Course Content
Topic outline
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- History and evolution of Python
- Features and advantages
- Basic syntax and data types (strings, numbers, booleans)
- Variables, operators, and control structures (if/else, for loops)
- Functions and modules
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- Lists ( indexing, slicing, append, sort)
- Tuples
- Dictionaries (key-value pairs, dictionary methods)
- Sets (union, intersection, difference)
- Data structure operations (concat, split, join)
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- Reading and writing text files (open, read, write, close)
- Reading and writing CSV files (csv module)
- Reading and writing JSON files (json module)
- File input/output best practices
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- Classes and objects (attributes, methods, init)
- Inheritance (single and multiple inheritance)
- Polymorphism (method overriding, method overloading)
- Encapsulation and abstraction
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- Introduction to Pandas (data frames, series)
- Data manipulation and analysis (filter, groupby, merge)
- Data visualization (Matplotlib, Seaborn)
- Data analysis best practices
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- Introduction to Flask or Django
- Building web applications (routes, templates, databases)
- Web development best practices
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- Decorators
- Generators and iterators
- Async/await (asynchronous programming)
- Lambda functions and map-reduce
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- Building a full-stack project (web scraper, game, chatbot)
- Project planning and management
- Debugging and testing
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- Error handling and debugging
- Testing and automation (unittest, pytest)
- Best practices and coding standards
- Advanced libraries and frameworks ( NumPy, SciPy, Scikit-learn)
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