Python for MLOPS
Python for MLOPS
Published 7/2025
Duration: 4h 40m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.11 GB
Genre: eLearning | Language: English
Published 7/2025
Duration: 4h 40m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.11 GB
Genre: eLearning | Language: English
Learn Python step by step with hands-on project, data analysis, and scripting for MLOps tasks
What you'll learn
- Understand Python fundamentals including variables, data types, conditionals, and loops
- Work with data structures like lists, dictionaries, sets, and functions in Python
- Use Pandas and NumPy to load, clean, and analyze real-world datasets
- Build Python scripts and simple CLI tools for data tasks in MLOps workflows
Requirements
- There are no special skills or experience required to take this course. It is designed for complete beginners. All you need is: A computer (Windows, macOS, or Linux) An internet connection Willingness to learn Python step by step.
Description
This course is a practical introduction to Python for anyone interested in MLOps. It starts with the basics, such as variables, data types, conditionals, and working with lists, dictionaries, tuples, and sets. You’ll also learn about functions, how to structure them, and how to use arguments effectively.
The course gradually introduces more advanced topics like classes, object-oriented programming, and working with modules and Python scripts. It also covers how to manage your project environment using virtual environments and dependencies, which is an essential part of real-world development.
Once the foundation is set, the course moves into using Python for data handling. You’ll work with popular libraries like Pandas and NumPy to load, clean, manipulate, and analyze data. There are several hands-on lessons on exploratory data analysis, text processing in DataFrames, and visualizing data.
Toward the end of the course, you’ll apply what you’ve learned in a project based on the Titanic dataset. You’ll practice loading data, handling missing values, feature engineering, and performing analysis using Pandas. The project wraps up with writing the analysis into a Python script for easy reuse.
Finally, the course introduces you to argparse, a tool to create command-line interfaces. You’ll learn to build a simple CLI tool, giving you a small but useful taste of how Python is used in automation and scripting tasks, especially in MLOps workflows.
This course is beginner-friendly and aims to build your confidence with Python step by step.
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Who this course is for:
- This course is intended for beginners who want to learn Python with a focus on practical skills useful in MLOps and data-related tasks. It’s ideal for: Aspiring MLOps engineers who need a solid foundation in Python Data analysts or data science beginners looking to work with real datasets Developers or sysadmins transitioning into automation or data workflows Students or self-learners curious about Python for scripting and analysis If you’re looking for a hands-on way to start coding in Python and apply it to real data projects, this course is a good starting point.
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