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Module - 1
What is Artificial Inetelligence
What is Machine Learning
What is Deep Learning
What is Data Science
What is Data Science
Module - 2 - Numpy Introduction
Introduction to Numpy
How to create an Array in Numpy and different way to create an array
Module - 3 - Indexing and Slicing
Numpy Array Indexing
Numpy Advanced Indexing
Module-4 Different Data Types NumPy and Converting data types in python
NumPy Data Types
Module-4 Array Manipulation
NumPy Array Shape
NumPy Array Reshaping
Module-5 Iteration over an Array
NumPy Array Iterating
Module-6 NumPy Joining the array
NumPy Joining Array
Splitting the Array in NumPy
NumPy Splitting Array
NumPy Array Search
NumPy Searching Arrays
NumPy Array Sort
NumPy Sorting Arrays
Module-7 Numpy-Random
Random Introduction
Normal Distribution "
"2.Binomial Distribution "
"3.poission Distribution "
4.Uniform Distribution
Module-8 Introduction
Introducrion of Pandas
Module-9 Pandas-Series
How to creat a Pandas Series
Module-10 Pnadas Data Frame
How to create a pandas data frame and different ways to create data frame
Data Frame Basic Functionality for Data Science
Iterate over Pandas DataFrame
"1.How to iterate over DataFrame 2.Iterate Using Index Method "
3.Iterate Using loc function
4.Iterate Using Iloc Function
"4.Iterate Using iterrows method "
5.Iterate Using itertuples Method
Module-11 Handling Missing Values
"Theory Session 1.What is Missing Values 2.How to impute the Misisng values"
"Practical Session 3.How to find Missing value with various technique"
4.Handling Missing value with Dropna Function.
5.handle missing value in Numerical Data with fillna function
6.handle and impute missing value on categorical Data with fillna Function
7.Imputing missing value in Both Numerical and Categorical variable at once with Lambda Function
7.Imputing missing value in Both Numerical and Categorical variable at once with Lambda Function
Module-12 Sorting Data
Pandas Sort DataFrame By single Column
"Pandas Sort DataFrame By Multiple Column Sort Data Frame "
Soritng by index in Ascending/ Descending Order
Soritng by index in Ascending/ Descending Order
Working with missing data when sorting
Module-13 Guoup By In Pnadas
How to Grouping the Data in Pnadas
How to marge two DataFrame In Pnadas
MatplotLib Tutorials
"1.Introduction of Matplotlib 2.Matplotlib Plotting "
3.Matplotlib Marker
4. Matplotlib LIne
5. Matplotlib set grid line
6.Matplotlib set subplot
7. Matplotlib Scatter Plot
8. Matplotlib Bar Graph
9. Matplotlib Histogram
10. Matplotlib Pie Chart
Statistics
What is Statistics
Types of Data in Data Science
Understanding the difference between a population and a sample
Measure of central Tendancy
What is mean and How to calculate the mean
What is Median How to calculate the median
"The measure of the spread Whatares variance and standard deviation and how to calculate it?"
Calculating and Understanding the covariance
What is distribution
Understand the Normal Distribution
Understand the Standard Normal Distribution
Working with Eastimator and Estimate
Student T Distribution
calculating confidence intervals within a population with an unknown variance
Hypothesis Testing
Test for the mean. Population variance known
What is P-value why it is one of the most useful tools for data science
Machine Learning
What is Machine Learning
What is Supervised Learning
What is unsupervised learning
"Importing the libraries importing the DataSet"
How to Describe the Data
Check Unique Value
How to Filter the Data using loc and Iloc function
Filter and Group the data groupby function
Filter the data using iteration
Filter the data using Crostab method
Filter the data using Pivot table
Find Missing value throgh graph
Count the value through the countplot
Find the skewness in the Data
Find the outliers in the Data
Encoding Categorical Data with one hot encodeing
Encoding Categorical Data with one label encoding
Splitting the dataset into the training set and test
What is Regresion
Simple Linear regression intution
Simple Linear Regression Mathematical equation
R-Square Mathematical Solution
Simple Linear Regression Practical Session
What is Multiple Linear Regression and It's assumption
Multiple Linear Regression Practical Part 1
Polynomial regression intituiion
Polynomial Regression Practical Session
Support Vector Machine Intition
Support Vector Machine Practical Session
Decision Tree intution
Decision Tree Practical Session
Random Forest Intution
Random Forest Practical Session
Logistic Regression Intution
Logistic Regression Practical session
KNN Regression Practical Session
K means Practical session