Data Science with Python Course Syllabus

Introduction of Python

• Why do we need Python?
• Program structure

Execution Steps

• Interactive Shell
• Executable or script files
• User Interface or IDE

Data types in Python

• Memory management and Garbage collections
• Object creation and deletion
• Object properties

Data Types and Operations

• Numbers
• Strings
• List
• Tuple
• Dictionary
• Other Core Types

Loops and expression in Python

• Assignments, Expressions and prints
• Statements and Syntax
• If tests and Syntax Rules
• While and For Loops
• Iterations and Comprehensions

User defined function in Python

• Functions
• Function definition and call
• Function Scope
• Arguments
• Function Objects
• Anonymous Functions

Exception handling in Python

• Exception Handling
• Default Exception Handler
• Catching Exceptions
• Raise an exception
• User defined exception

Data Science Data Science and AI

• All the topics in data science will covered with following concept:
• All the topics in data science will covered with following concept:
• Mathematics beside of each model
• Which scenario we want to use a particular algorithm
• How to apply it in tool
• An inferential thing of each model

Difference between each model

• Introduction to Machine Learning & Predictive Modelling
• Major Classes of Learning Algorithms -Supervised vs Unsupervised Learning

Statistics

• Standard Deviation
• Variance
• Concept of hypothesis testing
• T-test
• Chi-square
• Anova
• Correlation
• Probability
• Outliers
• Drop highly correlated features