Machine Learning Fundamentals - Syllabus

Upgrade your skills with Codecademy's Pro Intensive, Machine Learning Fundamentals.

Each unit will cover conceptual and syntax lessons and quizzes. There will also be a few cumulative off-platform projects throughout the Intensive. Articles and videos will be available to supplement your learning.

Unit 1- What is Machine Learning?

Learn about the types of problems to solve with machine learning.

  • Machine Learning Process
  • Learn about Scikit
  • Why Data?

Unit 2 - Regression

Predict continuous-valued output based on the input value(s).

  • Distance Formula
  • Linear Regression
  • Multiple Linear Regression
  • Precision vs Recall

Unit 3 - Classification

Classify data into different categories.

  • Bayes’ Theorem
  • Naive Bayes Classifier
  • K-Nearest Neighbors
  • The Ethics of Overfitting

Unit 4 - Unsupervised Learning

Find patterns and structures in unlabeled data points.

  • K-Means Clustering
  • K-Means++ Clustering

Unit 5 - Neural Network Teaser

Implement a single neuron - the building block of neural networks.

  • Perceptron

Unit 6 - Capstone Project

Apply your new knowledge to complex projects reviewed by experts.

  • Yelp recommender 
  • Date-a-Scientist 
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