BRINGING IN-HOUSE TEAMS UP TO SPEED

AGILE TOOLS AND PROCESS TRAINING FOR ADVANCED ANALYTICS

WebbMason Analytics offers a variety of courses to help in-house teams leverage Agile project management methods and tools for advanced analytics. We customized each course for your industry, team, and technology stack.

All our course leaders deliver practical and useful coursework and exercises, encourage engagement, and provide interactive support during class and workshop sessions.

Interactive Agile Training Courses

Our suite of Agile courses teaches participants how to use Agile in the analytics development lifecycle so they can deliver solutions on time and on budget.

Agile Training | Duration: 2-days

Who should attend: Analytics Center of Excellence staff, Agile toolset administrators, and scrum masters
Curriculum: You’ll learn the basic concepts of Agile and how to implement it in your analytics organization. This course will level-up your team, so everyone knows how and when to use stories, Kanban, scrum, and sprint tactics.

Scrum Master Training | Duration: 2-days

Who should attend: New and experienced scrum masters
Curriculum: This is a deep dive into advanced Agile principles and tactics for scrum masters. Participants will learn to manage the analytics development team using ticket management, sprints, and stand-up scrum meetings.

Agile Toolset Administration Training | Duration: 2-days

Who should attend: Analytics teams including scrum masters and toolset administrators.
Curriculum: Learn to configure and use popular Agile toolsets such as Jira, Confluence, Service Desk and Slack for project management and communications.

Accelerating Data Science Adoption

These course materials are designed to accelerate your businesses’ advanced analytics capabilities by bringing data scientists up to date on the latest advances, techniques, and technologies used in advanced analytics, data science, machine learning, and data modeling.

Data Science Training | Duration: 8-days

Who should attend: Statisticians, economists and other business professionals who already have a deep understanding of modeling and statistics.
Curriculum: This course will give participants a solid foundation in data science. We will look at data wrangling, machine learning, and how to choose, develop, and evaluate statistical and machine learning algorithms to extract the insights you need. You will also learn how to leverage Agile project planning and management for data science projects.

Implement the Agile Analytics Development Lifecycle

A series of workshop-style training sessions for employees who need to become proficient at implementing the analytics development process from beginning to end.

Analytics Development Lifecycle Training | Duration: 3-days

Who should attend: Leaders of the Analytics Center of Excellence or Analytics Group
Curriculum: In this course, participants will learn to master the processes and policies for all phases of the analytics development lifecycle from project planning and user-acceptance testing through operations and maintenance.

Big Data Technology Training Labs for Analytics Professionals

These hands-on training labs for beginners and advanced users of Apache Spark and H2O leverage use cases and practical exercises.

Spark & H2O: Basic Training Lab | Duration: 5-days

Who should attend: Software developers, systems engineers, analysts and program managers
Curriculum: This is a comprehensive introduction to Spark and H2O and covers everything from how Spark integrates with big data tools to using its libraries, developing data operations workflows, and developing solutions using H2O algorithms.

Spark Intermediate & H2O: Basic Training Lab | Duration: 5-days

Who should attend: Software developers, systems engineers, analysts and program managers
Curriculum: This course builds on the material taught in the Spark: Basic Training Lab. The syllabus covers advanced topics such as best practices, performance tuning, and optimization.