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Overview of Python, setting up the environment, and basic syntax.
Declaring variables, understanding data types, and type conversion.
Arithmetic, relational, logical, and assignment operators.
If, else, and switch-case constructs with examples.
For, while, and do-while loops; iterating through collections.
Defining functions, parameters, return values, and scope.
Introduction to lists, dictionaries, sets, and tuples.
Accessing, modifying, and iterating over lists.
Using dictionaries to manage data and examples of real-world applications.
Characteristics, use cases, and differences between sets and tuples.
Implementing basic sorting techniques and analyzing performance.
Implementing search algorithms and discussing time complexity.
Introduction to classes, objects, and methods.
How objects are created and initialized in Python.
How inheritance promotes code reuse and extends functionality.
Techniques for achieving dynamic behavior in objects.
Managing access to data using Python conventions.
Analyze a real-world Python application that leverages OOP.
Techniques to fetch and process data from web services.
Methods to handle data formats commonly used in web applications.
Connecting to databases using SQLite and SQLAlchemy.
Data manipulation and analysis using the Pandas library.
Creating visual representations of data to gain insights.
Analyze a project that combines web APIs, databases, and data analysis.
Introduce the project, define requirements, and set objectives.
Outline the system architecture and key features of your project.
Begin coding the project with iterative feedback and testing.
Continue project development with integration of advanced features.
Test your project and refine for performance and usability.
Present your project, receive feedback, and discuss lessons learned along with emerging trends.
