ACQUIRE THE BASICS AHEAD OF CLASS
This preparatory session establishes a baseline understanding of the introductory material required to hit the ground running in the highly interactive “Building the Analytics-Driven Operation” courseware. By viewing this initial lecture in advance of the live training session, participants will be prepared to proceed directly into the lecture / demo / work-along cycle format. In addition, those attending the Comprehensive course will not be exposed to the same introductory material at the start of each independent module within the series.
This presentation is an asynchronous lecture that may be viewed at your leisure. It is an independent prerequisite module and not representative of the delivery style of the interactive classroom or live online training. Core Concepts conveys a mind-shifting perspective for applied analytics and AI to those new to the practice, while preparing a platform for more coverage and momentum in the “Building the Analytics-Driven Operation” courseware.
WHO SHOULD PARTICIPATE
- ALL “Building the Analytics-Driven Operation” COURSE REGISTRANTS to arrive with a general overview and solid baseline underfoot, ready to dive directly into the interactive work-along sessions of the classroom or online productions
- TECHNOLOGY INVESTIGATORS who seek an efficient orientation to AI & machine learning to prioritize the practice among other organizational business intelligence objectives
- THE ANALYTICALLY CURIOUS who desire additional perspectives on the topic
UPON COMPLETION, YOU WILL BE ABLE TO:
- Start the mind shift from a traditional tactical emphasis to a strategic focus for AI and machine learning
- Recognize primary strategic and tactical pitfalls that plague the majority of AI implementations
- Outline and understand the four stages of the low-risk / high-impact Incremental Development Strategy
- Identify and understand the Three-Step Project Design and the Four Core Analytic Project Types
- Define basic performance metrics and behaviors of interest
- Understand the basic factors in qualifying and prioritizing organizational analytic opportunities
- Proceed efficiently into any course within “Applied AI & Machine Learning” course series with the required baseline knowledge
TOPIC COVERAGE
INTRODUCTION
- Welcome and Series Organization | Eric A. King | 1:47
OVERVIEW
- What is Predictive Analytics & Data Mining? | Keith McCormick | 15:00
- An Established Process: CRISP-DM | Keith McCormick | 9:10
- TMAs Modeling Practice Framework | Keith McCormick | 14:24
ASSESS PHASE
- Assess Phase Introduction | Keith McCormick | 8:49
- The Project Team, Roles and Themes | Keith McCormick | 16:49
- Software Considerations | Keith McCormick | 12:18
PREPARE PHASE*
(*Required Only for Comprehensive Course)
- The Interplay of Stats and Machine Learning | Patrick Rooney, PhD | 7:26
- The Process and Effect of Normality | Patrick Rooney, PhD | 7:51
- The Scale of Measure | Scott Terry | 12:25
MODEL PHASE*
(*Required Only for Comprehensive and Development Courses)
- Three Major Modeling Types | Scott Terry | 12:22
- Holdout Validation | Patrick Rooney | 3:55
- Other Modeling Types | Patrick Rooney | 7:23
DEPLOY PHASE*
(*Required Only for Comprehensive and Development Courses)
- Deploy Phase Introduction | Keith McCormick | 8:45
MONITOR PHASE*
(*Required Only for Comprehensive and Development Courses)
- Monitor Phase Introduction | Keith McCormick | 9:11
WRAP UP
- You’re Ready for Training! | Eric A. King | 0:44