Basic concepts

Basic concepts

×

- 50 Years Data Science
- Data Science 101

- Python for Data Analysis

- Introduction to Data Science in Python
- Toward Data Science
- Chris Albon

- An Introduction to Statistical Learning
- Kaggle

Basic concepts

Basic concepts

Study the basics of

Statistics

Learn more basics

Manipulate data with

Python

Learn new concepts

Shared knowledge

Apply concepts with

Have fun

Reap knowledge from data with

Machine Learning

Learn new concepts

Shared information

Learn how to work with

SQL

Get extra information

Concepts, ideas, and codes

*Upvote*
*
*

Community of data scientists, machine learning competitions, datasets

*Upvote*
*
*

Writing code and working with real-life data sets from your browser

*Upvote*
*
*

Questions and answers

*Upvote*
*
*

Collaborative data science platform, explore, prototype, build data products

*Upvote*
*
*

Weekly podcast featuring short mini-episodes explaining high level concepts in data science, and longer interview segments with researchers and practitioners

*Upvote*
*
*

Data manipulation, cleaning analysis, pandas, Series and DataFrames, groupby, merge, and pivot tables, hypothesis testing

*Upvote*
*
*

Introduction to statistics, descriptive statistics, correlation and linear regression, introduction to probability, probability distributions

*Upvote*
*
*

Principles of Information Visualization, basic charting with Matplotlib

*Upvote*
*
*

Definition of data science, practioneers, business, use cases

*Upvote*
*
*

Business understanding, analytic approach, data compilation, preparation, modeling, model evaluation

*Upvote*
*
*

Code snippets on data manipulation, preprocessing, machine Learning, deep learning, statistics

*Upvote*
*
*

Manipulating, processing, cleaning, and crunching data with Pandas, NumPy, and IPython

*Upvote*
*
*

Exploratory data analysis, distributions, probability mass functions, cumulative distribution functions, modeling, probability density functions, hypothesis testing

*Upvote*
*
*

Modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering

*Upvote*
*
*

Introduction to Numpy, Data Manipulation with Pandas, Visualization with Matplotlib, Machine Learning with Scikit-Learn

*Upvote*
*
*

*Upvote*
*
*

*Upvote*
*
*

This paper reviews some ingredients of the current “Data Science moment”, including recent commentary about data science in the popular media, and about how/whether Data Science is really different from Statistics.

*Upvote*
*
*

Manipulating, processing, cleaning, and crunching data with Pandas, NumPy, and IPython

*Upvote*
*
*

Data manipulation, cleaning analysis, pandas, Series and DataFrames, groupby, merge, and pivot tables, hypothesis testing

*Upvote*
*
*

Exploratory data analysis, distributions, probability mass functions, cumulative distribution functions, modeling, probability density functions, hypothesis testing

*Upvote*
*
*

Modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering

*Upvote*
*
*

Writing code and working with real-life data sets from your browser

*Upvote*
*
*

Introduction to Numpy, Data Manipulation with Pandas, Visualization with Matplotlib, Machine Learning with Scikit-Learn

*Upvote*
*
*

Introduction to statistics, descriptive statistics, correlation and linear regression, introduction to probability, probability distributions

*Upvote*
*
*

Principles of Information Visualization, basic charting with Matplotlib

*Upvote*
*
*

Definition of data science, practioneers, business, use cases

*Upvote*
*
*

Business understanding, analytic approach, data compilation, preparation, modeling, model evaluation

*Upvote*
*
*

*Upvote*
*
*

*Upvote*
*
*

Concepts, ideas, and codes

*Upvote*
*
*

Community of data scientists, machine learning competitions, datasets

*Upvote*
*
*

Questions and answers

*Upvote*
*
*

Code snippets on data manipulation, preprocessing, machine Learning, deep learning, statistics

*Upvote*
*
*

Collaborative data science platform, explore, prototype, build data products

*Upvote*
*
*

Weekly podcast featuring short mini-episodes explaining high level concepts in data science, and longer interview segments with researchers and practitioners

*Upvote*
*
*

0%
Module 1
1%
Module 2
0%
Module 3
0%
Module 4

Information

Education

Exchange

Application

Camillo ##### is curator for

Data Science

Data Science