Introduction to Artificial Intelligence with Python

Chapters

1Orientation and Python Environment Setup

2Python Essentials for AI

3AI Foundations and Problem Framing

4Math for Machine Learning

5Data Handling with NumPy and Pandas

6Data Cleaning and Feature Engineering

Data Quality Assessment Outlier Detection Imputation Strategies Scaling and Normalization Encoding Categoricals Feature Hashing Feature Selection Dimensionality Reduction Text Vectorization Image Preprocessing Signal Processing Basics Feature Crossing Target Leakage Avoidance Pipeline Construction Feature Store Concepts

7Supervised Learning Fundamentals

8Model Evaluation and Validation

9Unsupervised Learning Techniques

10Optimization and Regularization

11Neural Networks with PyTorch

12Deep Learning Architectures

13Computer Vision Basics

14Model Deployment and MLOps

Courses/Introduction to Artificial Intelligence with Python/Data Cleaning and Feature Engineering

Data Cleaning and Feature Engineering

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Prepare high-quality datasets and craft informative features using robust, repeatable pipelines.

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Signal Processing Basics

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