Full Stack Python Developer
Working with Data
Full Stack Python Developer
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Completed
Module 1: Introduction to Python
Introduction to programming and Python
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Installing and setting up Python
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Python's interactive mode and scripting
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Basic syntax and data types
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Writing and executing simple programs
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Module 2: Control Structures and Loops
Conditional statements: if, elif, else
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Logical operators and comparisons
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Introduction to loops: while and for
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Using break and continue statements
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Nested loops and loop optimization
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Module 3: Functions and Modules
Defining and calling functions
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Function parameters and return values
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Scope and lifetime of variables
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Creating and using modules
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Standard library modules and their applications
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Module 4: Lists, Tuples, and Dictionaries
Working with lists: indexing, slicing, and manipulation
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Understanding tuples and their immutability
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Introduction to dictionaries and key-value pairs
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Dictionary methods and practical use cases
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Combining data structures for complex applications
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Module 5: File Handling and Exception Handling
Reading from and writing to files
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Managing file pointers and modes
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Handling exceptions and using try-except blocks
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Exception hierarchy and custom exceptions
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Best practices for error handling and resource management
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Module 6: Object-Oriented Programming (OOP) Basics
OOP concepts: classes, objects, attributes, and methods
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Defining classes and creating objects
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Constructors and destructors
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Inheritance and polymorphism
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Encapsulation and access modifiers
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Module 7: Advanced OOP Concepts
Method overriding and overloading
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Abstract classes and interfaces
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Composition vs. inheritance
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Working with multiple inheritance
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Design principles: SOLID and DRY
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Module 8: Working with Modules and Packages
Creating and using modules in-depth
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Python's module search path
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Introduction to packages and their structure
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Importing and organizing modules within packages
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Distributing your own packages
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Module 9: Regular Expressions and Text Processing
Understanding regular expressions
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Pattern matching using regex
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Using regex in string manipulation
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Search, match, and substitution operations
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Practical applications in data validation and manipulation
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Module 10: Introduction to Data Visualization
Data visualization importance and principles
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Introduction to data visualization libraries
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Creating basic plots with Matplotlib
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Customizing plots: labels, titles, colors, and styles
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Visualizing data trends and patterns
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Module 11: Working with External APIs
Introduction to APIs and their significance
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Making HTTP requests with Python
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Parsing JSON responses
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Authentication and API tokens
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Building a practical application using an external API
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Module 12: Final Project and Best Practices
Planning and designing a Python project
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Applying programming concepts to a real-world scenario
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Implementing a complete Python application
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Code documentation and commenting
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Version control with Git and project submission
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Course Info
Working with Data
Manipulating data using libraries like NumPy and Pandas
Data cleaning, transformation, and analysis
Introduction to data visualization with Matplotlib and Seaborn
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