AI+ Subscription Content Available Right Now
By: Odsc - Open Data Science
Tags: Open Data, Data Science, Deep Learning, Machine Learning, Artificial Intelligence

The AI+ Training Subscription Plans are now live! With workshops, tutorials, and training sessions on essential data science and AI topics, such as NLP, Machine Learning, AI Fairness and Explainability, Data Engineering, and MLOps, and new content added all the time, you’ll never have to stop learning with our offerings of AI+ subscription content.

[Related: Announcing the AI+ Data Science Live Training Subscription Service]

Below is a sample of the on-demand AI+ subscription content & data science training you can access right now.

Deep Learning (with TensorFlow 2 & PyTorch) with Dr. Jon Krohn, Chief Data Scientist at untapt and Author of Deep Learning Illustrated

In just a few short years, deep learning has become an essential data science skill that is utilized for applications as diverse as NLP, machine vision, complex sequential decision making, and artistic creativity. During this interactive data science training course, you’ll begin to build an intuitive understanding of deep learning’s foundations through essential theory and hands-on exercises. You’ll leave this session able to avoid common pitfalls and build deep neural network models as part of this initial AI+ subscription content.

Using Bootstrapping for Modern Data Science with Ryan Harter, Principal Data Scientist at Mozilla

Incredibly powerful, the bootstrap resampling method has become increasingly popular in data science. However, it’s not without its pitfalls. In this data science and AI training, you’ll learn to understand how the bootstrap fails, how to spot it, and how to fix it. You’ll also learn when to use the bootstrap and when to use more traditional methods like the t-test.

DS 101 and 102: Machine Learning & Modelling in Theory & Practice with Dr. Kirk Borne, Principal Data Scientist at Booz Allen Hamilton

Modeling is an essential component of any science and data science is no exception. In data science, observations are utilized to inform models, machine learning is used to create testable models, and the scientific method is utilized to test and improve the models to discover actionable insights. In this two-part data science course on machine learning and modeling, you’ll focus on both foundational concepts and theory and examples.

Data Science and Machine Learning in the Cloud for Cloud Novices with Joy Payton Supervisor, Data Education at Children’s Hospital of Philadelphia

Never used cloud computing before? No worries! In this hands-on AI+ subscription content training, you’ll be introduced to cloud computing and learn how to use its resources in machine learning and data science. To get the most out of this session, however, you should have some experience with data science, machine learning, or data analytics.

Explaining and Interpreting Gradient Boosting Models in Machine Learning with Brian Lucena, PhD Consulting Data Scientist at Agentero

Although Gradient Boosted Trees in many cases provide the best predictive power, and have become a common method of prediction when utilizing structured data, they are occasionally criticized as “difficult to interpret.” During this data science AI+ subscription content, you’ll get hands-on experience using XGBoost with data sets from the real-world to learn how approach data sets in a way that improving prediction also improves understanding of the data.

Streaming Decision Intelligence and Predictive Analytics with Spark 3 with Scott Haines, Principal Software Engineer at Twilio

It’s becoming increasingly important to be able to use data science and AI to make decisions. Current examples of intelligent decision making include assisted analysis used for forecasting and integrated systems utilized for customer service. During this AI training course, you’ll learn how to utilize Apache Spark to create a data ingestion pipeline capable of making a simple decision in a parallel streaming system with SparkSQL.

Network Analysis Made Simple with Eric Ma, PhD, author of nxviz Package

This data science AI+ subscription content will focus on the fundamentals of network thinking. Using a variety of datasets, you’ll learn about visualizing, constructing, and summarizing complex networks. This knowledge will help you understand how recommendation systems function and how epidemiologists track the source of a viral outbreak.

Hands-on Machine Learning Explainability with Violeta Misheva, PhD, Data Scientist at ABN AMRO Bank N.V.

Over the last several years explainable AI and machine learning have become increasingly essential in a wide variety of industries such as insurance, healthcare, and finance. Concurrently, research into this field has also grown significantly. There are numerous methods available that provide some level of explainability. There are also several libraries and packages. In this AI training course, you’ll learn about some of the more promising methods, as well as, get hands-on experience with several different explainable AI libraries.

Don’t miss this chance to start your continuous learning journey with some of the best and brightest minds in data science and AI with a monthly subscription to the AI+ Training Platform with this novel AI+ subscription content.