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computational thinking

Computer Science

2022-01-31

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Lessons List

Introduction to Computational Thinking and Data Science | Optimization | 0 1 Knapsack Problem

Introduction to Computational Thinking and Data Science | Optimization | Greedy Algorithms

Introduction to Computational Thinking and Data Science | Decision Trees | Brute Force Algorithms

Introduction to Computational Thinking and Data Science | Decision Trees | Recursive Fibonacci

Introduction to Computational Thinking and Data Science | Decision Trees | Dynamic Programming

Introduction to Computational Thinking and Data Science | Graph Problems | Graphs

Introduction to Computational Thinking and Data Science | Graph Problems | Graph Class

Introduction to Computational Thinking and Data Science | Graph Problems | Finding the Shortest Path

Introduction to Computational Thinking and Data Science | Stochastic Thinking | Stochastic Processes

Introduction to Computational Thinking and Data Science | Stochastic Thinking | Probabilities

Introduction to Computational Thinking and Data Science | Stochastic Thinking | Random Walks

Introduction to Computational Thinking and Data Science | Random Walks | Location Field and Drunk

Introduction to Computational Thinking and Data Science | Random Walks | Simulating a Walk

Introduction to Computational Thinking and Data Science | Inferential Statistics | Variation in Data

Introduction to Computational Thinking and Data Science | Inferential Statistics | Distributions

Intro to Computational Thinking and Data Science | Monte Carlo Simulations | Central Limit Theorem

Intro to Computational Thinking and Data Science | | Monte Carlo Simulations Simulation to Find Pi

Intro to Computational Thinking and Data Science | Sampling and Standard Error | Data Sampling

Introduction to Computational Thinking and Data Science | Sampling and Standard Error | Sample Sizes

Intro to Computational Thinking and Data Science | Sampling and Standard Error | Standard Error

Intro to Computational Thinking and Data Science | Independent Random Samples

Intro to Computational Thinking and Data Science | Experimental Data | Fitting a Model to Data

Introduction to Computational Thinking and Data Science | Experimental Data | Goodness of Fit

Introduction to Computational Thinking and Data Science | Experimental Data | Fits for Datasets

Intro to Computational Thinking Data Science | Experimental Data | Model Predictions and Overfitting

Introduction to Computational Thinking and Data Science | Experimental Data | Cross Validation

Intro to Computational Thinking and Data Science | Machine Learning | What is Machine Learning

Introduction to Computational Thinking and Data Science | Machine Learning | K Nearest Neighbors

Introduction to Computational Thinking and Data Science | Machine Learning | Clustering

Intro to Comp Thinking and Data Science | Statistical Fallacies | Lies Damned Lies and Statistics

Introduction to Computational Thinking and Data Science | Statistical Fallacies | Texas Sharpshooter

Intro to Computational Thinking and Data Science | Statistical Fallacies | Correlation and Causation

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Computational Thinking teaches the use of abstraction and decomposition when solving complex problems; it presents a framework for understanding algorithms; and it describes essential concepts in dealing with data and code and in expressing the limits of modern computing machinery .

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