1-day data science workshops

 

Our workshops are 5-hour 'deep dives' that focus in on a particular skill

each workshop features dense and comprehensive coverage of the skill. 

and each gives you data science projects to add to your portfolio and resume.

upon completion, you'll receive an official accelerate certificate of completion. 

You'll be satisfied with what you'll get.

How confident are we? We stand by our workshops with a money back guarantee.

spots are limited. secure your seat today. 

Machine Learning Clustering Techniques Workshop

Coming in 2020

Cluster analysis is the most popular and useful form of unsupervised machine learning. Here you'll gain in-depth coverage and experience with the most in-demand clustering techniques. 

Prerequisites: Some basic computer programming background in R is recommended. Some statistics background is recommended, but not strictly necessary. 

 

 

Deliverables: 2 clustering projects to add to your portfolio and resume

Linear Regression Deep Dive Workshop

 

Now enrolling for:

September 28, 2019

Linear regression is the most widely used technique in machine learning and statistical modeling. It is the perfect starting place if you are just getting started in data science, stats, or machine learning. Even good for intermediates, we go deep into linear regression in this workshop, covering its use and common issues for both inferential statistics and predictive analytics.

Prerequisites: None, but some basic knowledge of R programming is recommended

Deliverables: 3 linear regression projects to add to your portfolio and resume

Tree-based Machine Learning Algorithms Workshop

Enrollment currently closed. Will be offered again in 2020.

Tree-based algorithms are widely popular these days, and for good reason (they are awesome techniques that can give you impressive accuracy at relatively low cost). To become a data scientist, you must be proficient in the algorithms covered in this workshop. Here we will go deep into decision trees, bagging, random forests, gradient boosting, and more. 

Prerequisites: Comfort with programming in R. Some statistics background recommended.

Deliverables: 3 machine learning tree-based projects to add to your portfolio and resume

how to get started? 

reach out to us to discuss how you can get  started with accelerate.

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