Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We will work with you to tune this course and level of coverage to target the skills you need most. Course agenda, topics and labs are subject to adjust during live delivery in response to student skill level, interests and participation.
Getting Started with the Python Environment
- Starting Python
- Using the interpreter
- Running a Python script
- Editors and IDEs
Variables and Values
- Using variables
- Builtin functions
- String data
- Numeric data
- Converting types
Basic input and output
- Writing to the screen
- String formatting
- Command line arguments
- Reading the keyboard
Flow Control
- About flow control
- The if statement
- Relational and Boolean values
- while loops
- Exiting from loops
Array types
- Sequence types in general
- Lists and list methods
- Tuples
- Indexing and slicing
- Iterating through a sequence
- Sequence functions, keywords, and operators
- List comprehensions and generators
Working with files
- File I/O overview
- Opening a text file
- Reading a text file
- Writing to a text file
Dictionaries and Sets
- About dictionaries
- Creating dictionaries
- Getting values
- Iterating through a dictionary
- About sets
- Creating sets
- Working with sets
Functions, modules, and packages
- Returning values
- Types of function parameters
- Variable scoping
- Documentation best practices
- Creating and importing modules
- Organizing modules into packages
Virtual Environments
- Why do we need virtual environments
- Creating an environment
- Activating and deactivating
- Replicating an environment
- Tools for environments
Exception handling and logging
- About exceptions
- Using try/catch/else/finally
- Handling multiple exceptions
- Logging setup
- Basic logging
Introduction to Python Classes
- Defining classes
- Constructors
- Instance methods and data
- Attributes
- Inheritance
- Multiple inheritance
Excel spreadsheets
- The openpyxl module
- Reading an existing spreadsheet
- Creating a spreadsheet from scratch
- Modifying an existing spreadsheet
Serializing Data
- Using ElementTree
- Creating a new XML document
- Parsing XML
- Finding by tags and XPath
- Parsing JSON into Python
- Parsing Python into JSON
- Working with CSV
iPython and Jupyterlab
- iPython features & iPython "magic" commands
- iPython configuration
- Creating Jupyter notebooks
- Managing notebooks with Jupyterlab
Intro to NumPy
- NumPy basics
- Creating arrays
- Indexing and slicing
- Large number sets
- Transforming data
- SciPy overview
Intro to Pandas
- Pandas overview
- Series and Dataframes
- Reading and writing data
- Data summaries
- Data alignment and reshaping
- Selecting and indexing
- Merging and joining data sets
- Plotting data
Matplotlib
- Creating a basic plot
- Commonly used plots
- Ad hoc data visualization
- Advanced usage
- Exporting images
Optional Topics or Day Five:
For Dedicated / Private Classes:
Introduction to AI with Python for Data Analysis
- Overview of AI Libraries
- Setting Up Your Environment:
- Understanding AI Models
- Creating Your First Model
- Evaluating Model Performance
Practical AI Projects in Python
- Set up a Python project for AI applications.
- Data Handling
- Model Development
- Test and validate your AI model's effectiveness.
- Applying Your Model
Using GPT Tools for Record Analysis in Data Science
- Introduction to GPT
- Setting Up GPT Tools
- Analyzing Text Data
- Generating Insights
- Practical Applications
