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Course Detail

Data Analysis and Visualization with Python

2024-01-25

Course Duration
30h
Course OverView

Null

Course Audience

- Economics

- Business

-Finance

- Computer Science  

Course Outline

Module 1: Introduction to Python
• Data types
• String, Numbers
• Basic python operations
Module 1: Conditional Structure
• If-else statement
• If-elif-else statement
• Comparison operators
• Logical values and operations
• Nested-if statement
Module 3: Loop Structure
• For loops
• While loops
• Range
• Nested-for loops
Module 4: Functions
• Write functions of basic operations
• Write functions with/without parameters
• Calling a function
• Scope of variables
• Write a more complex functions to solve problems.
Module 5: Arrays
• Array Basics
• 2D Array
• List, Tuple, Dictionary
Module 6: Python Fundamentals Challenge
• Challenge involving practical revision exercises of the variables, conditional and loop structure, functions, and arrays

Module 1: Introduction to Python
• Data types
• String, Numbers
• Basic python operations
Module 1: Conditional Structure
• If-else statement
• If-elif-else statement
• Comparison operators
• Logical values and operations
• Nested-if statement
Module 3: Loop Structure
• For loops
• While loops
• Range
• Nested-for loops
Module 4: Functions
• Write functions of basic operations
• Write functions with/without parameters
• Calling a function
• Scope of variables
• Write a more complex functions to solve problems.
Module 5: Arrays
• Array Basics
• 2D Array
• List, Tuple, Dictionary
Module 6: Python Fundamentals Challenge
• Challenge involving practical revision exercises of the variables, conditional and loop structure, functions, and arrays

 

Course Completion

After completing this course, students can pursue their work in Python for Data Engineering or Machine Learning algorithms as the next stage of the Data Science journey.

 

Course Prerequisites
  • Python for Data Analysis.
  • Computer Programming.
  • Algorithmic Thinking.
  • Analytical Thinking.
  • Data Mining, Manipulation, Modelling, and Visualization.
  • Best Practices in Programming.
  • Statistical Operations.
  • Data-Driven Decision-Making.
Course Schedule