4 topics

Scikit-learn Pipeline

Pipeline API · ColumnTransformer

🔮 Deep Learning

4 topics

Neural Networks

Perceptron · Backpropagation

4 topics

PyTorch

Tensors · Autograd

4 topics

CNNs

Convolution operation · Pooling layers

4 topics

RNNs & LSTMs

Sequence modeling · LSTM gates

4 topics

Transformers

Attention mechanism · BERT & GPT

💬 LLMs & Generative AI

4 topics

LLM Fundamentals

How LLMs work · GPT architecture

4 topics

Prompt Engineering

Zero-shot prompting · Few-shot prompting

4 topics

RAG Systems

Vector databases · Embeddings

4 topics

Fine-tuning LLMs

LoRA & QLoRA · PEFT methods

4 topics

AI Agents

Agent architecture · Tool calling

🚀 MLOps & Production AI

4 topics

Model Serving

FastAPI for ML · ONNX runtime

4 topics

MLflow

Experiment tracking · Model registry

4 topics

Docker for AI

Containerizing models · GPU Docker

4 topics

Monitoring

Data drift detection · Model drift

4 topics

AI Project End-to-End

Problem framing · Data pipeline

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