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Artificial Intelligence

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Level-1(Understanding Of AI)
What is AI Sub Topic
Introduction What is AI?
What does AI do?
Where did AI come from?
Why People Worried about AI
Types of AI
What to Expect from AI and its day to day

uses

Steps to Built a good AI Model Identify the problem.
Get and Prepare the data.
Choose the algorithms.
Train the algorithms.
Choose a programming language.
Run on a selected platform.
Understanding the Data Sub Topic
What is data Definition of Data
Understanding the data around us
Type of Data Data Definition
Understanding Structured Data What Is Structured data
Sources in everyday life
Concept required to understand Structure data
Understanding Un Structured Data What Is Un Structured data
Sources in everyday life
Concept required to understand Un Structure data
Power Of BI Operating On BI Tool for Data Interpretation
Level-2
Preparing the Data Subtopic
Extracting the data Using SQL
Clean the data Using SQL
Data Spliting Using SQL
Getting Data Ready For AI systems
Python Topics Subtopic
Introduction To Python Python Installation
Using Jupiter
Using Anaconda
Values and Variables Integer Values
Variables and Assignment
Identifiers
Floating-point Types
Control Codes within Strings
User Input
The eval Function
Controlling the print Function

 

Expressions and Arithmetic Expressions
Operator Precedence and Associativity
Comments
Errors
Syntax Errors
Run-Time Errors
Logic Errors
Arithmetic Examples
More Arithmetic Operators
Algorithms
Conditional Execution Boolean Expressions
Boolean Expressions 2.0
The Simple if Statement
The if-else Statement
Compound Boolean Expressions
Nested Conditionals
Multiway Decision Statements
Conditional Expressions
Errors in Conditional Statements
Iteration The while statement
Definite Loops vs Indefinite Loops
The for statement
Nested Loops
Abnormal Loop Termination
The break statement
The continue statement
Infinite Loops
Iteration Examples
Computing Square root
Drawing a Tree
Printing Prime Number
Insisting on the Proper Input
Numpy Library Introduction to NumPy
Understanding Data Types in Python
Fixed Type Arrays in Python
Creating Arrays from Scratch
The Basics of NumPy Arrays
Array Slicing – Accessing Subarrays
Reshaping of Arrays
Splitting of Arrays
Splitting of Arrays – 2
Exploring NumPy’s UFuncs
Exponents and Logarithms
Advanced UFunc Functions

 

Aggregations
Computation on Arrays – Broadcasting
Broadcasting Example
Broadcasting in Practice
Comparisons, Masks and Boolean Logic
Boolean Operators
Boolean Arrays as Masks
Fancy Indexing
Combined Indexing
Modifying values with Fancy Indexing
Sorting Arrays
Fast Sorting in NumPy
Example: k-Nearest Neighbors
Structured Data – NumPy’s Structured Arrays
Data Manipulation with Pandas Introduction
Installing and Using Pandas
Introducing Pandas Objects
Constructing Series Objects
The Pandas DataFrame Object
DataFrame as a specialized Dictionary
The Pandas Index Object
Data Indexing and Selection
Data Selection in DataFrame
DataFrame as two-dimensional array
Operating on Data in Pandas
UFuncs Index Alignment
Index alignment in DataFrame
Ufuncs Operations Between DataFrame and Series
Handling Missing Data
Missing Data in Pandas
NaN and None in Pandas
Hierarchical Indexing
The better way Pandas MultiIndex
Methods of MultiIndex Creation
MultiIndex for columns
Indexing and Slicing a MultiIndex
Rearranging Multi-Indices
Index setting and resetting
Data Aggregations on Multi-Indices
Combining Datasets Concat and Append
Duplicate indices
Catching the repeats as an error
Combining Datasets Merge and Join
Specification of the Merge Key

 

Specifying Set Arithmetic for Joins
Aggregation and Grouping
GroupBy Split, Apply, Combine
Iteration over groups
Aggregate, filter, transform, apply
Transformation
Pivot Tables
Pivot Table Syntax
Vectorized String Operations
Methods using regular expressions
Working with Time Series
Dates and times in Pandas Best of both worlds
Pandas Time Series Data Structures
Using Functions Introduction to Using Functions
Standard Mathematical Functions
time Functions
Random Numbers
Importing Issues
Writing Functions Function Basics
Using Functions
Main Function
Parameter Passing
Function examples
Better Organized Prime Generator
Command Interpreter
Restricted Input
Better Die Rolling Simulator
Tree Drawing Functions
Floating Point Equality
Custom Functions vs Standard Functions
More on Functions Global Variables
Default Parameters
Recursion
Making Functions Reusable
Documenting Functions and Modules
Functions as Data
Lists Using Lists
List Assignment and Equivalence
List Bounds
Slicing
Lists and Functions
Prime Generation with a List
List Processing Sorting
Flexible Sorting

 

Search
Linear Search
Binary Search
List Permutations
Randomly Permuting a List
Reversing a List
Classes & Objects Using Objects
String Objects
Level-3(AI playing field and rules to play for it)
Python Topics Subtopic
Introduction ML Introduction
What is Machine Learning?
Examples of Machine Learning Applications
Learning Association
Classification
Regression
Introduction Stats & coding Essential Libraries and Tools
A First Application Classifying Iris Species
Measuring Success Training and Testing Data
First Things Fast – Look at your Data
Building your first model k-Nearest Neighbors
Making Predictions
Supervised Learning with Python Supervised Learning
load_breast_cancer function from scikit-learn
Data set analysis
Linear Models
Linear regression (aka ordinary least squares)
Ridge regression
Boston Housing dataset and evaluated LinearRegression
Lasso
Linear models for classification
Decision boundaries of a linear SVM
Coefficients Learned by the models with the three different settings
Linear Models for Multiclass Classification
Predictions for all regions of the 2D
Strengths, weaknesses, and parameter
Decision Trees
Decision Trees Decision Trees
Introduction
Univariate Trees
Classification Trees
Regression Trees
Pruning
Start On January 1, 2020
Duration 6 Months
Instution PCTIL
Branch Pitampura, New Delhi

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