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What you will learn

 

Start with Basics of Python like Lists and Function and move up to Numpy

 

Coding Exercises for Python

 

Learn the best practices of using Python for Data Science

 

Complete Numpy Basics

 

Practice in coding exercises and participate in quizzes

 

Grasp on how to summarize large data using NumPy

 

Statistical Analysis using NumPy for Data Analysis

 

Summarizing using Numpy on large dataset

Description

The new gold is data. This statement demonstrates how data capture, storage, and analysis are at the heart of every modern IT system. It doesn’t matter if you’re making a business choice, forecasting the weather, investigating protein structures in biology, or creating a marketing strategy. All of these scenarios call for a multidisciplinary approach that includes the use of mathematical models, statistics, graphs, databases, and, of course, the commercial or scientific rationale that underpins the data analysis. As a result, we need a programming language that can handle all of these different data science requirements. Python stands out as one of these languages since it comes with a plethora of libraries and built-in capabilities that make it simple to meet the demands of data research.

This beginner-friendly introduction to Python will help you get started learning Python for data science and programming in general. Python is one of the most widely used programming languages in the world, and there has never been a bigger demand for individuals who can apply Python basics to drive business solutions in a variety of industries.

 


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In this course, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular Python libraries, including NumPy.This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary!

 

What you’ll learn:

  • Programming with Python

  • NumPy with Python

  • The basic process of data science

  • Python IDEs and notebooks

  • An applied understanding of how to manipulate and analyze uncurated datasets

  • Basic statistical analysis

  • How to visualize the results

  • 30+ coding exercises and quizzes

Gain the career-building Python skills you need to succeed as a data scientist. No prior coding experience is required.

By the end of this course, you’ll feel comfortable creating basic programs, working with data, and solving real-world problems in Python. You’ll gain a strong foundation for more advanced learning in the field, and develop skills to help advance your career.

 

English
language

Content

Introduction

Introduction
The right development environment

Basics of Python

Experiencing with Udemy’s Python Interpreter
The Python Interface
Python as a Calculator
Python Mathematics warmup exercise
VS Code Tips: Keyboard Shortcut to run Python File
Variables and Data Types
Variable Assignment
Calculate the coumpound interest
Calculations with variable
Other Variable Types
String Concatenation
Conversion

Python List fiesta

Understanding the Python List
Different Types of Python List – in Code
Examples on all there are to Python Lists
Create LIST
List of Lists
Sub-setting Python
Calculation from Subset
Slicing and Dicing
Subsetting List of Lists – Quiz
Manipulating List
Replacing List Elements
Extending List Elements
Deleting List Elements

Functions

Functions in Python
Examples of Python Functions
A little we already know
Help(Range)
Multiple Arguments
Methods in Python
String Methods
List Methods
List Method 2
Function Package
Importing Package
Selective Import
Different ways of importing

NUMPY

NumPy
Getting started with NumPy
NumPy Calculation
More NumPy Calculations
Boolean NumPy Array
NumPy and List – difference
Subsetting NumPy arrays
2D NumPy arrays
2D NumPy Array
Subsetting NumPy Arrays
NumPy Statistics
Feel what data are saying
Continuing with the data story
Final with Soccer story
A final note

 

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