In this course, you will:

• Learn Python basics, including syntax and data types, and how to use Python as a calculator.
• Manipulate and work with lists, which are essential for handling data in Python.
• Write reusable code with functions and manage program flow using if-else statements and loops.
• Start using NumPy, a fundamental library for data science, to handle arrays and perform efficient data operations.

In this course, you will:

• Master Python dictionaries and pandas DataFrames for data manipulation.
• Practice creating and accessing datasets using dictionaries and pandas.
• Explore boolean logic for decision-making in Python.
• Learn control flow, filtering, and loops for efficient data processing.
• Apply Python skills to real-world scenarios.

In this course, you will:

• Learn to write custom functions in Python.
• Understand function parameters, return values, and default arguments.
• Gain insight into scoping and lambda functions.
• Practice error handling in function writing and apply skills to analyse Twitter DataFrames.

In this course, you will:

• Explore iterators and their role in Python.
• Master list comprehensions for efficient data manipulation.
• Apply learned techniques in a case study to solidify understanding.
• Enhance Python data science skills through practical application.

Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualising movie data. Explore Netflix movie data and perform exploratory data analysis for a production company to uncover insights about movies from a particular decade.