Ch 1. Python Introduction

• Need for Data Analytics
• Python in Data Analysis
• History of Python
• Python Versions
• Python Implementations
• Python Installations
• Python IDE & Usage
• Jupyter Notebooks

Ch 2. Python Basics, Architecture

• Python Scripting Options
• Basic Operations in Python
• Python Scripts, Print()
• Single, Multiline Statements
• Adding Cells, Saving Notebook
• Single, Multi Line Comments
• Python : Internal Architecture
• Compiler Versus Interpreter

Ch 3. Data Types & Variables

• Integer / Int Data Types
• Float & String Data Types
• Boolean, Binary Types
• Sequence Types: List, Tuple
• Range, Complex & memview
• Retrieving Data Type: type()
• Multi Assignments & Casting
• Unpack Collection, Outputs

Ch 4. Python Operators

• Arithmetic, Assignment Ops
• Comparison Operators
• Logical, Identity Operators
• Member, Bitwise Operators
• Operator Precedence
• If … Else Statement, Pass
• Short Hand If, OR, AND
• ELIF and ELSE IF Statements
• Expressions, Ternary OPs

Ch 5: Python Loops, Iterations

• Python Loop & Realtime Use
• Python While Loop Statement
• Break and Continue Statement
• Using Print with While()
• Iterations & Conditions
• Exit Conditions & For Loops
• Break, Continue & Range
• __iter__() and __next__()
• iter() and Looping Options

Ch 6: Python Collections

• Python Collections (Arrays)
• list() Constructor, print()
• Python Tuples, Tuple Items
• tuple() Constructor, Usage
• Python Sets : Syntax Rules
• Duplicates, Types, Ordered
• Python Dictionaries: Usage
• Changeable, Ordered Data
• Dictionary Construct, type()

Ch 7: Python Functions

• Python Functions & Usage
• Function Parameters
• Arguments, **kwargs
• Default & List Parameters
• Python Lambda Functions
• Anonymous Functions
• Recursive Functions, Usage
• Return & Print @ Lamdba

Ch 8: Python Classes & Arrays

• Python Classes & Objects
• __init__() Function
• __str__() Function
• Self Parameters & Objects
• Python Inheritance & Classes
• Parent & Child Classes
• __init__() & super() Function
• Polymorphism in Python

Ch 9: Python Modules

• import Python Modules
• Variables in Modules
• Built In Modules & dir
• datetime module in Python
• Date Objections Creation
• strftime Method & Usage
• imports & datetime.now()
• Using Python Constructors

Ch 10: : Python JSON & RegEx

• JSON Concepts, Usage
• Dictionary & import json
• Python Objects into JSON
• Formatting & Ordering
• json.dumps, print options
• Python Regular Expressions
• RegEx Module & Function
•  search() & span() , Strings
• Using RegEx with JSON

Ch 11: Python User Inputs & TRY

• Try Except, Exception Handling
• NameError Resolution
• Python Finally Block, Usage
• Raise an exception method
• TypeError, Scripting in Python
• Python User Inputs
• Python Index Numbers
• Named Indexes, Usage
• input() & raw_input()

Ch 12: Python File Handling

• File Handling, Activities
• r, a, w, x modes
• t, b Operations
• Read Only Parts
• Loop, Write, Close Files
• Appending, Overwriting
• import os, path.exists
• f.open, f.write
• f.read, f.close

Ch 13: Data Analytics – Pandas

• Python Modules & Pandas
• Pandas Codebase & Usage
• Installation of Pandas
• import pandas.DataFrame
• Checking Pandas Version
• Pandas Series, arrays
• Labels : Creation, Use
• series(), print()

Ch 14: Data Analytics – DataFrames

• Indexes & Named Options
• Locate Row and Load Rows
• Row Index & Index Lists
• Load Files Into a DataFrame
• pd.read_csv() Function
• pd.options.display.max_rows
• df.to_string() Function
• tail() & null() Function

Ch 15: Data Analytics – Pandas

• Pandas – Cleaning Data
• Replace, Transform Columns
• Data Discovery & Column Fill
• Identify & Remove Duplicates
• dropna(), fillna() Functions
• Pandas – Data Correlations
• Good & Bad Correlation
• Data Plotting & matlib Lib

Ch 16: : SQL DB & Python – 1

• SQL & Databases
• Azure Data Studio Tool
• sp_execute_external_script
• Input Data & Result Sets
• DDL & DML with Python
• SQL_out, SQL_in
• Variables & Parameters
• Versions, Package List
• WITH RESULT SETS Options

Ch 17: SQL & Python – 2

• pandas.Series with SQL DBs
• Indexing Methods in Realtime
• Convert series to data frame
• Output values into data.frame
• pymssql package in SQL Server
• pip list & Package Manager
• Python runtime, Py Package
• pymssql.connect & Usage
• Cursor Variables & Usage

Ch 18: Realtime Case Study

Ch 1. Python Dictionary

• Dictionary Creation, Use
• Hashing, Copy, Update
• Deletion, Sorting
• Len(), Inbuilt Functions
• Variable Types – python List
• Cmp() List Method
• Python Dictionary Str(dict)
• Programming Concepts
• Loops and Sets
• Realtime Usage

Ch 2. Python Packages

• Package in Python
• Creating a package
• Package Imports, Modules
• Sub Packages Creation
• Sub Package Imports
• Popular Packages in Python
• NumPy & SciPy
• Libraries in Python
• Python Seaborn
• Python framework

Ch 3. Exception Handling

• Shell Script Commands
• OS operations in Python
• File System Shell Methods
• os – math – cmd -csv – random
• Numpy ( numerical python )
• Pandas – sys – Matplotlib;
• Common RunTime Errors
• Python Custom Exception;
• Exception Handling
• Try…Except…else,Try…finally

Ch 4: Python Class & Objects

• Class variables, Instances
• Built in Class Attributes
• Objects – Constructors
• Modifiers – Self Variable
• Python Garbage Collections
• Hierarchical Inheritance
• Multilevel, Multiple, Hybrid
• Overloading & OverRiding
• Polymorphism – Abstraction

Ch 5: Regular Expressions

• Regular Expression
• Regular Expression Patterns
• Literals – Repetition Cases
• Groups andGrouping
• w+ and ^ , \s Expressions
• re.split function
• Regular expression methods
• re.match() in Regular Expr
• re.search(), re.findall for Text

Ch 6: Multi-Threading

• Python Multi-Threading
• Thread Synchronization
• Multiprocessing
• Python Gil & Programming
• Thread Control Block (TCB)
• Stack Pointers & App Usage
• Program Counters in Realtim
•  Thread State Concept
• Python Exception Handling

Ch 7: Python TKinter

• Tkinter GUI Program
• Components & Events
• Adding Controls inTkinter
• Entry, Text Widgets
• Radio & Check Buttons
• Tkinter Forms in Realtime
• List Boxes, Menu, ComboBox
• Mainloop () & Functions

Ch 8: Python Web & IoT Intro

• Python Web Frameworks
• Django : Advantages
• Web Framework
• MVC and MVT – Django
• Web Pages using python
• HTML5, CSS3 usage
• PYTHON Bottle & Pyramid
• Falcon ; smart_open in python

Ch 15: Data Analytics – Pandas

• Pandas – Cleaning Data
• Replace, Transform Columns
• Data Discovery & Column Fill
• Identify & Remove Duplicates
• dropna(), fillna() Functions
• Pandas – Data Correlations
• Good & Bad Correlation
• Data Plotting & matlib Lib

Ch 1. Machine Learning Basics

• Machine Learning Funda
• Python ML in Realtime
• Pandas Extension in ML
• Machine Learning Ops
• Business to Data Conversions
• ML Algorithms in Realtime

Ch 2. Python ML Concepts

• Machine Learning (ML) Intro
• Supervised, Unsupervised
• Scikit-Learn Library
• Python Libraries for ML
• sklearn : Advantages & Uses
• sklearn : Functions, Use

Ch 3. Python Data Handling

• Data structures
• Lists, Tuples, Sets
• Dictionaries,
• Pandas Data Operations
• Data Visualizations
• Matplotlib & Seaborn

Ch 4. AI With Python Intro

• Artificial Intelligence
• Applications of AI
• AI Applicative Uses
• AI Usage with Python
• AI – Python Environment
• Python Libraries
• AI with Python in Realtime

Ch 5: Supervised Learning

• Linear & Logistic Regression
• Decision Trees
• Random Forests
• Support Vector Machines
• Neural Networks Basics
• Linear Regression Steps
• Linear Regression in AI-ML

Ch 6: Unsupervised Learning – 1

• Clustering & K-means
• DBSCAN & Realtime Usage
• Dimensionality Reduction
• K clustering hierarchical
• DBScan : Realtime Uses
• KMeans clustering Vs DBSCAN?
• PCA Vs t-SNE

Ch 7: Unsupervised Learning 2

• Unsupervised Learning
• Concepts and Scope
• Realtime Usage
• Dimensionality Reduction
• Component Analysis (PCA)
• PCA: Concept & Usage

Ch 8: Generalized Models

• GLM Concept in Python
• GLM in Regression
• Considerations for GLM
• Problem Solving Skills
• Python Libraries
• Python Extensions: GLM

Ch 9: Python Tree Models

• Decision Tree Models
• Decision Tree Working
• Model Works, Algorithms
• Random Forest Concept
• Random Forest Tree
• Random Forest Vs Knn

Ch 10: Big Data and ML

• Spark and Big Data
• Big Data with Python
• Spark with Python
• Spark with Big Data
• Spark Algorithms
• AI ML Libraries

Ch 11: Natural Lang” Processing

• NLP : Purpose, Usage
• NLP Applicative Uses
• NLP Vs Machine Learning
• NLP in Machine Learning
• Using NLP in AI – ML
• NLP code in Python?

Ch 12: AI in Real-World

• AI in Chatbots
• AI in Virtual Assistants
• AI Ethical Considerations
• AI Deployments (Flask)
• AI with FastAPI
• AI with Streamlit