Taking your code from the lab and into production!

Transform your ML skills from models to real-world applications. By bridging the gap between data science and software engineering, you'll acquire the critical knowledge and abilities necessary to transform any ML model within a Jupyter notebook into a fully operational, production-ready microservice from scratch!

Course prerequisites

  1. Knowledge and practical experience of Python syntax
  2. Experience in model development in Python (train-test split, tuning hyperparameters, evaluating model performance, making predictions)

Who can benefit?

Ideal for aspiring data scientists or software engineers at any stage of their career, seeking to fast-track their engineering skills / become an ML Engineer.


Get to know the detailed course outline by watching Course Compass: Exploring the Jorney Ahead!
Check out the free preview videos to confirm this course is right for you!

Curriculum


  Getting started
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  1. Model Creation in Jupyter Notebook
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  2. Model-to-App Packaging: Production Codebase Design
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  3. App-to-Micro Transformation: API Development (WIP)
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  4. Deploying Microservice (WIP)
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Enrolment