Curriculum in Python
Introduction to Python
Sequences and File Operations
Functions and Object-oriented Programming
Working with Modules and Handling Exceptions
Array Manipulation using NumPy
Data Manipulation using Pandas
Data Visualization using Matplotlib and Seaborn
GUI Programming
Curriculum in Python
Python is preferred by more than 45% of developers. The most widely used and in-demand programming language in the tech industry is Python.
- Need for programming
- Advantages of programming
- Overview of python
- Organizations using python
- Python Applications in various domains
- Variables
- Operands and expressions
- Conditional statements
- Loops
- Structural pattern matching
- Accepting user input and eval function
- Files input/output functions
- Lists
- Tuples
- Strings manipulation
- Sets and set operations
- Python dictionary
- User-defined functions
- Function parameters
- Different types of arguments
- Global variables
- Global keyword
- Lambda functions
- Built-in functions
- Object-oriented concepts
- Public, protected and private attributes
- Class variable and instance variable
- Constructor and destructor
- Inheritance and its types
- Method resolution order
- Overloading and overriding
- Getter and setter
- Standard libraries
- Packages and import statements
- Reload function
- Creating a module
- Important modules in python
- Sys module
- OS module
- Math module
- Date-time module
- Random module
- JSON module
- Regular expression
- Exception ha
- Basics of data analysis
- NumPy - Arrays
- Array operations
- Indexing, slicing, and Iterating
- NumPy array attributes
- Matrix product
- NumPy functions
- Array manipulation
- File handling using NumPy
- Introduction to Pandas
- Data structures in Pandas
- Series
- Data Frames
- Importing and exporting files in Python
- Basic functionalities of a data object
- Merging of data objects
- Pivoting a dataframe
- Concatenation of data objects
- Types of joins on data objects
- Exploring datasets
- Why data visualization?
- Matplotlib library
- Seaborn
- Line plots
- Multiline plots
- Bar plot
- Histogram
- Pie chart
- Scatter plot
- Boxplot
- Saving charts
- Customizing visualizations
- Saving plots
- Grids
- Subplots
- Heatmaps
- Ipywidgets package
- Numeric widgets
- Boolean widgets
- Selection widgets
- String widgets
- Date picker
- Color picker
- Container widgets
- Creating a GUI application