AI and Machine Learning: Today’s Implementation Realities
Duration: Three Day Workshop
AI and machine learning have returned to the spotlight. This time, they’ve caught the attention of the C-Suite and stakeholders as the leading value-drivers within data science.
With this level of visibility, today’s machine learning needs to do more than uncover interesting insights. Most organizations focus almost exclusively on algorithms, software, coding, and platforms. Although these tactics are important, they only make up one of three pillars required to run a productive AI operation.
Each day of this three-day workshop focuses on one of the pillars:
- Preparing for AI and machine learning action and adoption
- AI opportunity identification, project design, and preparation
- The methods and mechanics of machine learning
Attend this workshop to learn how to apply a comprehensive implementation framework that not only ensures superior model performance, but prepares the operational environment for automated decision-making and the organizational team for adoption.
You Will Learn
- Identify, qualify, and prioritize viable and actionable AI opportunities
- Develop a strategy for applying data-driven decisions aligned with organizational priorities
- Evaluate the latest machine learning methods and approaches in view of the project design
- View a comprehensive implementation framework for running an AI operation
- Acquire a balance of tactical and strategic skills required to stand out as a data scientist
- Prevent AI project failure and understand why it’s almost never due to technology
- Enhance your professional profile with unique translator skills in low supply and high demand
- C-Suite executives looking to set a confident vision and realistic goals for AI
- Line-of-business leaders ready to move from mere analysis to measurable action
- Functional managers seeking a low-risk/high-impact implementation framework
- Data scientists wanting to stand out from quants and coders with broader process acumen
- BI and IT leaders concerned with deploying and operationalizing models
- AI consultants wishing to experience the modern complexities of organizational AI implementation
- Innovation planners charged with investigating leading strategies for AI practice development