From learning Python to creating analytical reports, learn about ten easy steps to become a data scientist.

Modern organizations regard data as a strategic asset that drives efficiency, enhances decision making, and creates new value for customers. Across the organization—product management, marketing, operations, finance, and more—teams are overflowing with ideas on how data can elevate the business. To bring these ideas to life, companies are eagerly hiring data scientists for their technical […]

This new program offers two immersive program levels, industry-recognized credentials, classroom instruction, around-the-clock access to SAS software and course materials, and more.

This new program offers two immersive program levels, industry-recognized credentials, classroom instruction, around-the-clock access to SAS software and course materials, and more.

Learn how to become a data-driven organization from Linda Schumacher, senior director of analytics and data strategy at CX company Qualified Digital.

It’s almost 10 years since "Data Science" became mainstream. We ask less about how to get into Data Science, but wonder "what’s next?" This article includes insights on four non-trivial, but practical, options and their pitfalls.

Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.

Check out these 10 books that can help data scientists and aspiring data scientists learn machine learning today.

The COVID-19 pandemic has affected everything, and building predictions during this time is difficult. Data science teams need to update their models to prepare for the recovery, and know how to properly train 2020 data models to learn from the coronavirus anomaly.

This year's KDD Cup features four distinct tracks that welcome participants to tackle challenges in e-commerce, generative adversarial networks, automatic graph representation learning (AutoGraph) and mobility-on-demand (MoD) platforms. Winners will be recognized at KDD 2020, the leading interdisciplinary conference in data science, in San Diego on August 23-27, 2020.

At present, the data scientist is one of the most sought after professions. That’s one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.

I realized that from a corporate perspective, “fortune teller” was not entirely off from the role of a “data scientist”.

IBM today announced a significant new release of its PowerAI deep learning software distribution on Power Systems that attacks the major challenges facing data scientists and developers by simplifying the development experience with tools and data preparation while also dramatically reducing the time required for AI system training from weeks to hours.

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.

Seth Stephens-Davidowitz claimed that Google search results from around the world could be key to determining undiscovered coronavirus symptoms.

Barker Library - QA276.M73 2019

New York, NY : Springer New York : Imprint: Springer, 2014