Zdeněk Hejl

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Developing Data Products

Practical Machine Learning

Regression Models

Statistical Inference

Reproducible Research

Exploratory Data Analysis

Getting and Cleaning Data

R Programming

1<p>Section<p><b>25 hours to complete</b><p>Week 1: Background, Getting Started, and Nuts & Bolts<p>This week covers the basics to get you started up with R. The …

The Data Scientist’s Toolbox

An Introduction to R

2.7 Index vectors; selecting and modifying subsets of a data set<p>Subsets of the elements of a vector may be selected by appending to the name of the …

Foundations of Data Analysis - Part 1: Statistics Using R

Data, Analytics and Learning

Learning From Data (Introductory Machine Learning)

Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."

Introduction to Statistics: Inference

https://prod-discovery.edx-cdn.org/media/course/image/8f62ff56-70d1-4d7d-8402-998ba0a87393.small.jpg<p>An introduction to statistical ideas and methods …

Introduction to Statistics: Probability

An introduction to probability, with the aim of developing probabilistic intuition as well as techniques needed to analyze simple random samples.

Introduction to Statistics: Descriptive Statistics

https://prod-discovery.edx-cdn.org/media/course/image/e08f2ee5-199b-4754-a218-5071aff0468e.small.jpg<p>An introduction to descriptive statistics, …

Introduction to Probability - The Science of Uncertainty

An introduction to probabilistic models, including random processes and the basic elements of statistical inference.

Data Analysis: Take It to the MAX

Enhance your data analysis skills using spreadsheets and data visualization. Increase your productivity and make better business decisions.

I "Heart" Stats: Learning to Love Statistics

Is your relationship with statistics dysfunctional? We can help: Get to know stats, build a healthy bond, and maybe even fall in love!

Distributed Machine Learning with Apache Spark

Learn the underlying principles required to develop scalable machine learning pipelines and gain hands-on experience using Apache Spark.

Introduction to Computer Science and Programming Using Python

A new and updated introduction to computer science as a tool to solve real-world analytical problems using Python 3.5.

Introduction to Computational Thinking and Data Science

Statistical Inference and Modeling for High-throughput Experiments

Statistics and R

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Introduction to Linear Models and Matrix Algebra

Introduction to Psychology

There is no more salient topic in the global information age than the human condition, including learning, behavior and dysfunction.


Explore Statistics with R

Learn basic statistics in a practical, experimental way, through statistical programming with R, using examples from the health sciences.

The Analytics Edge

Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.