Support Vector Machines in R
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
In this course youll learn how to perform inference using linear models.
Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.
Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.
In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.
Learn all about how DataCamp builds the best platform to learn and teach data skills.
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
This course is for R users who want to get up to speed with Python!
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Explore HR data analysis in Tableau with this case study.
Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
This course will show you how to combine and merge datasets with data.table.
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.
Learn to use the Bioconductor package limma for differential gene expression analysis.
In this course youll learn how to leverage statistical techniques for working with categorical data.
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Learn how to access financial data from local files as well as from internet sources.
This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
In this course youll learn techniques for performing statistical inference on numerical data.