Python for AI & ML
NumPy, pandas, data wrangling and the scientific Python stack for machine learning
100% Free · All lessons unlocked
Course Content
Foundations
Core concepts and groundwork
Introduction to Python and AI/ML Fundamentals
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Python Basics: Variables, Data Types, and Operations
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Control Flow: Conditionals and Loops
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Functions and Modules in Python
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Working with Lists, Tuples, and Dictionaries
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File Handling and Input/Output Operations
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Core Skills
Essential techniques and patterns
Object-Oriented Programming Fundamentals
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Exception Handling and Debugging
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NumPy: Creating and Manipulating Arrays
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Foundation Concepts Review and Practice
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Pandas: Data Structures and Loading Data
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Exploratory Data Analysis with Pandas
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Applied Practice
Hands-on, real-world scenarios
Data Cleaning and Preprocessing Techniques
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Feature Engineering and Selection
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Statistical Analysis and Hypothesis Testing
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Data Visualization with Matplotlib and Seaborn
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Introduction to Scikit-Learn and Model Building
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Core Skills Assessment and Practice
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Advanced Topics
Deeper, more complex material
Supervised Learning: Regression Models
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End-to-End Machine Learning Project: House Price Prediction
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Supervised Learning: Classification Models
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Model Evaluation Metrics and Cross-Validation
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Hyperparameter Tuning and Grid Search
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Ensemble Methods: Bagging and Boosting
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Production & Scale
Building for the real world
Intermediate Machine Learning Practice
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Unsupervised Learning: Clustering Algorithms
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Dimensionality Reduction Techniques
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Introduction to Neural Networks and Deep Learning
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Building Neural Networks with TensorFlow and Keras
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Advanced Topics Assessment and Practice
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Mastery & Capstone
Projects and final review
Convolutional Neural Networks for Image Processing
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Recurrent Neural Networks and Sequence Modeling
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Natural Language Processing with Python
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Model Deployment and Production Considerations
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Comprehensive AI/ML Capstone Project
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100% Free · All lessons unlocked
Topic Overview
What you'll learn
- Core concepts and fundamentals of Python for AI & ML
- Industry best practices and design patterns
- Hands-on exercises with real-world scenarios
- Performance optimization and advanced techniques
- Building production-ready applications