Module 1: Basic Programming

• Using Jupyter as a development IDE
• Introduction to Python programming
• Understanding Python syntax and constructs

Module 2: Data Frames & Datasets

• Inspecting data frames with head() and tail()
• Exploring data types and information using info()

Module 3: Data Frame Methods and Computations

• Calculating Min, Max, Sum, and Count
• Understanding Mean, Median, & Mode
• Describing data with numeric and object values

Module 4: Series and Columns

• Selecting a single column and exploring series
• Important series methods: unique(), nunique(), nlargest(), nsmallest()
• Using value_counts() and visualizing with plot()
• Adding and removing columns

Module 5: Organizing Data and Working With Dates/Times

• Indexing and creating a MultiIndex
• Sorting and filtering DataFrames
• Using condition operators (AND/OR)
• Working with dates and performing date math

Module 6: Python for Data Analysis with NumPy

• Introduction to NumPy and its applications in data analysis
• Working with NumPy arrays and indexing
• Performing operations with NumPy