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0. Overview

This course bridges the critical gap between software development and data science. We provide a hands-on, Python-based curriculum to give you the skills and confidence needed to successfully lead and execute AI and machine learning projects. Whether you are a data scientist aiming to productionize models or a software developer entering the AI/ML space, you will find practical guidance here.

This chapter outlines the core components of your learning journey:

  • 0.0. Course: Discover our mission: to merge software engineering discipline with data science and empower you to build robust AI/ML solutions with Python.
  • 0.1. Projects: Learn about the hands-on projects that form the core of this course and how to apply the concepts to your own work.
  • 0.2. Datasets: Understand the role of datasets in the AI/ML lifecycle and learn how to select and manage them effectively.
  • 0.3. Platforms: Explore the MLOps platform landscape and learn how to select the right tools, in line with our platform-agnostic philosophy.
  • 0.4. Mentoring: Find out how to accelerate your learning with personalized mentoring and expert support from our course creators.
  • 0.5. Assistants: Meet your AI-powered course assistant and learn how to use it to get instant help and guidance.
  • 0.6. Resources: Access additional materials to deepen your knowledge and learn how you can contribute to our open-source curriculum.