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Python for Machine Learning Operations

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:

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Python for Machine Learning Operations

This course includes

5 Weeks

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

38,999

Audit For Free

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

Python Programming
MLOps
Data Analysis
Testing
APIs
Command Line Tools
Pandas
NumPy
FastAPI
Flask

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

Alfredo Deza
Alfredo Deza

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.

Python for Machine Learning Operations

This course includes

5 Weeks

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

38,999

Audit For Free

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.