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Learn Data Science With Python

This data science with Python tutorial will help you learn the basics of Python along with different steps of data science according to the need of 2023 such as data preprocessing, data visualization, statistics, making machine learning models, and much more with the help of detailed and well-explained examples. This tutorial will help both beginners as well as some trained professionals in mastering data science with Python.

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What is Data Science

Data science is an interconnected field that involves the use of statistical and computational methods to extract insightful information and knowledge from data. Python is a popular and versatile programming language, now has become a popular choice among data scientists for its ease of use, extensive libraries, and flexibility. Python provide and efficient and streamlined approach to handing complex data structure and extracts insights....

Introduction

Introduction to Data Science What is Data? Python for Data Science Python Pandas Python Numpy Python Scikit-learn Python Matplotlib...

Python Basics

Taking input in Python Python | Output using print() function Variables, expression condition and function Basic operator in python Data Types Strings List Tuples Sets Dictionary Arrays Loops Loops and Control Statements (continue, break and pass) in Python else with for Functions in Python Yield instead of Return Python OOPs Concepts Exception handling...

Data Processing

Understanding Data Processing Python: Operations on Numpy Arrays Overview of Data Cleaning Slicing, Indexing, Manipulating and Cleaning Pandas Dataframe Working with Missing Data in Pandas Pandas and CSV Python | Read CSV Export Pandas dataframe to a CSV file Pandas and JSON Pandas | Parsing JSON Dataset Exporting Pandas DataFrame to JSON File Working with excel files using Pandas Python Relational Database Connect MySQL database using MySQL-Connector Python Python: MySQL Create Table Python MySQL – Insert into Table Python MySQL – Select Query Python MySQL – Update Query Python MySQL – Delete Query Python NoSQL Database Python Datetime Data Wrangling in Python Pandas Groupby: Summarising, Aggregating, and Grouping data What is Unstructured Data? Label Encoding of datasets One Hot Encoding of datasets...

Data Visualization

Data Visualization using Matplotlib Style Plots using Matplotlib Line chart in Matplotlib Bar Plot in Matplotlib Box Plot in Python using Matplotlib Scatter Plot in Matplotlib Heatmap in Matplotlib Three-dimensional Plotting using Matplotlib Time Series Plot or Line plot with Pandas Python Geospatial Data Other Plotting Libraries in Python Data Visualization with Python Seaborn Using Plotly for Interactive Data Visualization in Python Interactive Data Visualization with Bokeh...

Statistics

Measures of Central Tendency Statistics with Python Measuring Variance Normal Distribution Binomial Distribution Poisson Discrete Distribution Bernoulli Distribution P-value Exploring Correlation in Python Create a correlation Matrix using Python Pearson’s Chi-Square Test...

Machine Learning

Supervised learning...

Natural Language Processing

Introduction to Natural Language Processing Text Preprocessing in Python | Set – 1 Text Preprocessing in Python | Set 2 Removing stop words with NLTK in Python Tokenize text using NLTK in python How tokenizing text, sentence, words works Introduction to Stemming Stemming words with NLTK Lemmatization with NLTK Lemmatization with TextBlob How to get synonyms/antonyms from NLTK WordNet in Python?...

How to Learn Data Science?

Usually, There are four areas to master data science....

Applications of Data Science

Data science is used in every domain....

Career Opportunities in Data Science

Data Scientist : The data scientist develops model like econometric and statistical for various problems like projection, classification, clustering, pattern analysis. Data Architect : The Data Scientist performs a important role in the improving of innovative strategies to understand the business’s consumer trends and management as well as ways to solve business problems, for instance, the optimization of product fulfilment and entire profit. Data Analytics : The data scientist supports the construction of the base of futuristic and various planned and continuing data analytics projects. Machine Learning Engineer : They built data funnels and deliver solutions for complex software. Data Engineer : Data engineers process the real-time gathered data or stored data and create and maintain data pipelines that create interconnected ecosystem within an company....

FAQs on Data Science Tutorial

Q.1 What is data science?...