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Introduction to Computational Thinking and Data Science (MIT)

(14 Lectures Available)


Lecture Course Institute Discipline
Introduction and Optimization Problems Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Graph-theoretic Models Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Stochastic Thinking Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Random Walks Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Monte Carlo Simulation Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Confidence Intervals Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Sampling and Standard Error Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Understanding Experimental Data Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Understanding Experimental Data (cont.) Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Introduction to Machine Learning Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Clustering Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Classification Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Classification and Statistical Sins Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences
Statistical Sins and Wrap Up Introduction to Computational Thinking and Data Science (MIT) MIT Applied Sciences

of 1 14 Lectures Available.