Notebook to Production with GitHub

Lightning Lessons

Practical skills & tools to accelerate your career

Notebook to Production with GitHub

Hosted by Manisha Arora

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438 students

Share this lesson

438 students

Go deeper with a course

AI-ML Projects for Data Professionals

Manisha Arora and Siddarth Ranganathan

What you'll learn

Organize Workflows for Reproducibility and Scalability

Structure projects with modular code, clean hierarchies, and version control for scalability and reproducibility.

Transition from Jupyter Notebooks to Production Code

Convert messy notebook code into reusable scripts and pipelines for ingestion, training, and deployment.

Collaborate with your Team via GitHub

Use GitHub branching, pull requests, and automations to streamline workflows and enhance team collaboration.

Why this topic matters

Many data scientists struggle to move beyond notebooks, leading to scattered files, poor reproducibility, and collaboration issues. Adopting GitHub best practices helps organize workflows, streamline collaboration, and transition to production smoothly. These skills are essential for solving real-world challenges and showcasing polished, professional projects that can elevate your career.

You'll learn from

Manisha Arora

Data Science Lead at Google

I am a seasoned Data Science professional with 10+ years of experience leading data science teams and driving business growth through data-driven decision making. Having navigated the job market both as a candidate and as an interviewer, I understand the intricacies of the hiring process from both perspectives.

I am passionate about democratizing data science and enabling others level up in their careers. I found PrepVector to enable aspiring professionals to excel in their data science careers. I have taught 350+ data professionals through my courses at Maven & PrepVector. I am committed to providing individuals with the skills and knowledge required to thrive in the industry.

Previously at