Module 1: User Defined functions and Built-in Class function in Python
✓ Difference between Built-in and User defined functions in Python.
✓ How to create user defined functions using def.
✓ Introducing Lambda functions.
✓ Set, frozen set class and object and its functions

Module 2: Python Builtin Classes and Objects
✓ Int, Float and Complex Class and Object in Python.
✓ What are operators and how to use the in-number objects. Str class and Objects in Python.
✓ Different data Structures, data processing Techniques to learn.

Module 3: Understand Text File Handling with Python
✓ Handle different format types of files in Python. How to read, write and append data using Python
✓ File pointer and seek the pointer introduction to Python –
✓ Built-in Modules

Module 4: Python Libraries/Modules and Packages
✓ Discussion on Python Modules. User Defined Modules, Python inbuilt Modules/libraries and 3rd Party
✓ Modules
✓ Python inbuilt libraries – os, sys, logging, datetime, time, zip, json, csv
✓ Create your own Python Modules
✓ Configuration of Python UDM and Define PYTHONPATH Create your own Python Packages

Module 5: Python Exceptional Handling Features
✓ How to handle Python run time exceptions Zero Division Exception, Name Error, Type Error and Generic Exception Class
✓ Raising an exceptions User-Defined Exceptions

Module 6: Introduction of Regular Expression
✓ Match, compile, search and findall Function Matching vs searching operations
✓ Search and Replace feature using RE Extended Regular Expressions
✓ Wildcard characters and work with them

Module 7: Python – Database Interaction
✓ Introduction of Python Library sqlite3 Creating Databases and Tables CRUD Operations
✓ Creating a Database Object

Module 8: Introduction to pip and package installation
✓ Introduction to pip and package installation. What is pip?
✓ Install, download, uninstall, upgrade and search packages using pip. Install package using pip and Pycharm
✓ Install packages for XLS interface and XLS parsing with Python Create XLS reports with Python

Module 9: Introduction to Anaconda Distribution
✓ Set Virtual environment using conda Integrating Anaconda with Pycharm.

Module 10: Introduction to numpy and statistical analysis
✓ Introduction to numpy functions Dealing with Flat files using numpy Mathematical functions
✓ Statistical function Operations with arrays

Module 11: Introduction to panda’s framework and statistical analysis
✓ What is Python – Pandas framework. Creating Series and data filter/transformation Creating Data Frames on pandas
✓ Practical use cases using data analysis mini projects

Module 12: Introduction to Python Matplotlib Library
✓ What is matplotlib and its gallery.
✓ Create different graph from dataset
✓ Practical use cases using data analysis Mini Projects

Module 13: Machine Learning Regression
✓ Logistic Regression
✓ Random Forest

Module 14: Classification
✓ K-means Hierarchical