## 2023 Master class on Data Science using Python AZ for ML

### What you’ll 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.

### Requirements

Little knowledge in Python will be an added advantage. Student can still learn python basics from the BONUS section.

### 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.√ 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.

### Overview

Section 1: BONUS : Python Crash Course

Lecture 1 Variables in Python

Lecture 2 Conditionals & If statement

Lecture 3 Example for If statement

Lecture 4 If else statement

Lecture 5 Example of If else statement

Lecture 6 Nested If statement

Lecture 7 Example for Nested If statement

Lecture 8 Elif statement

Lecture 9 Example for Elif statement

Lecture 10 While loop

Lecture 11 Example of while loop

Lecture 12 For Loop

Lecture 13 Example of For Loop

Lecture 14 Break & Continue Statement

Lecture 15 Introduction to containers

Lecture 16 Creating and accessing lists in Python

Lecture 17 List indexing and slicing

Lecture 18 Working with List methods

Lecture 19 Working with operators on lists

Lecture 20 List Comprehension

Lecture 21 Tuple : definition

Lecture 22 Tuples

Lecture 23 Tuple Indexing & Slicing

Lecture 24 Manipulating Tuples

Lecture 25 Unpacking Tuples

Lecture 26 Sets

Lecture 27 Dictionaries

Lecture 28 Basics of dictionary

Lecture 29 Accessing dictionary

Lecture 30 len, str & type functions in dictionary

Lecture 31 Functions in python

Lecture 32 Example program1 on Functions

Lecture 33 Example program2 on functions

Section 2: Data Handling using Numpy

Lecture 34 Introduction to modules in python

Lecture 35 Creating & Displaying 1D array

Lecture 36 Understanding 1D array Index

Lecture 37 Creating Array of 0’s and Array of 1’s

Lecture 38 Sorting elements in 1D array

Lecture 39 Slicing a 1D array

Lecture 40 Mathematical Operations on Array

Lecture 41 Searching an element in a Array

Lecture 42 Filtering an array

Lecture 43 Checking whether given array is empty or not ?

Lecture 44 Creating & Displaying 2D array

Lecture 45 ndim Attribute

Lecture 46 Size Attribute

Lecture 47 Shape and reshape of array

Lecture 48 Creating an Identity Matrix

Lecture 49 arange()

Lecture 50 linspace()

Lecture 51 Random array

Lecture 52 Random matrix

Lecture 53 Creating a diagonal matrix

Lecture 54 Flatten a Matrix

Lecture 55 Computing Trace of a Matrix

Lecture 56 Finding Transpose of a Matrix

Lecture 57 Negative indexing to access elements in a 2D array

Section 3: Data Handling using Pandas

Lecture 58 Introduction to Pandas

Lecture 59 Working with series in Pandas

Lecture 60 Combining series with Numpy

Lecture 61 Finding number of elements in a series

Lecture 62 Computing mean, max and min in a series

Lecture 63 Sorting a Series

Lecture 64 Displaying Unique values in a Series

Lecture 65 Summary of series statistics

Section 4: Data Visualization using Matplotlib in Python

Lecture 66 Introduction to Matplotlib

Lecture 67 Creating Line Graph

Lecture 68 Creating Bar Graph

Lecture 69 Creating Scatter Graph

Lecture 70 Creating Histogram Graph

Lecture 71 Creating Pie Chart

Lecture 72 Creating 3D Plot

Lecture 73 Creating 3D Line graph

Section 5: Data Visualization using Seaborn in Python

Lecture 74 Understanding a sample Dataset (Downloadable)

Lecture 75 Introduction to Seaborn

Lecture 76 Swarm Plot

Lecture 77 Violin Plot

Lecture 78 Facet Grids

Lecture 79 Heatmap

Section 6: Problem Solving Assignments

Section 7: Projects

√ This course is for you if you want to learn NumPy, Pandas, and Matplotlib 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, and Matplotlib courses that are too brief, too simple, or too complicated. √ This course is for you if you want to build real-world applications using NumPy or Panda and visualize them with Matplotlib. √ 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 master the in-and-out of NumPy, Pandas, and data visualization. √ 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.

#### Course Information:

Udemy | English | 5h 49m | 2.43 GB

Created by: Surendra Varma Pericherla

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