Learn Core Python, Numpy, and Pandas – Free Udemy Courses
Learn all the important concepts about Core Python, Numpy, and Pandas
What you’ll learn
Learn Core Python, Numpy, and Pandas – Free Udemy Courses
- Python
- Numpy
- Pandas
Requirements
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Basic programming
Description
The course covers Core Python, Numpy, and Pandas. Numpy and Pandas are stumbling blocks for many people who venture into machine learning. This course will help students to understand machine learning code as Numpy, Pandas are the building blocks for machine learning. Please note this is not a machine learning course. Please note that I have covered only core concepts of Python and there is far more to Python than what I have covered.
Google Python Notebook is used for code.
The following are the topics in Core Python.
- Setting up Google Notebook
- Variables in Python – String, Integer, Boolean
- Python Blocks
- If else statement
- While Loop
- List operations
- Range
- Functions
- Modules
- Exceptions
- File Handling
- Dictionaries
- Tuples
- List Slices
- List Comprehensions
- String functions
- Any, All operations
- Object Oriented Programming
- Magic methods
- Class and Static methods
The following are topics in Numpy and Pandas
- What is Numpy
- Numpy – Add, Subtract, Multiply
- Numpy Dot Product
- Numpy Slicing
- Mixing Integer Indexing And Slice Indexing
- Numpy Array Indexing
- More Array Indexing
- Boolean Array Indexing
- Numpy Sum
- Numpy Reshape
- Numpy Tensors 1D, 2D,3D
- Numpy Transposing
- Numpy Broadcasting
Pandas
- What is Pandas
- Pandas Series
- Pandas Series Index
- Pandas Advantage Over Numpy
- Pandas Loc and iLoc
- Pandas example – Finding Max
- Pandas Series Addition
- Pandas Apply Function
- Pandas DataFrames Introduction
- Pandas DataFrame Index, Loc and ILoc
- Pandas Sum Along Axis
- Pandas DataFrame Addition
- Pandas DataFrame ApplyMap
- Pandas Reading A CSV File
Who this course is for:
- Developers interested in learning Python
- Developers interested in learning Numpy
- Developers interested in learning about Pandas
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