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Syllabus

Python for Data Analytics

Everything the module covers, from the first line of Python through pandas and NumPy — the same ground a working analyst uses every day.

6Sections
86Topics
LiveInstructor-led
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What you will cover

Open a section to see every topic inside it.

6 sections 86 topics
01 Python Basics 18 topics
  • Need for Programming
  • Advantages of Programming
  • Overview of Python
  • Organizations using Python
  • Python Applications in Various Domains
  • Python Installation
  • Variables
  • Operands and Expressions
  • Conditional Statements
  • Loops
  • User-Defined Functions
  • Concept of Return Statement
  • Concept of name =" main "
  • Function Parameters
  • Different Types of Arguments
  • Global Variables
  • Global Keyword
  • Command Line Arguments
02 Working with Modules and Handling Exceptions 11 topics
  • Standard Libraries
  • Packages and Import Statements
  • Reload Function
  • Important Modules in Python
  • Sys Module
  • Os Module
  • Math Module
  • Working with Modules and
  • Handling Exceptions
  • Date-Time Module
  • Random Module
03 Functions and Object Oriented Programming 23 topics
  • User-Defined Functions
  • Concept of Return Statement
  • Concept of name =" main "
  • Function Parameters
  • Different Types of Arguments
  • Global Variables
  • Global Keyword
  • Variable Scope and Returning Values
  • Lambda Functions
  • Various Built-In Functions
  • Introduction to Object-Oriented Concepts
  • Built-In Class Attributes
  • Public, Protected and Private Attributes,and Methods
  • Class Variable and Instance Variable
  • Constructor and Destructor
  • Decorator in Python
  • Core Object-Oriented Principles
  • Inheritance and Its Types
  • Method Resolution Order
  • Overloading
  • Overriding
  • Getter and Setter Methods
  • Inheritance-In-Class Case Study
04 Data Manipulation using pandas 11 topics
  • Introduction to pandas
  • Data structures in pandas
  • Series
  • Data Frames
  • Importing and Exporting Files in Python
  • Basic Functionalities of a Data Object
  • Merging of Data Objects
  • Concatenation of Data Objects
  • JSON Module
  • Regular Expression
  • Exception Handling
05 Data Structure and File Operations 7 topics
  • Method of Accepting User Input and eval Function
  • Python - Files Input/Output Functions
  • Lists and Related Operations
  • Tuples and Related Operations
  • Strings and Related Operations
  • Sets and Related Operations
  • Dictionaries and Related Operations
06 Introduction to NumPy 16 topics
  • Basics of Data Analysis
  • NumPy - Arrays
  • Operations on Arrays
  • Indexing Slicing and Iterating
  • NumPy ArrayAttributes
  • Introduction to NumPy
  • Matrix Product
  • NumPy Functions
  • Functions
  • Array Manipulation
  • File Handling Using NumPy
  • Array Creation and Logic Functions
  • File Handling Using Numpy
  • Types of Joins on Data Objects
  • Data Cleaning using pandas
  • Exploring Datasets

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