Python and Pandas for Data Engineering
Master Python essentials and Pandas library for data engineering with hands-on practice in setup, manipulation, and analysis using modern tools.
Master Python essentials and Pandas library for data engineering with hands-on practice in setup, manipulation, and analysis using modern tools.
This comprehensive course teaches the fundamentals of Python and Pandas for data engineering applications. Students learn to set up version-controlled Python environments, write effective programs using key language features, and manipulate data using Pandas. The curriculum covers essential concepts including package management, data structures, DataFrame operations, and alternatives like NumPy arrays and PySpark. Through hands-on exercises, participants gain practical experience with modern development tools like Vim, Visual Studio Code, and Git. The course provides a solid foundation for both beginners and those with some programming experience.
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What you'll learn
Set up and manage Python development environments with version control
Master core Python syntax and essential data structures
Manipulate and analyze data using Pandas DataFrames
Work with alternative data structures like NumPy arrays and PySpark
Develop efficiently using Vim, Visual Studio Code, and Git
Skills you'll gain
This course includes:
PreRecorded video
Quizzes, Labs, Final Challenge
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
The course provides comprehensive training in Python programming and data manipulation using Pandas. Students learn environment setup, core Python syntax, data structures, and DataFrame operations. The curriculum includes hands-on practice with development tools like Vim and Git, preparing learners for real-world data engineering tasks.
Getting Started with Python
Module 1
Essential Python
Module 2
Data in Python: Pandas and Alternatives
Module 3
Python Development Environments
Module 4
Fee Structure
Instructors
30 Courses
Pioneering Tech Leader & AI Educator Shaping the Future of Machine Learning
Noah Gift is a distinguished technology leader and founder of Pragmatic AI Labs with a remarkable 30-year career spanning film, TV, telecom, social networks, startups, and big data, currently serving as an Executive-in-Residence at Duke University. As an AWS ML Hero and Python Software Foundation Fellow, he has authored best-selling books through O'Reilly and Pearson on DevOps, MLOps, data engineering, and cloud computing that are widely adopted by major universities. His expertise in MLOps, data engineering, cloud architecture, and Rust programming has led him to teach thousands of students across prestigious institutions including Duke, Northwestern, UC Berkeley, University of San Francisco, and UC Davis, while also collaborating with Caltech and JPL on automated IT systems. Gift's impact extends beyond academia through his work as a startup CTO, his role in developing scalable distributed systems, and his contributions as a keynote speaker at conferences focused on cloud development and ethical AI use, holding certifications from AWS, Google, and Microsoft, and having published over 100 technical works while conducting workshops for organizations like NASA, PayPal, and PyCon.
4 Courses
A Pioneering Data Engineer and AI Education Leader
Kennedy Behrman is a distinguished data engineering expert and educator who currently serves as a Senior Data Engineer at Envestnet, Inc. His extensive career spans data engineering, cloud solutions, and machine learning, backed by both undergraduate and graduate degrees from the University of Pennsylvania. As an accomplished author, he has written several influential books including "Foundational Python for Data Science" and co-authored "Python for DevOps" with O'Reilly Media. His educational impact extends through his role as an instructor for multiple prestigious courses, including the "Applied Python Data Engineering Specialization" and "Python, Bash and SQL Essentials for Data Engineering Specialization" which have reached over 21,000 students combined. Previously, he founded Pragmatic AI Labs, providing pragmatic cloud solutions for AI requirements, and held leadership positions including CTO and VP Engineering at Sqor Sports where he led engineering, product, and design teams. His technical expertise encompasses Python, data engineering, AWS solutions, and machine learning, with particular focus on developing scalable data pipelines and implementing cloud-based solutions. Behrman's influence in the field is further demonstrated through his contributions to various platforms, including the development of AWS machine learning certification tests and his role in creating comprehensive educational content for data science and engineering professionals.
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