Learn essential data engineering skills using Python and SQL to manipulate, analyze, and automate data processing tasks in this comprehensive course.
Learn essential data engineering skills using Python and SQL to manipulate, analyze, and automate data processing tasks in this comprehensive course.
Master data manipulation techniques using Python and SQL in this comprehensive data engineering course. You'll learn to leverage Python's powerful data structures, create automated scripts for data processing, and work with both SQLite and MySQL databases. The course covers essential web scraping techniques, database management, and practical applications in VSCode. Through hands-on projects and real-world scenarios, you'll develop the skills to efficiently extract, transform, and load data while building a strong foundation in modern data engineering practices.
4.5
Instructors:
English
English
What you'll learn
Develop proficiency in manipulating data using Python's built-in data structures
Create automated Python scripts for efficient data processing tasks
Master SQLite database operations including creation, connection, and querying
Implement web scraping techniques to extract and store data from websites
Gain practical experience with MySQL database operations in VSCode
Learn to import and export data across different database systems
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 4 modules in this course
In this comprehensive course, students will master essential data engineering skills using Python and SQL. The curriculum covers fundamental data structures in Python, creating automated scripts for data processing, and working with various database systems including SQLite and MySQL. Students will learn web scraping techniques to extract data from websites and understand how to persist this data in different formats. The course emphasizes practical skills through hands-on exercises in VSCode, teaching students to execute queries, manage databases, and implement efficient data processing workflows. Special attention is given to real-world applications and best practices in data engineering.
Working with Data in Python
Module 1
Python Scripting and SQL
Module 2
Web Scraping using Python
Module 3
Working with MySQL
Module 4
Fee Structure
Instructor

20 Courses
A Technology Educator and Former Olympic Athlete Pioneering AI Innovation
Alfredo Deza embodies a unique combination of athletic excellence and technological expertise, transitioning from a distinguished career as Peru's first World Junior Champion in high jump and 2004 Olympian to becoming a leading voice in technology education and development. Currently serving as a Principal Cloud Advocate at Microsoft and Adjunct Assistant Professor at Duke University's Pratt School of Engineering, Deza has built an impressive career spanning nearly two decades in software engineering and education. His academic contributions extend through guest lectures at prestigious institutions including Oxford University, Georgia Tech, and Carnegie Mellon University, where he shares expertise in machine learning, cloud computing, and programming languages. As an accomplished author, he has co-authored several influential books with O'Reilly Media, including "Practical MLOps" and "Python for DevOps," while developing comprehensive courses on Coursera covering topics from large language models to Rust programming. His teaching portfolio at Duke includes graduate-level courses in machine learning operations and Python programming, reflecting his commitment to making complex technical concepts accessible. Deza's expertise encompasses a broad spectrum of technologies, including Azure, MLOps, DevOps, Python, Rust, and Databricks, which he leverages to bridge the gap between academic theory and industry practice. His unique perspective, shaped by his background as an Olympic athlete, influences his approach to teaching and technology, emphasizing the importance of continuous learning and knowledge sharing in the rapidly evolving field of artificial intelligence and cloud computing.
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