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Course Type : paid
Duration : 70 hrs
Category
AI and Data Science
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Data Analysis with Python

Course Description

<p>Data analysis&nbsp;is a process of inspecting,&nbsp;cleansing,&nbsp;transforming, and&nbsp;modeling&nbsp;data&nbsp;with the goal of discovering useful information, informing conclusions, and supporting decision-making.The purpose of Data Analysis is&nbsp;to extract useful information from data and taking the decision based upon the data analysis.</p>

Curriculum

    • Introduction to Programming
    • Introduction to Python and How Python Works
    • Introduction to Python Basic Course Structure
    • How to install Python
    • How to run Python Program using Command Line Window, IDLE, Notepad
    • How to install Anaconda and run jupyter notebook for python
    • Comments, Identifier, Reserved Words and Constant in Python
    • Variable in Python
    • Data Type in Python
    • Declaring and Intializing Variables in Python
    • Operators in Python
    • Implicit and Explicit Type Conversion in Python
    • Output Statement or Print Function in Python
    • Getting input from user or Input Statement or input Function in Python
    • Escape Sequence in Python
    • If Statement in Python
    • Nested if Statement in Python
    • if Statement with Logical Operator in Python
    • Indentation in Python
    • if else Statement in Python
    • Nested if else Statement in Python
    • if elif and if elif else Statement in Python
    • range Function in Python
    • For Loop and Nested for Loop in Python
    • Enumerate() in Python with EXAMPLES
    • While Loop and Nested while Loop in Python
    • Break, Continue and Pass Statement in Python
    • String in Python
    • More on Strings(Access string using loop, repetitation and concatenation in string, mutable and immutable)
    • String Formatting in Python
    • String Methods in Python
    • List in Python
    • List methods in python
    • More on Lists (Use loops with list, slicing in list, concatenation, repeatition, aliasing, copying and cloning in list)
    • Nested List in Python
    • Tuple and tuple methods in Python
    • More on Tuple(Use loops with tuple, slicing tuple, concatenation, repeatition, aliasing, copying tuple, getting user input as tuple, modifying and deleting tuple)
    • Nested Tuple in Python
    • Set Type in Python
    • Set methods in Python
    • Nested Set in Python - FrozenSet
    • Dictionary in Python
    • Dictionary methods in Python
    • More on Dictionary (Loop in Dictionary, Getting Dictionary input from user)
    • Nested Dictionary in Python
    • Function and How Function Work in Python
    • Arguments and its types in Python
    • Local and Global Variable in Python
    • global Keyword and function in Python
    • Passing and returning List, Tuple, Set, Dictionary in Function
    • Recursion in Python
    • Anonymous Function or Lambda Expression in Python
    • Function Decorator in Python
    • Ternary if
    • List, Tuple, Set and Dictionary Comprehension in Python
    • Nested Comprehension in Python
    • Generator Function Yield Statement and Next Function in Python
    • Type and isinstance Function in Python
    • Len,min,max and sorted Function
    • Zip method
    • Filter, map Function in Python
    • Tips and Tricks in Python
    • Getting Help in Python
    • Class and Object in Python
    • Constructor in Python
    • Inheritance in Python
    • Constructor in Inheritance
    • Method Overloading, Overriding and Method with super in Python
    • Special (Magic/Dunder) Methods
    • Exception Handling and Builtin Exception in Python
    • User Defined Exception in Python
    • Difference between Error and Exception and Warning in Python
    • Installing VSCode and coding in VSCode
    • Debugging in VSCode
    • Introduction to Virtual Environments
    • Using conda and virtual environments with VSCode
    • Module in Python, Math module in python
    • Datetime Class in Python
    • Random, sleep in Python
    • Functools(Reduce and Memoization), getpass(getpass and getuser) and sys Module
    • if __name__ == "__main__"
    • What is File and File Handling in Python
    • Reading Files in Python
    • Write Create Files in Python
    • What is git/ What is Version control system?
    • What is Github?
    • How To Insatll Git
    • Basic Commands: add, commit, push
    • Undoing/Reverting/Resetting code changes
    • Branches (Create, Merge, Delete)
    • What is HEAD?
    • .gitignore file
    • Diff and Merge using vscode
    • What is Pull Request?
    • Brief intro to working with git, github with help of vscode and github desktop
    • Introduction to Libraries
    • Introduction to Web Scrapping - Beautiful Soup
    • Project 1 - Web scraping table from wikipedia
    • PyQt Tutorial: Python GUI Designer
    • Project 2 - Making a simple calculator
    • Image Manipulation with Pillow
    • Project 3 - Adding logo into Multiple images at once.
    • Data on the Web
    • eXtensible Markup Language(XML)
    • XML Schema
    • Parsing XML
    • JSON Introduction
    • Encoding JSON Python Objects
    • Decoding JSON Python Objects
    • Connecting to a server
    • A simple server-client program
    • What is Database?
    • Connect to Database in Python
    • Create a Table
    • Insert Record into Table
    • Query and Fetchall
    • Use the Where Clause
    • Course Introduction
    • Classroom and Chat media Setup and Overview
    • Jupyter Notebook and Other required Media installation.
    • Introduction to Data Science
    • Numpy Array Creation
    • Numpy Indexing
    • Numpy Array Operation
    • Numpy Problem
    • Numpy Quiz
    • Numpy Practical Application
    • Numpy Exercise
    • Series
    • DataFrames
    • Index Objects
    • Reindex
    • Drop Entry
    • Selecting Entries
    • Data Alignment
    • Rank and Sort
    • Summary Statistics
    • Missing Data
    • Index Hierarchy
    • Reading and Writing Text Files
    • JSON with Python
    • HTML with Python
    • Microsoft Excel files with Python
    • Merge
    • Merge on Index
    • Concatenate
    • Combining Dataframes
    • Reshaping
    • Pivoting
    • Duplicates in DataFrames
    • Mapping
    • Replace
    • Rename Index
    • Binning
    • Outliers
    • Permutation
    • GroupBy on DataFrames
    • GroupBy on Dict and Series
    • Aggregation
    • Splitting Applying and Combining
    • Cross Tabulation
    • Creating and Customizing Our First Plots
    • Bar Charts and Analyzing Data from CSVs
    • Pie Charts
    • Stack Plots
    • Filling Area on Line Plots
    • Histograms
    • Scatter Plots
    • Plotting Time Series Data
    • Plotting Live Data in Real-Time
    • SubPlots
    • Installing Seaborn
    • Histograms
    • Kernel Density Estimate Plots
    • Combining Plot Styles
    • Box and Violin Plots
    • Regression Plots
    • Heatmaps and Clustered Matrices
    • Data Projects Preview
    • Titanic Project
    • What is Plotly?
    • Installation
    • Line Plots
    • Bar Charts
    • Scatter Plot
    • Pie Charts
    • Histograms
    • Box Plots
    • Violin Plot
    • Density Heatmap
    • 3D Scatter Plots
    • 3D Line Plots
    • Scatter Matrix
    • Map Scatter Plots
    • Choropleth Maps
    • Polar Chart
    • Ternary Plot
    • Facets
    • Animated Plots
    • What is EDA?
    • 2D, 3D plots and Findings
    • Probability Density Function and KDE
    • Calculate Cummulative Distribution Function
    • Use of Mean, Variance, Standard Deviation
    • Use of Median, Percentile, Quantile, IQR, MAD
    • Box plot and Whiskers median, quantile, IQR
    • Violin plots and why we use it
    • Summarizing plots in english
    • Univariate, Bivariate and Multivariate Analysis
    • Multivariate probability density, contour plot
    • Exercise

Instructor

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