Machine learning (ML) is on the rise at businesses hungry for greater automation and intelligence with use cases spreading across industries. At the same time, most projects are still in the early phases. From selecting datasets and data platforms to architecting and optimizing data pipelines, there are many success factors to keep in mind. The advantages that ML offers organizations—the ability to automatically build models that can analyze huge volumes of data and deliver lightning-fast results—have also led to a growth in the availability of both commercial and open source frameworks, libraries and toolkits for engineers. Attend this workshop for a hands-on course in the enabling technologies, techniques, and applications you need to know to succeed in today’s environments.

DataOps has emerged as an agile methodology to improve the speed and accuracy of analytics through new data management practices and processes, from data quality and integration to model deployment and management. By leveraging automation, data democratization, and greater collaboration among data scientists, engineers, and other technologists, DataOps can help organizations improve the time-to-value of their data. Attend this workshop to hear about the key supporting technologies, real-world strategies, and success stories and how to get started on your DataOps journey.

Data science, the ability to sift through massive amounts of data to discover hidden patterns and predict future trends, may be the "sexiest" job of the 21st century, but it requires an understanding of many different elements of data analysis. Extracting actionable knowledge from all your data to make decisions and predictions requires a number of skills, from statistics and programming to data visualization and business domain expertise. Attend this workshop for a deep dive into the fundamentals of data exploration, mining, and preparation, applying the principles of statistical modeling and data visualization in real-world applications.

A new era of cognitive computing is unfolding, and its impact is already being felt across industries, from preventative maintenance at manufacturing plants and patient diagnosis at hospitals to the rise of sophisticated chatbots ready to assist us across the connected world. The goal of cognitive computing is straightforward: to simulate human thought processes in a computerized model. However, building cognitive systems and applications that can perform specific, humanlike tasks in an intelligent way is far from easy. Attend this workshop to get a full understanding of how cognitive computing works, popular use cases, and best practices IT leaders and practitioners can apply today.