#### Case Studies in Statistical Thinking

Take vital steps towards mastery as you apply your statistical thinking skills to real-world *data* sets and extract actionable insights from them.

133 results
for "data analytics"

Take vital steps towards mastery as you apply your statistical thinking skills to real-world *data* sets and extract actionable insights from them.

4 hours
Probability & Statistics
Justin Bois
Course

Learn to diagnose and treat dirty *data* and develop the skills needed to transform your raw *data* into accurate insights!

4 hours
Importing & Cleaning Data
Adel Nehme
Course

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

4 hours
Programming
Justin Kiggins
Course

Learn to work with time-to-event *data*. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

4 hours
Probability & Statistics
Heidi Seibold
Course

Get started on the path to exploring and visualizing your own *data* with the tidyverse, a powerful and popular collection of *data* science tools within R.

4 hours
Programming
David Robinson
Course

Gain a 360° overview of how to explore and use Power BI to build impactful reports.

4 hours
Data Visualization
Sara Billen
Course

Learn how to make sense of spatial *data* and deal with various classes of statistical problems associated with it.

4 hours
Probability & Statistics
Barry Rowlingson
Course

Learn the fundamentals of working with big *data* with PySpark.

4 hours
Programming
Upendra Kumar Devisetty
Course

Learn how to import, clean and manipulate IoT *data* in Python to make it ready for machine learning.

4 hours
Data Manipulation
Matthias Voppichler
Course

Learn to read, explore, and manipulate spatial *data* then use your skills to create informative maps using R.

4 hours
Data Visualization
Charlotte Wickham
Course

Master the complex SQL queries necessary to answer a wide variety of *data* science questions and prepare robust *data* sets for *analysis* in PostgreSQL.

4 hours
Programming
Mona Khalil
Course

Learn how to pull character strings apart, put them back together and use the stringr package.

4 hours
Programming
Charlotte Wickham
Course

Extract and visualize Twitter *data*, perform sentiment and network *analysis*, and map the geolocation of your tweets.

4 hours
Data Manipulation
Sowmya Vivek
Course

Use RNA-Seq differential expression *analysis* to identify genes likely to be important for different diseases or conditions.

4 hours
Other
Mary Piper
Course

Learn essential *data* structures such as lists and *data* frames and apply that knowledge directly to financial examples.

4 hours
Applied Finance
Lore Dirick
Course

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your *data*.

4 hours
Probability & Statistics
EDWARD KWARTLER
Course

Explore association rules in market basket *analysis* with Python by bookstore *data* and creating movie recommendations.

4 hours
Machine Learning
Isaiah Hull
Course

Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!

4 hours
Other
Paula Martinez
Course

Explore association rules in market basket *analysis* with R by analyzing retail *data* and creating movie recommendations.

4 hours
Data Manipulation
Christopher Bruffaerts
Course

Explore ways to work with date and time *data* in SQL Server for time series *analysis*

5 hours
Data Manipulation
Kevin Feasel
Course

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

4 hours
Probability & Statistics
Justin Bois
Course

Learn to analyze, plot, and model multivariate *data*.

4 hours
Probability & Statistics
Surajit Ray
Course

An introduction to *data* science with no coding involved.

4 hours
Other
Hadrien Lacroix
Course

Master core concepts about *data* manipulation such as filtering, selecting and calculating groupwise statistics using *data*.table.

4 hours
Programming
Matt Dowle
Course

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hours
Machine Learning
Shaumik Daityari
Course

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your *data*.

4 hours
Machine Learning
Dmitriy Gorenshteyn
Course

In this course you'll learn to analyze and visualize network *data* with the igraph package.

4 hours
Probability & Statistics
JAMES CURLEY
Course

Analyze spatial *data* using the sf and raster packages.

4 hours
Probability & Statistics
Zev Ross
Course

Explore latent variables, such as personality using exploratory and confirmatory factor analyses.

4 hours
Probability & Statistics
Jennifer Brussow
Course

Learn how to analyze and visualize network *data* in the R programming language using the tidyverse approach.

4 hours
Probability & Statistics
Massimo Franceschet
Course

In this course you'll learn the basics of analyzing time series *data*.

4 hours
Probability & Statistics
Rob Reider
Course

Learn the core techniques necessary to extract meaningful insights from time series *data*.

4 hours
Probability & Statistics
David S. Matteson
Course

Learn the fundamentals of exploring, manipulating, and measuring biomedical image *data*.

4 hours
Data Manipulation
Stephen Bailey
Course

Learn to use the Bioconductor package limma for differential gene expression *analysis*.

4 hours
Other
John Blischak
Course

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and *data*.table.

3 hours
Importing & Cleaning Data
Filip Schouwenaars
Course

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

4 hours
Probability & Statistics
Eric Ma
Course

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

4 hours
Data Manipulation
Jeffrey Ryan
Course

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning *data* science.

4 hours
Probability & Statistics
Eric Eager
Course

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

5 hours
Applied Finance
Kris Boudt
Course

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

4 hours
Applied Finance
Charlotte Werger
Course

Learn how to efficiently import *data* from the web into R.

4 hours
Importing & Cleaning Data
Charlotte Wickham
Course

Learn how to visualize time series in R, then practice with a stock-picking case study.

4 hours
Data Visualization
Arnaud Amsellem
Course

Apply fundamental concepts in network *analysis* to large real-world datasets in 4 different case studies.

4 hours
Probability & Statistics
Ted Hart
Course

Learn powerful techniques for image *analysis* in Python using deep learning and convolutional neural networks in Keras.

4 hours
Machine Learning
Ariel Rokem
Course

Analyze single-cell RNA-Seq *data* using normalization, dimensionality reduction, clustering and differential expression.

4 hours
Other
Fanny Perraudeau
Course

This course introduces Python for financial *analysis*.

4 hours
Applied Finance
Adina Howe
Course

Learn to analyze and model customer choice *data* in R.

4 hours
Probability & Statistics
Elea McDonnell Feit
Course

Learn how to analyse and interpret ChIP-seq *data* with the help of Bioconductor using a human cancer dataset.

4 hours
Other
Peter Humburg
Course

Develop your intuition for when to reduce dimensionality in your *data*, and master the fundamentals of how to do so in R.

4 hours
Machine Learning
Alexandros Tantos
Course

Learn about AWS Boto and harnessing cloud technology to optimize your *data* workflow.

4 hours
Programming
Maksim Pecherskiy
Course