Self-Paced Course
Python Foundations for Data Analysis
Master the core building blocks of Python for data analysis, including data types, variables, conditional logic, loops, functions and more.
Course Description
This is a hands-on, project-based course designed to help you master the core building blocks of Python for data analysis.
We'll start by introducing the Python language and ecosystem, installing Jupyter Notebooks where we'll write our first lines of code, and reviewing some key Python data types and properties.
From there we'll dive into foundational tools like variables, numeric and string operators, conditional logic, loops, functions and more. You'll learn how to create and manipulate raw data, define conditional logic, loop through iterables or indices, and extract values stored in a wide variety of data types including dictionaries, lists, tuples, and more.
Throughout the course you'll play the role of a Data Analytics Intern for Maven Ski Shop, the world's #1 store for skis, snowboards and winter gear. Using the skills you learn throughout the course, you'll help the Maven team track inventory, pricing, and sales performance using Python.
Last but not least, we'll practice importing and manipulating data from an Excel workbook using the openpyxl package, and bring it all together with a final course project.
If you're a data analyst or business intelligence professional looking to add Python to your skill set, this is the course for you.
COURSE CONTENTS:
11.5 hours on-demand video (19.0 CPE credits)
40 homework assignments (plus 1 final project)
10 quizzes
2 skills assessments (1 benchmark, 1 final)
COURSE CURRICULUM:
- Welcome to the Course!
- Benchmark Assessment
- Course Structure & Outline
- DOWNLOAD: Course Resources
- Introducing the Course Project
- Setting Expectations
- What is Python?
- Python for Data Analysis
- The Python Analytics Ecosystem
- Data Roles that Use Python
- Jupyter Notebooks Intro & Install
- Launching Jupyter & Creating a Notebook
- The Jupyter Interface
- The Code Cell
- Comments & Markdown
- The Print Function & Function Help
- ALTERNATIVE: Google Colab
- Helpful Resources & Key Takeaways
- QUIZ: Jupyter Notebooks
- Python Data Types
- The Type Function & Type Conversion
- DEMO: Type Function & Conversion
- Iterables & Mutability
- QUIZ: Python Data Types
- Intro to Variables
- DEMO: Variable Assignment
- ASSIGNMENT: Variable Assignment
- SOLUTION: Variable Assignment
- Overwriting Variables
- Deleting Variables
- DEMO: Overwriting & Deleting Variables
- Variable Naming Rules
- Keeping Track of Variables
- DEMO: Naming & Tracking Variables
- ASSIGNMENT: Variable Naming Rules
- SOLUTION: Variable Naming Rules
- Key Takeaways
- QUIZ: Variables
- Intro to Numeric Data
- Numeric Data Types
- Numeric Type Conversion
- Arithmetic Operators & Order of Operations
- DEMO: Numeric Data
- ASSIGNMENT: Arithemetic Operators
- SOLUTION: Arithmetic Operators
- Numeric Functions
- DEMO: Numeric Functions
- ASSIGNMENT: Numeric Functions
- SOLUTION: Numeric Functions
- Key Takeaways
- QUIZ: Numeric Data
- Intro to Strings
- String Arithmetic
- DEMO: String Creation & Arithmetic
- String Indexing
- DEMO: String Indexing
- ASSIGNMENT: String Indexing
- SOLUTION: String Indexing
- String Slicing
- DEMO: String Slicing
- ASSIGNMENT: String Slicing
- SOLUTION: String Slicing
- The Length Function
- ASSIGNMENT: The Length Function
- SOLUTION: The Length Function
- String Methods
- DEMO: String Methods
- ASSIGNMENT: String Methods
- SOLUTION: String Methods
- F-Strings
- DEMO: F-Strings
- ASSIGNMENT: F-Strings
- SOLUTION: F-Strings
- Key Takeaways
- QUIZ: Strings
- The Boolean Data Type
- Comparison Operators & Membership Tests
- Boolean Operators
- DEMO: Boolean Data Types & Operators
- ASSIGNMENT: Boolean Operators
- SOLUTION: Boolean Operators
- The IF Statement & Control Flow
- Else & Elif Statements
- DEMO: If, Else, Elif
- ASSIGNMENT: Control Flow
- SOLUTION: Control Flow
- Nested If Statements
- ASSIGNMENT: Nested If Statements
- SOLUTION: Nested If Statements
- Key Takeaways
- QUIZ: Conditional Logic
- Sequence & List Basics
- List Operations
- DEMO: List Operations
- ASSIGNMENT: List Operations
- SOLUTION: List Operations
- Modifying Lists
- DEMO: Modifying Lists
- ASSIGNMENT: Adding List Elements
- SOLUTION: Adding List Elements
- ASSIGNMENT: Removing List Elements
- SOLUTION: Removing List Elements
- List Methods & Functions
- DEMO: List Methods & Functions
- ASSIGNMENT: List Methods & Functions
- SOLUTION: List Methods & Functions
- Nesting & Copying Lists
- DEMO: Nested Lists & Copying Lists
- ASSIGNMENT: Nested Lists & Copying Lists
- SOLUTION: Nested Lists & Copying Lists
- Tuples
- DEMO: Tuples
- ASSIGNMENT: Tuples
- SOLUTION: Tuples
- Ranges
- DEMO: Ranges
- ASSIGNMENT: Ranges
- SOLUTION: Ranges
- Key Takeaways
- QUIZ: Sequence Data Types
- Loop Basics
- For Loops & Looping Over Items
- DEMO: For Loops
- Looping Over Indices & Multiple Iterables
- DEMO: Looping Over Indices
- PRO TIP: Enumerate
- DEMO: Enumerate
- ASSIGNMENT: For Loops
- SOLUTION: For Loops
- ASSIGNMENT: Enumerate
- SOLUTION: Enumerate
- While Loops
- DEMO: While Loops
- ASSIGNMENT: While Loops
- SOLUTION: While Loops
- Nested Loops
- DEMO: Nested Loops
- ASSIGNMENT: Nested Loops
- SOLUTION: Nested Loops
- Loop Control
- Break, Continue & Pass
- Try-Except
- DEMO: Loop Control
- ASSIGNMENT: Loop Control
- SOLUTION: Loop Control
- Key Takeaways
- QUIZ: Loops
- Intro to Dictionaries
- Dictionary Overview
- Accessing & Modifying Dictionary Values
- DEMO: Dictionary Operations
- ASSIGNMENT: Dictionary Basics
- SOLUTION: Dictionary Basics
- ASSIGNMENT: Dictionary Creation
- SOLUTION: Dictionary Creation
- Keys & Values Methods
- Get, Items & Update Methods
- DEMO: Dictionary Methods
- ASSIGNMENT: Dictionary Methods
- SOLUTION: Dictionary Methods
- The Zip Function
- ASSIGNMENT: The Zip Function
- SOLUTION: The Zip Function
- Nested Dictionaries
- DEMO: Nested Dictionaries
- ASSIGNMENT: Nested Dictionaries
- SOLUTION: Nested Dictionaries
- Intro to Sets
- DEMO: Sets
- ASSIGNMENT: Sets
- SOLUTION:Sets
- Set Operations
- Set Use Cases
- DEMO: Set Operations
- ASSIGNMENT: Set Operations
- SOLUTION: Set Operations
- Key Takeaways
- QUIZ: Dictionaries & Sets
- Intro to Functions
- Anatomy of a Function
- Defining Functions
- The Docstring
- DEMO: Defining a Function
- ASSIGNMENT: Defining a Function
- SOLUTION: Defining a Function
- Argument Types
- DEMO: Argument Types
- Return Values
- DEMO: Return Values
- Variable Scope
- DEMO: Variable Scope
- Creating Modules
- Importing Modules
- DEMO: Creating & Importing Modules
- ASSIGNMENT: Creating a Module
- SOLUTION: Creating A Module
- ASSIGNMENT: Importing a Function
- SOLUTION: Importing a Function
- Importing External Functions
- PRO TIP: Naming Conflicts
- Installing & Managing Packages
- DEMO: Installing Packages
- The Map Function
- ASSIGNMENT: The Map Function
- SOLUTION: The Map Function
- Lambda Functions
- DEMO: Lambda Functions
- ASSIGNMENT: Lambda Functions
- SOLUTION: Lambda Functions
- PRO TIP: Comprehensions
- DEMO: List Comprehensions
- ASSIGNMENT: List Comprehensions
- SOLUTION: List Comprehensions
- PRO TIP: Dictionary Comprehensions
- DEMO: Dictionary Comprehensions
- ASSIGNMENT: Dictionary Comprehensions
- SOLUTION: Dictionary Comprehensions
- PRO TIP: Comprehensions vs. Map()
- Key Takeaways
- QUIZ: Functions
- The Openpyxl Package
- Navigating Excel Workbooks, Worksheets & Cells
- DEMO: Navigating Excel Workbooks With Python
- ASSIGNMENT: Missing Sales Tax
- SOLUTION: Missing Sales Tax
- Determining Ranges & Writing to Cells
- DEMO: Writing To Excel From Python
- ASSIGNMENT: Pound & Yen Columns
- SOLUTION: Pound & Yen Columns
- Inserting & Deleting Columns
- Saving Workbooks
- Bringing it All Together
- Key Takeaways
- QUIZ: Manipulating Excel Sheets
- Welcome to the Final Project!
- SOLUTION: Final Project (Part 1)
- SOLUTION: Final Project (Part 2)
- Final Assessment
- Course Feedback Survey
- Share the love!
- Next Steps
WHO SHOULD TAKE THIS COURSE?
- Analysts or BI professionals looking for a deep introduction to basic Python
- Aspiring data scientists who want to build foundational Python skills
- Anyone interested in learning one of the most popular open source programming languages in the world
WHAT ARE THE COURSE REQUIREMENTS?
- Jupyter Notebooks (free download, we'll walk through the install)
- No advance preparation is required (basic familiarity with programming is a plus, but not a prerequisite)
WHAT ARE THE COURSE OBJECTIVES?
Identify Jupyter Notebook tools and best practices, including the notebook server, menu options, edit & command modes, comments, and markdown
Identify Python's data types and their properties, including type conversion, mutability, and iterability
Identify examples of variable assignment in Python, including naming, tracking, overwriting, and deleting variables
Identify and interpret base Python syntax for working with numeric data using arithmetic operators, order of operations, and numeric functions
Identify and interpret base Python syntax for manipulating text data via string arithmetic, indexing & slicing, string methods, and f-strings
Identify and interpret control flow using Boolean operators and conditional statements, including if, else, and elif
Identify and interpret examples of looping through iterable data types using for & while loops, including the enumerate function, nested loops, and control statements
Identify and interpret base Python syntax for creating, modifying, and nesting sequence & map data types, including lists, tuples, ranges, dictionaries, and sets
Identify the proper syntax for defining custom Python functions, including variable scope, external modules & packages, lambda functions, and comprehensions
Identify basic openpyxl functions and use cases for manipulating Excel sheets using Python, including reading & writing data, navigating workbooks, and looping through cells
CPE ACCREDITATION DETAILS:
CPE Credits: 19.0
Field of Study: Information Technology
Delivery Method: QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: April 14, 2022
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