The Fastest Way To accelerate Your Data Career.
Fill In The Skill Gaps That Hold You Back From Advancing.
Self-Paced Course
Exercises
Live Career Advisory Time
Optional 1 on 1 Support
You'll Get 12 Month's Access To The complete course And office Hours.
The Value Centric Data Professional.
Get All This For Just $195
Why Data Teams Struggle With Value
Introducing 2 frameworks to help you teach the business where data science fits and what problems the team can solve. Get buy in from external teams.
Reframing A Business Problem As A Data Science Problem
Explaining a framework for breaking business problems down into digital, data, or model solutions. Value starts by selecting the right problems to work on and delivering the best technical solution.
Defining The Project
Providing a framework to define the project along 3 lines: business problem, data, and solution. I also cover assessing initiative feasibility and selecting the right success metrics. This is where high value projects begin to take shape.
Working With External Teams & Stakeholders
I introduce a framework to solve the AI last mile problem that keeps data products from reaching production and being adopted by users. Using the AI Governance framework, external teams become partners and bring high value initiatives to the data team.
Understanding The Business & Basic Strategy
Covering business essentials like the business and operating models, value streams, competition, and introducing the technology model framework. This section will take your business IQ into the top 1% of data professionals.
The Communications Framework
Executive level communications skills are critical for career and data initiative success. I teach an advanced communications framework with examples of how to implement it. Examples include getting buy in for data engineering infrastructure and justifying a data science initiative.
Career Advancement Frameworks
Covering frameworks for developing a career roadmap, setting expectations with your leader, and aligning with the business. This section gets you ready to move forward and leverage your new skills to achieve your career goals.
Implementation Cases & Exercises
I walk through 5 implementation case exercises that reinforce the main frameworks and provide real world examples to follow. This is the most popular section in the course. Students enjoy the implementation cases and solution walk throughs.
Meet Your Instructor
Your learning outcomes and objectives are my highest priority.
I have a 3-layered professional background: Technology, Leadership, and Strategy.
Over 25 years in technology, I started my career in software engineering and moved into data science in 2012.
I am one of the only published authors on Data and AI Strategy (From Data to Profit, Wiley 23) and one of the most experienced practitioners. I built Data and AI Strategies for 10 of the largest companies in the world, 21 SMEs, and 3 startups.
V-Squared is one of the oldest data science consulting firms. I founded it in 2012 as a technical consulting practice but quickly realized that I needed C-level buy-in if I wanted to get the budget for advanced machine learning projects. I began developing the frameworks I teach in 2015. I taught my first cohort in 2017 and offered the course publicly in 2020.
Since 2014, I have been called a Data Science and AI Strategy expert by IBM, Intel, SAP, LinkedIn, NVIDIA, and others. I am a globally recognized thought leader, followed by Gartner, Walmart, Uber, Microsoft, Salesforce, MongoDB, Deloitte, and more.
Thank you for giving me the opportunity to teach. It is an honor to teach and one I greatly enjoy.
Self-Paced Course Overview
1. Introduction
- Course Benefits & Outcomes
- Course Outline & Overview
3. Reframing A Business Problem As A Data Problem
- 3 Different Problems: Software, Data, and Model
- Defining A Software Problem
- Defining A Data Problem
- Defining A Simple Model Problem
- Defining An Advanced Model Problem
5. Building Data Science Requirements From User Requirements
- The AI Last Mile Problem
- Phase 1: Commercialization
- Phase 2: Productization
- Phase 3: Monetization
7. The Communications Framework
- Introduction To The Communications Framework
- How Impact Changes Communications
- Communications Objectives
- Communications Discipline
- Creating Opportunities For Multiway Communications
9. Career Advancement Frameworks
- There Must Be Something In It For You
- Career Roadmap: Main Career Tracks And Transitions
- Career Roadmap: Definition Points
- Aligning With Your Leader And The Business
- Finding Advocates And Mentors
11. Working With The Business
- Starting With Experts
- Introducing Improvements
- Meet The Business Where It Is
- Ending Us VS Them
- Trusting And Building Trust
2. Why Data Teams Struggle To Deliver Value
- The Business Isn’t Ready For Data
- Fitting The Data Team Into The Business
- Explaining The New Paradigm
4. Defining The Project
- Why Define These Upfront?
- Problem Space Definition
- Data Space Definition
- Solution Space Definition
- The Feasibility Assessment
- Transforming A Technical Presentation To A Business Presentation
- A New Presentation Approach
- Selecting The Right Success Metrics
6. Understanding The Business And Basic Strategy
- Business Model
- Operating Model
- Technology Model
- Value Stream
- Business Strategy
- Assessment Framework
8. Advanced Communications
- Communicating For Impact
- Crafting Communications Objectives
- Introduction To Presentation Flow
- Slide Flow Basics
- Understanding C-Level Communications
- Gaining A C-Level Sponsor
- Pushback Strategies That Won’t Get You Fired
- 3 Examples Of Communications In Action
10. Exercises
- Fixing Broken Communications
- Business Model Assessment
- Operating Model Assessment
- Which Technologies Should You Use?
- Choosing Success Metrics When There Aren’t Any
12. Product First Thinking
- Introduction To Product Management And Why Learn This?
- Product Maturity And A More Structured Approach To Building Products
- Product First Thinking
Get Reimbursed By Your Employer
Value determines career velocity. People who can solve the business’s toughest challenges get the greatest rewards. Here's what you'll get.
Acquire Business Acumen & Improve Your Business IQ
Become More Strategic
Develop Your Executive Communications Skills
Manage Stakeholders & Collaborate Effectively With External Business Units
Align Your Work With Business Value
Present Effectively To Non-Technical Audiences
Set & Manage Expectations
Get & Keep Senior Leadership Buy-In
Gain External Team Support
Higher Customer & User Adoption Rates
Overcome Resistance To Data-Driven
Improved Your Credibility With Leadership
Businesses now expect it and will not hire Data Scientists without business acumen and strategy. These quotes from recent job descriptions tell the story.
Johnson and Johnson
“Ability to build strong networks across the business and technology group to develop partnerships at all levels of the business.”
Microsoft
“Interprets results and develops insights into formulated problems within the business/customer context and provides guidance on risks and limitations.
Works collaboratively with PMs to translate the business needs into metrics and then works with data engineering to implement these metrics including identifying and obtaining the necessary data.”
Zoom
“Build cross-functional relationships with multiple business leaders to understand data needs and deliver on those needs.”
Spotify
“Identify the most impactful opportunities for product development based on user needs and execute on them diligently and resourcefully.
Maintain a culture of rigor and data-informed decision-making to drive tangible business impact.”
Amazon
“Write detailed analysis reports to communicate findings and recommendations to teammates, stakeholders, and executive leadership.
Track record of solving ambiguous problems and delivering complex software systems to customers.
Excellent technical writing and communication skills and ability to convey scientific concepts to non-technical business audiences.”
Walmart
“Work closely with leaderships, product managers, system engineers to continuously and collaboratively ship new models, algorithms and improvements into production. Present business insights internally and externally.”
Visa
“Brainstorm innovative ways to use our unique data to answer business problems.
Connect with clients to understand the challenges they face and convince them with data.
Extract and understand data to form an opinion on how to best help our clients and derive relevant insights.”
IBM
“Demonstrate strong business acumen and ability to understand business problems, formulate hypotheses and test conclusions to influence solution design.
Expand partnerships at all levels of the client organization to identify new opportunities for data science applications.”
Shopify
“Proactively identify and champion projects that solve complex problems across multiple domains.
Partner closely with product, engineering and other business leaders to influence product and program decisions with data.
Apply specialized skills and fundamental data science methods (e.g. regression, survival analysis, segmentation, experimentation, and machine learning when needed) to inform improvements to our business.”