AI: Python and Pandas for Data Engineering
Master Python essentials and Pandas for data engineering. Learn to set up development environments, manipulate data, and efficiently solve real-world problems.
Hay una sesión disponible:
Python and Pandas for Data Engineering
Sobre este curso
Omitir Sobre este cursoIn this course, you'll gain the Python and Pandas skills essential for data engineering:
- Set up version-controlled Python environments with necessary libraries
- Write Python programs using key language features and data structures
- Manipulate and analyze data using the powerful Pandas library
- Explore alternative data structures like NumPy arrays and PySpark DataFrames
- Utilize Vim, Visual Studio Code, and Git for productive development
Whether you're a beginner or have some programming experience, you'll learn to harness Python and Pandas to tackle data engineering challenges. Hands-on exercises reinforce your learning each step of the way.
De un vistazo
- Institution
AI
- Subject Informática
- Level Introductory
- Prerequisites Ninguno
- Language English
- Video Transcript English
- Associated programs
- Professional Certificate en Data Engineering Foundations
Lo que aprenderás
Omitir Lo que aprenderás- Python environment setup and package management
- Core Python syntax and data structures
- Pandas DataFrames for data manipulation
- Alternatives to Pandas for big data
- Development with Vim, VS Code, and Git
Plan de estudios
Omitir Plan de estudiosModule 1: Getting Started with Python (14 hours)
\- Overview of Python, Bash and SQL Essentials for Data Engineering (video, 7 minutes)
\- Meet your Course Instructor: Kennedy Behrman (video, 0 minutes)
\- Overview of Key Concepts (video, 5 minutes)
\- Introduction to Setting Up Your Python Environment (video, 0 minutes)
\- Installing Packages with pip in Python (video, 6 minutes)
\- Saving Requirements File in Python (video, 3 minutes)
\- Creating and Using a Python Virtual Environment (video, 5 minutes)
\- Expression Statements in Python (video, 3 minutes)
\- Assignment Statements in Python (video, 5 minutes)
\- Import Statements in Python (video, 4 minutes)
\- Other Simple Statements in Python (video, 5 minutes)
\- Compound Statements in Python (video, 5 minutes)
\- If Statements in Python (video, 6 minutes)
\- While Loops in Python (video, 4 minutes)
\- Functions in Python (video, 7 minutes)
\- Key Terms (reading, 10 minutes)
\- Key Terms (reading, 10 minutes)
\- Meet your Supporting Instructors: Alfredo Deza and Noah Gift (reading, 10 minutes)
\- Course Structure and Discussion Etiquette (reading, 10 minutes)
\- Getting Started and Best Practices (reading, 10 minutes)
\- Key Terms (reading, 10 minutes)
\- Lesson Reflection (reading, 10 minutes)
\- Key Terms (reading, 10 minutes)
\- Lesson Reflection (reading, 10 minutes)
\- Key Terms (reading, 10 minutes)
\- Evaluating to True or False (reading, 10 minutes)
\- Lesson Reflection (reading, 10 minutes)
\- Python Statements (quiz, 30 minutes)
\- Assignment Statements (quiz, 30 minutes)
\- Import Statements (quiz, 30 minutes)
\- If Statements (quiz, 30 minutes)
\- While Loops (quiz, 30 minutes)
\- Quiz-Setting Up Your Python Environment (assignment, 180 minutes)
\- Meet and Greet (optional) (discussion prompt, 10 minutes)
\- Install a Package with the pip Command (ungraded lab, 60 minutes)
\- Export a Requirements File (ungraded lab, 60 minutes)
\- Create a Virtual Environment (ungraded lab, 60 minutes)
\- Practicing with Expression Statements (ungraded lab, 60 minutes)
\- Decorator Functions (ungraded lab, 60 minutes)
\- Setting up a Python Environment (ungraded lab, 60 minutes)
****
Module 2: Essential Python (11 hours)
- Introduction to Python Essentials (video, 0 minutes)
- Sequences in Python (video, 8 minutes)
- Lists and Tuples in Python (video, 5 minutes)
- Strings in Python (video, 10 minutes)
- Creating Range Objects in Python (video, 2 minutes)
- Creating Dictionaries in Python (video, 4 minutes)
- Accessing Dictionary Data in Python (video, 3 minutes)
- Dictionary Views in Python (video, 2 minutes)
- Sets and Set Operations in Python (video, 6 minutes)
- List Comprehensions in Python (video, 6 minutes)
- Generator Expressions in Python (video, 4 minutes)
- Generator Functions in Python (video, 7 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Essential Python Concepts (quiz, 30 minutes)
- Sequence Operations (quiz, 30 minutes)
- Lists and Tuples (quiz, 30 minutes)
- Range Objects (quiz, 30 minutes)
- Accessing Data in Dictionaries (quiz, 30 minutes)
- Sets and Set Operations (quiz, 30 minutes)
- List Comprehensions (quiz, 30 minutes)
- Generator Expressions (quiz, 30 minutes)
- Practicing with Strings in Python (ungraded lab, 60 minutes)
- Creating Dictionaries in Python (ungraded lab, 60 minutes)
- Dictionary Views in Python (ungraded lab, 60 minutes)
- Comprehensions and Generators in Python (ungraded lab, 60 minutes)
- Practicing Essential Python (ungraded lab, 60 minutes)
****
Module 3: Data in Python: Pandas and Alternatives (12 hours)
- Introduction to Data in Python: Pandas and Alternatives (video, 0 minutes)
- Creating Pandas DataFrames in Python (video, 4 minutes)
- Investigating Data in a Pandas DataFrame (video, 6 minutes)
- Selecting Data in a Pandas DataFrame (video, 6 minutes)
- Manipulating Pandas DataFrames (video, 4 minutes)
- Updating Pandas DataFrame Data (video, 5 minutes)
- Applying Functions in a Pandas DataFrame (video, 6 minutes)
- Creating NumPy Arrays in Python (video, 15 minutes)
- Spark and PySpark DataFrames in Python (video, 6 minutes)
- Creating Dask DataFrames in Python (video, 6 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Polars (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Pandas and Alternatives (quiz, 30 minutes)
- NumPy (quiz, 30 minutes)
- PySpark (quiz, 30 minutes)
- Dask (quiz, 30 minutes)
- Creating DataFrames (ungraded lab, 60 minutes)
- Looking at Data in DataFrames (ungraded lab, 60 minutes)
- Selecting Data in a Pandas DataFrame (ungraded lab, 60 minutes)
- Manipulating DataFrames (ungraded lab, 60 minutes)
- Updating Data in a DataFrame (ungraded lab, 60 minutes)
- Applying Functions in a Pandas DataFrame (ungraded lab, 60 minutes)
- Manipulate DataFrames with Polars to gain insights (ungraded lab, 60 minutes)
- Pandas and Alternatives (ungraded lab, 60 minutes)
****
Module 4: Python Development Environments (13 hours)
- Introduction to Python Development Environments (video, 0 minutes)
- Introduction to Vim Normal Mode (video, 6 minutes)
- Switching from Normal to Insert and Visual Modes in Vim (video, 4 minutes)
- Working with the Vim Command Line (video, 6 minutes)
- Vim Configuration (video, 3 minutes)
- Introduction to Visual Studio Code (video, 1 minute)
- Setting Up Visual Studio Code (video, 2 minutes)
- Debugging Visual Studio Code (video, 3 minutes)
- What is Version Control? (video, 3 minutes)
- Introduction to Git and Git Concepts (video, 7 minutes)
- Version Control with GitHub (video, 6 minutes)
- Summary of Python and Pandas for Data Engineering (video, 0 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Key Terms (reading, 10 minutes)
- Lesson Reflection (reading, 10 minutes)
- Next Steps (reading, 10 minutes)
- Cumulative Python and Pandas for Data Engineering Quiz (quiz, 45 minutes)
- Insert and Visual Modes (quiz, 30 minutes)
- Vim Command Line Mode (quiz, 30 minutes)
- Features of Visual Studio Code (quiz, 30 minutes)
- Version Control (quiz, 30 minutes)
- Git Commands (quiz, 30 minutes)
- Hosted Git (quiz, 30 minutes)
- Basic Vim Commands (ungraded lab, 60 minutes)
- Explore Visual Studio Code (ungraded lab, 60 minutes)
- Visual Studio Code Debugger (ungraded lab, 60 minutes)
- Setup and Provision a Python Project (ungraded lab, 60 minutes)
- Pandas Final Challenge: Life Expectancy and Happiness (ungraded lab, 60 minutes)
- Final Jupyter Sandbox (ungraded lab, 60 minutes)
- Final VS Code Sandbox (ungraded lab, 60 minutes)
- Final Sandbox Linux Desktop (ungraded lab, 60 minutes)
Este curso es parte del programa Data Engineering Foundations Professional Certificate
Más informaciónVerified Track | Audit Track | |
|---|---|---|
Costo | 449 US$ | Free |
Acceso a los materiales del curso | Ilimitado | Limitado Caduca el 1 nov |
World class institutions and universities | ||
Asistencia de edX | ||
Certificado para compartir al finalizar | ||
Tareas con calificación y exámenes |