Module 1: DATA SCIENCE & PYTHON INTRODUCTION
-Python Introduction
-Installation
-Variables
-Data types
-Operators
-Input
-Comments
Module 2: LOOPS
-If statements
-If..else statements
-While loop
-For Loops
Module 3: FUNCTIONS
-Basic math
-Advanced Mathematical Operators
-Creating your own functions
-Defining functions in python
-Advanced Math function creation
Module 4: DATA STRUCTURE OPERATIONS
Array
-Accessing Array
-Slicing
-Insert
-Modify
-Pop
-Scalar
-Vector
-0D,1D,2D,3D,4D,5D
List
-Len
-Append
-Insert
-Clear
-Del
-Remove
-Pop
-Index
-Count
-Sort
-Reverse
-Concatenation
-Type
-In and not in statement
-Replication
-List function
Tuples
-Len
-Concatenation
-Tuple
-Count
-Index
-Accessing using array
-Negative indexing with different ranges
-Replication
Sets
-Add
-Update
-Remove
-Clear
-Len
-Del
-Union
-Intersection
-Difference
-Discard
-Pop() with no arguments
-Set()
-Issubset()
Dictionaries
-Len
-Adding new key value
-Pop
-Popitem
-Del
-Clear
-Copy
-Items
-Values
-Keys
-Dict
Module 5: FILE HANDLING
File Operations
-Open()
-Read()
-Read by passing values()
-Readline()
-Write()
-Append()
-Remove()
-Close()
-Access mode
-Buffering
Read Files
-Create Files
-Delete Files
-Writing Files
Module 6: TYPE CONVERSION
-Int to str
-Int to float
-Str to float
Module 7: FUNCTIONAL PROGRAMMING
-Map
-Filter
-Lambda
Module 8: MODULES & LIBRARIES
Functions,Modules and standard libraries
-System version
-Getcwd
-System platform
-Datetime
-Components of datetime
-Time
Numpy
-0D,1D,2D,3D
-Ndim
-Version
-Ndimn
-Dtype
-Int
-Float
-Complex
-i1,i2,i4
-arange
-Numpy Zeros
-Numpy ones
Creating Array Indexing
-2D indexing
-3D indexing
-Negative indexing
Creating Array Slicing
-Using parameter
-Using colon
-Using 2D
-Using 3D
Array shape & Reshaping
-Shape
-Flattening numpy array into specific shape
-Reshape
Module 9: DATA VISUALIZATION USING PYTHON
-Matplotlib Introduction
-Matplotlib Plotters
-Matplotlib Bar Plotters
-Matplotlib Scatters
-Two different scatters
-Matplotlib Grids & Bars
-Seaborn point plotters
Module 10: Pandas
-Introduction
-Pandas version
-Series
-Series data creation
-Series creation with custom index
-Head
-Tail
-Mean
-Sum
-Type
-Sort_values
-Dataframes
-Rename
-Reset index
-Drop columns and row
-Ascending
Module 11: OpenCV
-RGB image
-Gray scale image
-RGB to grayscale conversion
-Imread
-Imwrite
-Imshow
-Imreadcolor
-Imgshape
-Imgresize
-BGRTORGB
-Image(Rowshape,columnshape)
-Reshape array (3D to 2D)
Module 12: Counters
-Mostcommon()
-Mostcommon(Using Slicing)
-Mostcommon(Using negative indexing)
-Zip()
-Barchart using Counters
Module 13: Processing Functions
-Rand
-randInt
-linspace
-rand with parameters
-seed
-uniform
-random.random
-arrange
-argmax
Module 14: Installing packages
-Pip install
-Pip list
Module 15: OOPS Concept
Classes
-Creation
-_init_ constructor
-Self
Objects
-Attributes
-Methods
-Modify object
-Delete object with attribute
-Delete object
-Accessing object with attributes
-Object Methods
-Object Method call
Inheritance
-Parent class creation
-Child class
-Accessing parent class from child class
Encapsulation
-Data hiding
-Public method
-Mangling method
-Access specifiers
-Public
-Private
-Protected
Polymorphism
Operator overloading
Module 16: Statistics
-Mean
-Median
-Mode
-Variance
-Standard deviation
Module 17: ADVANCED DATA STRUCTURES IN PYTHON
-List
-Tuples
-Set
-Dictionary
-Counter
Module 18: ADVANCED DATA FRAMES(USING REAL DATASET)
-Dataframes in Python Using Real Time Dataset
-Dataset Description using dataframes
-Loading Dataset
-Display Records of Dataframes
-Value Counts and Cross Tabulation
-Sorting Dataframes
-Creating New Columns
-Grouping and Aggregating
-Joining Dataframes
-Filtering Records
Module 19: CLUSTERING (USING REAL DATASET)
-Clustering
-How Clustering works
-Finding Similarities Using Distances
-Euclidean Distance
-Cosine Similarity
-K-Means Clustering
-Plotting with Segments
-Cluster Centers
Module 20: FORECASTING (USING REAL DATASET)
-Forecasting Overview
-Components of Time-Series Data
-Moving Average
1.Loading and visualizing the TimeSeries Dataset
2.Forecasting using Moving Average
Module 21: ADVANCED COMPUTER VISION TECHNIQUES
-Invariant Transformation
-Grayscale contrast and stretching
-Bilateral Filtering
-Thresholding
-Contours