Ch 1: Python Introduction

• Python Introduction
• Python Versions
• Python Job Roles
• Python for Data Analysts
• Python for Data Engineers
• Python for Data Scientists
• Python for Data Science Engineers

Ch 2: Python Architecture

•  Python Architecture
• PVM: Python Virtual Machine
• Compiler
• Byte Code
• Execution Process
• Resource Allocations
• Python Implementations

Ch 3: Python Installations

• Python Introduction
• Python Installations
• Anaconda Installation
• Python IDE & Usage
• Jupyter Notebooks

Ch 4: Python Print Statement

• Python Print Statement
• print(), print()
• Testing Case Sensitivity
• Single Line print()
• Multi Line print()
• print() with single quotations
• Debug with AI (AI Assistants)

Ch 5: Python Variables

• Python Variables
• Assigning values
• Purpose & Rules
• Variable Value Reads
• Multiple Variables & Print()

Ch 6: Python Operators

• Athematic *& Multiplier Operators
• Python String Literals
• Single, Double Quotes
• Format Strings (f string)
• Comparison, Indexing Operators

Ch 7: Python Data Types

•  Python Data Types
• Integer, Float, String Data Types
• Type Casting
• Type Identification
• Multi Value Assignments
• Python Built-In Classes (data types)

Ch 8: Python Lists

•  Creating Python Lists
• Printing List Items
• Print List Slices
• Length & Type
• list() method
• Empty Lists, Append
• Loops, List Updates

Ch 9: Python Dictionaries

• Python Dictionary
• Creating, Indexing Dictionaries
• Edit / Overwrite Key Values
• Lists inside Dictionaries
• Delete & Clear

Ch 10: Python Tuples

• Python Tuples
• Defining, Indexing
• Length(), Type()
• Mixed Values in Tuples
• Overwriting Tuples
• Tuple Class, (( ))

Ch 11: Python IF..ELSE Condition

• If..Else conditions
• if..elif..else & Shorthand if
• composite conditions
• Indent, pass statement
• in & negation operators
• range conditions

Ch 12: Python Loops (For)

•  Python For Loop
• For Loop @ Range
• For Loop @ Sequence Values
• Nested Loops
• Loop Control Statements
• Break, Continue, Paas

Ch 13: Python Loops (While)

• While Loop
• Termination Checks (Expressions)
• Variables, Logical Conditions
• Loop Conditions, Operators
• Exit Conditions
• iter() and Looping Options

Ch 14: Python Dataframes

• Dataframes: Creation
• Pandas Dataframes
• Dataframes From Single List
• Dataframes from Dictionary
• Display Dataframes, List Items
• Identify, Replace Nulls, NumPy

Ch 15: Python SQL DB Access

• SQL DB Access with Python
• import pandas.DataFrame
• pyodbc module, sql functions
• SQL DB Cursor Connections
• SQL Query Executions: DDL, DML
• Filters, Aggregations with SQL
• Dataframe Usage with SQL

Ch 16: Dataframe Transformations – 1

• Dataframe Transformations
• Concat & Append
• Merge Function
• Join with Multiple Dataframes
• Indexing Operations
• Data Type Checks, Conversions
• Loops with Dataframes

Ch 17: Dataframe Transformations – 2

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

Ch 18: Python Functions & Lambda

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

Ch 19: Python File Handling

• File Handling, Activities
• Loop, Write, Close Files
• Appending, Overwriting
• import os, path.exists
• f.open, f.write
• f.read, f.close

Realtime Case Study (Banking / Finance) For Data Analysis

Ch 19: Python Modules

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

Ch 20: Python User Inputs & TRY

• Try Except, Exception Handling
• Raise an exception method
• TypeError, Scripting in Python
• Python User Inputs
• Python Index Numbers
• input() & raw_input()

Ch 21: 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 22: 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 23: 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

Ch 24: 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 25: Regular Expressions

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

Ch 26: Multi-Threading

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

Ch 27: 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 28: 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

Realtime Project on Banking / Finance

Ch 29: 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 30: Python ML Concepts

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

Ch 31: Python Data Handling

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

Ch 32: 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 33: Supervised Learning

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

Ch 34: 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 35: Unsupervised Learning 2

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

Ch 36: Generalized Models

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

Ch 37: Python Tree Models

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

Ch 38: 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 39: 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 40: AI in Real-World

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

• End to End Project Work
• Python AI
• Python ML
• Realtime Project
• Resume Guidance
• 1:1 mentorship