Master Python programming fundamentals and advanced concepts essential for MLOps, from data manipulation to automation.
Master Python programming fundamentals and advanced concepts essential for MLOps, from data manipulation to automation.
This comprehensive course provides a strong foundation in Python programming specifically tailored for Machine Learning Operations. Students learn core Python concepts, data manipulation with Pandas and NumPy, testing methodologies, and practical MLOps automation. The curriculum progresses from basic programming fundamentals to advanced topics including API integration, command-line tool development, and building machine learning APIs, preparing learners for real-world MLOps challenges.
Instructors:
English
English
What you'll learn
Master Python programming fundamentals and data structures
Develop proficiency in data manipulation using Pandas and NumPy
Implement comprehensive testing strategies with pytest
Build command-line tools for ML automation
Create REST APIs using Flask and FastAPI
Work effectively with various ML-related APIs and SDKs
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 5 modules in this course
This comprehensive Python programming course focuses on essential skills for Machine Learning Operations. Beginning with fundamental Python concepts like data types and functions, students progress through advanced topics including testing, data manipulation with Pandas and NumPy, and MLOps automation. The curriculum emphasizes hands-on experience with practical applications, including building APIs, developing command-line tools, and implementing machine learning workflows. Special attention is given to best practices in testing and automation.
Introduction to Python
Module 1
Python Functions and Classes
Module 2
Testing in Python
Module 3
Introduction to Pandas and NumPy
Module 4
Applied Python for MLOps
Module 5
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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