2024 Master class on Data Science using Python A-Z for ML

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Python NumPy, Pandas, Matplotlib and Seaborn for Data Analysis, Data Science and ML. Pre-machine learning Analysis.

What you will learn

Students will learn how to create and manipulate arrays, perform mathematical operations on arrays, and use functions such as sorting, searching, and statistics

Students will learn how to create and manipulate Series and Data Frames.

Students will learn how to create plots and charts, customize the appearance of visualizations, and add annotations and labels.

NumPy, Pandas, and Matplotlib will typically teach students how to use these tools to analyze and visualize data.

Description

Welcome to 2023 Master class on Data Science using Python.

NumPy is a leading scientific computing library in Python while Pandas is for data manipulation and analysis. Also, learn to use Matplotlib for data visualization. Whether you are trying to go into Data Science, dive into machine learning, or deep learning, NumPy and Pandas are the top Modules in Python you should understand to make the journey smooth for you. In this course, we are going to start from the basics of Python NumPy and Pandas to the advanced NumPy and Pandas. This course will give you a solid understanding of NumPy, Pandas, and their functions.

At the end of the course, you should be able to write complex arrays for real-life projects, manipulate and analyze real-world data using Pandas.

WHO IS THIS COURSE FOR?

√ This course is for you if you want to master the in-and-out of NumPy, Pandas, and data visualization.

√ This course is for you if you want to build real-world applications using NumPy or Panda and visualize them with Matplotlib and Seaborn.


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√ This course is for you if you want to learn NumPy, Pandas, Matplotlib and Seaborn for the first time or get a deeper knowledge of NumPy and Pandas to increase your productivity with deep and Machine learning.

√ This course is for you if you are coming from other programming languages and want to learn Python NumPy and Pandas fast and know it really well.

√ This course is for you if you are tired of NumPy, Pandas, Matplotlib and Seaborn courses that are too brief, too simple, or too complicated.

√ This course is for you if you have to get the prerequisite knowledge to understanding Data Science and Machine Learning using NumPy and Pandas.

√ This course is for you if you want to learn NumPy and Pandas by doing exciting real-life challenges that will distinguish you from the crowd.

√ This course is for you if plan to pass an interview soon.

English
language

Content

BONUS : Python Crash Course

Variables in Python
Conditionals & If statement
Example for If statement
If else statement
Example of If else statement
Nested If statement
Example for Nested If statement
Elif statement
Example for Elif statement
While loop
Example of while loop
For Loop
Example of For Loop
Break & Continue Statement
Introduction to containers
Creating and accessing lists in Python
List indexing and slicing
Working with List methods
Working with operators on lists
List Comprehension
Tuple : definition
Tuples
Tuple Indexing & Slicing
Manipulating Tuples
Unpacking Tuples
Sets
Dictionaries
Basics of dictionary
Accessing dictionary
len, str & type functions in dictionary
Functions in python
Example program1 on Functions
Example program2 on functions

Data Handling using Numpy

Introduction to modules in python
Creating & Displaying 1D array
Understanding 1D array Index
Creating Array of 0’s and Array of 1’s
Sorting elements in 1D array
Slicing a 1D array
Mathematical Operations on Array
Searching an element in a Array
Filtering an array
Checking whether given array is empty or not ?
Creating & Displaying 2D array
ndim Attribute
Size Attribute
Shape and reshape of array
Creating an Identity Matrix
arange()
linspace()
Random array
Random matrix
Creating a diagonal matrix
Flatten a Matrix
Computing Trace of a Matrix
Finding Transpose of a Matrix
Negative indexing to access elements in a 2D array

Data Handling using Pandas

Introduction to Pandas
Working with series in Pandas
Combining series with Numpy
Finding number of elements in a series
Computing mean, max and min in a series
Sorting a Series
Displaying Unique values in a Series
Summary of series statistics
Creating DataFrame From Series
Creating DataFrame from List of Dictionaries
Data Frame access using row-wise and column-wise.
Add, Rename and Delete Columns in a Data Frame
Deleting rows and cols using drop()
Boolean Indexing in DataFrames
Concatenating DataFrames

Data Visualization using Matplotlib in Python

Introduction to Matplotlib
Creating Line Graph
Creating Bar Graph
Creating Scatter Graph
Creating Histogram Graph
Creating Pie Chart
Creating 3D Plot
Creating 3D Line graph

Data Visualization using Seaborn in Python

Understanding a sample Dataset (Downloadable)
Introduction to Seaborn
Swarm Plot
Violin Plot
Facet Grids
Heatmap

Problem Solving Assignments

Projects
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