We believe data science is for everyone!
So we created free data science tutorials just for you!
Our teaching team consists of leading data scientists and practitioners who are also passionate about teaching. If you like these data science tutorials, why not come and meet them at our data science bootcamp! Be sure to check back regularly as we upload our newest content here.
Python Tutorial: Web Scraping using Beautiful Soup
January 6, 2017
Web scraping is a very powerful tool to learn for any data professional. With web scraping, the entire internet becomes your database. In this python tutorial, we introduce the fundamentals
Web Scraping in R: Creating your automated script
December 19, 2018
R tutorial: In this video tutorial you will learn how to write standard web scraping commands in R, filter timely data based on time diffs, analyze or summarize key information
Web Scraping in R: Auto Scheduling your Script
February 25, 2019
R Tutorial: In part two of our R tutorial on web scraping, we will use taskscheduleR to set up our web scraping script to run as a background task on
Time Series Forecasting in Minutes
May 13, 2019
In this Data Science in Minutes, we will describe what time series forecasting is, and provide several examples of when you can use time series for your data. Time Series
One Versus One vs. One Versus All in Classification Models
April 15, 2019
In this quick overview, we introduce you to the concepts of one-versus-one and one-versus-all in classification. In classification models, you will often want to predict one class from another. This
N-grams in Minutes
April 8, 2019
In this quick tutorial, we learn that machines can not only make sense of words but also make sense of words in their context. N-grams are one way to help
Natural Language Processing
April 1, 2019
In this quick tutorial, we go over the basics of Natural Language Processing, what it is, and a few key applications of it. Machines can’t simply read and interpret language
Clustering Introduction
March 11, 2019
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and
Introduction to Precision, Recall and F1 in Classification Models
February 4, 2019
You may have come across the terms “Precision, Recall and F1” when reading about Classification Models and machine learning. In this Data Science in Minutes tutorial, we will explain what
Introduction to the Confusion Matrix
January 28, 2019
A confusion matrix, also known as an error matrix, uses a special table to help visualize the performance of your classification model. That way, you can easily see how successful
Introduction to Classification Models
January 21, 2019
Ever wonder what classification models do? In this quick introduction, we talk about what classifications models are, as well as what they are used for in machine learning. In machine
Steps in Experimentation
January 14, 2019
In this tutorial we go over what you need for steps in online experimentation. When running a business, there are many different moving parts happening all at once. This is
A/A Testing in Minutes
January 9, 2019
So, we’ve just covered what is an A/B test and what is a multivariate test, but what is an A/A test? In this quick tutorial we go over A/A testing,
Multivariate Testing in Minutes
January 8, 2019
Multivariate testing is a technique for testing a hypothesis in which multiple variables are modified. In this tutorial, we will explain how a multivariate test differs from an A/B Test, how to create and
A/B Testing in Minutes
December 28, 2018
What is A/B testing? In this quick tutorial, we go over the basics of A/B testing, as well as answer some in-depth questions such as: why should businesses conduct A/B
Experiment Management for Machine Learning
September 2, 2019
An average data scientist spends a significant amount of time designing and running machine learning experiments This involves one or many of the following: – trying out various training algorithms
AMA About Data Science Job Interviews
July 29, 2019
Are you interviewing for a position in data science or considering switching careers? Join us for an AMA about job interviews in data science! Job interviews don’t always go the
What is a Data Engineer?
June 3, 2019
In this webinar, we will explore what is a data engineer. This includes discussing what are the goals, skills, and tools that they use on a daily basis. We wanted
R Tutorial: Automated Web Scraping Using rvest
February 22, 2019
In this R tutorial, we show you how to automatically web scrape using rvest periodically so you can analyze timely/frequently updated data. This talk was given by one of our
Building data science products? Think business first!
February 18, 2019
Modern machine learning libraries are both a blessing and a curse. Due to the ease with which the libraries can be used, most users focus too much on tools and
Artificial Intelligence For Social Good
February 4, 2019
It’s not hard to see machine learning and artificial intelligence in nearly every app we use – from any website we visit, to any mobile device we carry, to any
NLP 101 + Chatbots
November 12, 2018
In this meetup, Chris Shei talks about the basics of natural language processing: the components of NLP , enterprise applications of NLP, and finally build a simple Frequently Asked Questions
Data Visualization with ggplot2
June 20, 2018
The focus of the webinar will be using ggplot2 to analyze your data visually with a specific focus on discovering the underlying signals/patterns of your business. As an example, R’s
Data Manipulation with dplyr
March 15, 2018
dplyr is a a great tool to perform data manipulation. It makes your data analysis process a lot more efficient. Even better, it’s fairly simple to learn and start applying
Machine Learning Models: Building a Business Case for your idea
January 11, 2018
This presentation will discuss building a business case for machine learning models. In this talk, our presenter, Neeti Gupta, will provide a 10-step checklist with examples for the audience to
Ethical Dimensions of Data Science
December 15, 2017
From distorting experiments with systemic bias to imposing human ethics on machine learning models, data scientists have far more to worry about than the raw numbers in their spreadsheet. Join
Feature Engineering for Bot Detection
October 25, 2017
According to some estimates, bots constitute close to 50% of the overall traffic. In this introductory talk to Feature Engineering for Bot Detection, we will cover various aspects of feature
Online Experimentation and A/B Testing
October 13, 2017
In this meetup, we provide a quick introduction to online experimentation and A/B testing. To keep the tutorial self-contained, we will first give an overview of stats fundamentals needed to
Building Robust Models Machine Learning Models
October 12, 2017
Modern machine learning libraries make model building look deceptively easy. An unnecessary emphasis on tools like R, Python, SparkML, and techniques like deep learning is prevalent. Relying on tools and
Data Visualization with R and ggplot2
August 17, 2017
The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s rich and powerful data visualization capabilities. While
Power BI Storytelling
July 5, 2017
In this session, we will learn about telling impactful Storytelling with Power BI. Storytelling is a cornerstone of the human experience. Though many elements of stories have remained the same
Introduction to Online Experimentation and A/B Testing
June 11, 2017
In this full length segment we discuss A B testing: Online experimentation is perhaps the most misused of data science techniques. We will walk through the best practices for designing
caret Package – Machine Learning with R
June 7, 2017
The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s huge collection of open source machine learning
R Programming for Excel Users
May 3, 2017
R programming is rapidly becoming a valuable skill for data professionals of all stripes and a must-have skill for aspiring data scientists. Adding R programming to your data analyst skillset
Power BI for R Visualizations
April 5, 2017
Microsoft’s Power BI is a powerful technology for quickly creating rich r visualizations. Power BI has many practical uses for the modern data professional including executive dashboards, operational dashboards, and
Data Analysis with Excel
March 8, 2017
Business data analysis presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of
Event Log Mining with R
January 9, 2017
Event logs are everywhere and represent a prime source of Big Data. Event log sources run the gamut from e-commerce web servers to devices participating in globally distributed Internet of
Unstructured Text With Python, MS Cognitive Services & PowerBI
October 21, 2016
At this meetup, presenter Craig Guarraci speaks about how to Make Sense of Unstructured Text With Python, MS Cognitive Services & PowerBI. In this presentation we’ll take a broad look
Big Data Scaling in R Using Hadoop and Spark
June 17, 2016
R is currently one of the most popular data science languages in the world. However, it’s always had constraints around scaling out to big data. What happens when you expand
LIGO – Listening to the Melody of the Universe
March 24, 2016
Nearly 100 years after Einstein predicted the existence of gravitational waves, Laser Interferometer and Gravitational Wave Observatory astounded the world by successfully detecting these waves. Detection was made possible by
Sentiment Pipeline for Live Tweets
January 8, 2016
This will be an advanced talk on how to build a real-time predictive analytics pipeline. This will be a two hour talk and demo that covers the following: • Building
Predictive Modeling with R and Azure ML
August 6, 2014
In this 90-minute video tutorial, we will cover an overview of solving a simple predictive analytics problem. We will use R for Feature Exploration, Visualization, and Predictive Modeling with R
