Contents/Topics For Python Course



Contents/Topics For Python Course



Module 1



An Overview of Python



The Philosophy of Python



Python 2 vs Python 3



Installing Python 3 on Windows



Installing Python 3 on Linux



Python IDEs



Module 2



Whitespace in Python



Read, Evaluate, Print, Loop



Hello World



User Input

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Module 3



Modules and Imports



The int Type in Python

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The float Type in Python



Basic Math Functions in Python

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Module 4

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The bool Type in Python

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The str Type in Python

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The bytes Type in Python

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The bytearray Type in Python

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Module 5

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The list Type in Python

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The tuple Type in Python

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Slicing in Python

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The range Type and Function in Python

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The set Type in Python

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The dict Type in Python

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Module 6



The While Loop in Python



The For Loop in Python

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The if Statement in Python

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Module 7



NumPy Mathematical Library in Python



Dimensions of Array

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Array operations

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Create a Rank 2 Array

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Create Numpy Array of 3x3 with all zeroes

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Create a 2 x 2 Array with all ones

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Create a 3 x 3 Array with constant values



Create a 3 x 3 Array with random values

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Create Identity Matrix



Create a 3 x 3 matrix with random values with in range



Array to List conversions

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Module 8



Datatype management in Arrays



Create linear values of evenly spaced numbers with in a range

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Grid Indexed Arrays



Automatic and Forced Datatypes in Arrays



Slicing in Arrays



Module 9



Pandas Data Management Library



Create Series in Pandas

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Create 2D Objects similar to SQL Table



Reading and Writing Data using pandas



Reading a CSV File



Reading a TXT File



Reading an Excel File



Reading different Excel sheets with in one file



Reading from MySQL Databases



Module 10



Compute Count, Mean, Standard Deviation, Minimum, Maximum



Compute covariance between columns in DataFrames

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Compute correlation between columns in DataFrames

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Head, Tail, Columns, Data types operations on DataFrames



Get unique values from columns in DataFrames



Get row wise values from columns in DataFrames



Implement Sorting in Data Frames



Implement Select Statements in Data Frames using Conditions



Select rows from Data Frames using Row Indexes



Select rows from Data Frames using Positions



Select rows from Data Frames using Matrix Style



Module 11



Faster alternative to get scalar values from Data Frame



Transpose operations on Data Frames



Filter operations on Data Frames using Single Columns



Filter operations on Data Frames using Multiple Columns



Date Series conversions



Rename columns in Data Frames



Mark duplicates in Data Frames



Drop duplicates from Data Frames



Drop missing values from Data Frames



Add new columns in Data Frames from Lists



Compute cumulative sum of each column in Data Frames



Merge and Join operations



Module 12



Matplotlib Graphical Library



Create a bar plot



Create a scatter plot

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Create a box plot



Create a histogram



Create a line Plot



Create a bar plot for Student and Marks Scored



Customization of Plot Labels



Create Multiple Line plots on same axis



Create Multiple Line plots on multiple axis

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Line Styles and Markers for graphs

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Module 13



Data Transformation techniques in python



Label Binarizer



Label Encoding



Standardization of data

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Normalization of data



MinMax scaling of data



Exploratory analysis in python



Correlation Histogram Plots



Correlation Matrix



Projects Covered



Student Test Grade Prediction System



Live Cricket Score Prediction System



Attacker Detection and Prediction System



Mobile User Activity Identification and Prediction System



Breast Cancer Diagnosis System



Fake / False Comments & Feedback Identification system