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Growth Paths / DS Curriculum 10: Machine learning and data mining
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DS Curriculum 10: Machine learning and data mining

Train models, go deeper with neural nets, and mine large data.

Train models, go deeper with neural nets, and mine large data. Free courses, a free self-check for each, and real work confirmed by 3 people. Part of the Varsity Curriculum: Data Science, adapted from OSSU Data Science (CC BY-SA 4.0).

Part of: Data Science · Proves for: UG

6 required outcomes40 weeksCredential on completion

Path outcomes

How this is verified: 5 are checked automatically, then confirmed by one person; 7 are confirmed by people who saw the work.

Skills

Learn Machine Learning Basics

Supervised Machine Learning: Regression and Classification — reuses an outcome Powstik already has.

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2 milestones

  1. 1Do the course work in public
  2. 2Train a model on real data
Skills

Train Neural Networks and Tree Models (fast.ai)

Advanced Learning Algorithms

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2 milestones

  1. 1Do the course work in public
  2. 2Beat a baseline with a neural net or a forest
Skills

Learn Clustering, Recommenders and Reinforcement Learning (MIT 6.036)

Unsupervised Learning, Recommenders, Reinforcement Learning

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2 milestones

  1. 1Do the course work in public
  2. 2Build a small recommender or agent
Skills

Build Machine Learning Projects (Udacity Intro to ML)

Intro to Machine Learning

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2 milestones

  1. 1Do the course work in public
  2. 2Find a pattern in real data
Skills

Mine Massive Datasets (Stanford MMDS)

Mining Massive Datasets

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2 milestones

  1. 1Do the course work in public
  2. 2Find similar items at scale
Skills

Find How Work Really Flows (Process Mining)

Process Mining: Data Science in Action

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2 milestones

  1. 1Do the course work in public
  2. 2Map a real process from its event log

Resources for this path

No affiliate links. No sponsored placements.

The course map this path is adapted from (CC BY-SA 4.0).