Python Data Engineering Project
Master data engineering fundamentals with hands-on practice in Python, covering API data collection, web scraping, and ETL processes using Jupyter Notebooks.
Master data engineering fundamentals with hands-on practice in Python, covering API data collection, web scraping, and ETL processes using Jupyter Notebooks.
This practical course focuses on essential data engineering skills using Python. Students will learn to collect data through APIs and web scraping techniques, handle various file formats, and transform data for analysis. The course emphasizes hands-on experience with real-world data engineering tasks, including logging operations for transparency and reproducibility. Participants will work with Jupyter Notebooks in Watson Studio, engaging in collaborative learning through peer reviews. The project-based approach ensures students gain practical experience in handling data engineering challenges while developing skills in ETL processes, data transformation, and collaborative development.
4.8
(9 ratings)
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What you'll learn
Collect and extract data using APIs and web scraping techniques
Transform data into appropriate formats for analysis
Implement ETL processes using Python and Jupyter Notebooks
Log data operations effectively for transparency
Collaborate and share work through Watson Studio
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 2 modules in this course
This comprehensive data engineering project course focuses on practical implementation of ETL processes using Python. Students learn essential skills in data collection through APIs and web scraping, data transformation techniques, and proper logging procedures. The curriculum emphasizes hands-on experience with Jupyter Notebooks in Watson Studio, teaching students to handle real-world data engineering tasks efficiently. Through collaborative learning and peer reviews, participants develop both technical expertise and teamwork skills.
Extract, Transform, Load (ETL)
Module 1
Final Project
Module 2
Fee Structure
Instructors
Data Engineering and Technology Education Expert
Ramesh Sannareddy serves as a freelance technology educator and content developer, bringing over two and a half decades of experience in Information Technology Infrastructure Management, Database Administration, and Information Integration. After earning his Bachelor's Degree in Information Systems from Birla Institute of Technology, Pilani, he built an impressive career working with leading technology companies including Intergraph, Genpact, HCL, and Microsoft. Currently focused on his passion for teaching, he specializes in developing and delivering courses in Data Science, Machine Learning, Programming, and Databases. His educational impact is evidenced through his extensive course portfolio, which includes specialized programs in Data Engineering, Data Warehousing, Linux Commands, Machine Learning with Apache Spark, and Python Programming. His teaching reaches over 11,800 learners globally, maintaining a strong 4.5 rating for his educational content
Pioneering Data Scientist Bridging AI Research and Education
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
Testimonials
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4.8 course rating
9 ratings
Frequently asked questions
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