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Data ScienceFeaturedPython Mastery - Part 10

Python Data Science: NumPy, Pandas, and Data Analysis

Master data science with Python using NumPy and Pandas. Learn data manipulation, analysis, visualization, and statistical operations with practical examples and real-world datasets.

Rusman Wahab
Published on January 28, 2024
26 min read
PythonData ScienceNumPyPandasAnalytics
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Series
Python Mastery
Part 10 of 15
Progress67%
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Series Contents
1

Python Fundamentals: Introduction to Python Programming

Complete beginner's guide to Python programming - learn installation, setup, basic syntax, and write your first Python programs with practical examples.

2

Python Fundamentals: Variables and Data Types

Master Python variables and data types - learn about integers, floats, strings, booleans, lists, tuples, dictionaries, sets, and type conversion with hands-on examples.

3

Python Fundamentals: Control Structures and Flow Control

Master Python control structures - learn conditional statements, loops, loop control, list comprehensions, and flow control with hands-on examples and real-world applications.

4

Python Fundamentals: Functions and Modules

Master Python functions and modules - learn function definition, parameters, return values, scope, lambda functions, decorators, module creation, and package management with practical examples.

5

Python OOP: Classes, Objects, and Inheritance

Master Python Object-Oriented Programming - learn classes, objects, inheritance, polymorphism, encapsulation, special methods, and design patterns with hands-on examples.

6

Python File Handling and I/O Operations

Master Python file handling and I/O operations. Learn to read/write files, work with CSV/JSON, handle file systems, and implement robust error handling for file operations.

7

Python Advanced: Data Structures and Algorithms

Master Python advanced data structures and algorithms. Learn collections module, custom data structures, sorting algorithms, and performance optimization techniques.

8

Python Error Handling and Debugging

Master Python error handling and debugging techniques. Learn about exceptions, try-catch blocks, custom exceptions, debugging tools, and best practices for robust Python applications.

9

Python Web Development: Building APIs with Flask

Learn web development with Python using Flask. Build RESTful APIs, handle routing, templates, forms, and database integration with practical examples and best practices.

10

Python Machine Learning Basics: Introduction to ML with Scikit-learn

Master the fundamentals of machine learning with Python. Learn data preprocessing, model training, evaluation, and practical implementation using scikit-learn and pandas.

10

Python Data Science: NumPy, Pandas, and Data Analysis

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11

Python Testing and Best Practices

Master Python testing frameworks and best practices. Learn unit testing, integration testing, test-driven development, code quality tools, and professional Python development practices.

12

Python Packaging and Deployment

Learn Python packaging, distribution, and deployment strategies. Master pip, setuptools, virtual environments, Docker, and cloud deployment for Python applications.

13

Python Advanced Patterns and Design Patterns

Master Python advanced programming patterns and design patterns. Learn about decorators, context managers, metaclasses, design patterns, and architectural patterns for professional Python development.

14

Python Asynchronous Programming and Concurrency

Master Python asynchronous programming with asyncio, async/await, coroutines, and concurrent execution. Learn to build high-performance, scalable Python applications.

15

Python Performance Optimization and Best Practices

Master Python performance optimization techniques. Learn profiling, memory management, algorithmic optimization, and advanced techniques for building high-performance Python applications.

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