Dave on Data

The Dave on Data mission is to empower any professional (or team) with the DIY data science skills needed to unleash the power of AI technologies like Copilot in Excel.

What gets left out of the AI Hype Cycle is this:

AI will make you (or your team) wildly more productive.

**BUT**

You must have the requisite skills to make the most of AI.

**AND**

If these skills are lacking, you will not be able to recognize (and correct) the AI when it makes mistakes.

BTW - AI makes mistakes all the time.

Take Microsoft's Copilot in Excel AI as an example.

The "magical" scenarios where Copilot analyzes data using a few clicks and a couple of short prompts rely heavily on two things:

Python
Machine learning

Here's the thing, however. 

I've tested Copilot in Excel, which rarely generates the correct Python/machine learning code.

As the DIY data scientist, this is where you unleash Copilot's power.

I can teach you these DIY data science skills.

Regardless of role. Regardless of background.

Founder

TDWI

I develop and deliver live training experiences on data science topics such as data analysis and predictive analytics (e.g., machine learning). I focus on accelerating the data science journey for teams and organizations using a practical hands-on approach.

Training can be delivered virtually or in person with your team. The following offerings are certified by TDWI and can be taught using R or Python:

👉 Machine Learning Bootcamp
👉 Visual Data Analysis
👉 Linear/Logistic Regresion

💻 Learn more: https://daveondata.com/live-analytics-training

Data Science Consultant & Instructor

Schedulicity

VP of Analytics

Data Science Dojo

VP of Data Science

Microsoft

Sr. Director, BI and Analytics

Principal Program Manager

Sr. Director, Platform Architecture

Principal Architect

Ascentium Corp

Associate Partner, Solution Architect

Safeco Insurance

IT Architect

e-software, Inc.

Software Design Engineer

Programmer Analyst

I help ANY professional or team have more impact using data. Analytics demystified.

Want to differentiate yourself at work with Excel skills? Leaders aren't excited about this in 2025:

- Using PivotTables
- Knowing many Excel functions

You know what they're excited about: AI

And that means Copilot in Excel.

Here are the 4 steps to build the skills you need to master Copilot in Excel and impress your manager, business stakeholders, and executives:

1) Ignore "prompt engineering."
2) Learn Python.
3) Learn DIY data science.
4) Recognize hallucinations.

I want to help you own the future of Microsoft Excel.

I will help you get started today - for free.

Join 1,000s of professionals building skills for the future: 
https://daveondata.com/newsletter

David Langer

As an author, there's nothing quite like waking up to some good news from Amazon!

Back in May of 2023, I saw an early version of Python in Excel for the first time. I immediately knew I wanted to be a part of the most significant upgrade in Excel's analytics capabilities ever. 

And it didn't stop there.

When I first got access to Copilot in Excel's "advanced analysis" mode, I quickly saw Microsoft's vision for Excel's future. For professionals building Python analytics skills, the future of Excel lies in deep integration with Copilot AI to unleash the power of their data.

My book is the first step in building the skills for Excel's AI-powered future. It uses your existing knowledge of Excel to help you learn the Python foundation you need - fast.

If you're ready to make 2026 the year you embrace the power of Excel, AI, and data, you can pre-order my book here: https://lnkd.in/eQp4g5_d

#Excel #PythonInExcel #MicrosoftExcel

I help professionals and teams build better forecasts using machine learning with Python and Python in Excel.

Interesting behavior from Copilot in Excel. Just another example of how Python in Excel skills are part of Excel's AI-powered future.

I was working on the next issue of my LinkedIn newsletter, which will cover using AI to build better forecasts in Microsoft Excel, and asked Copilot to create a forecast for me.

I was surprised to see that Copilot didn't use Excel's FORECAST.ETS() function because that's the best way to build data-driven forecasts using native Excel features.

Instead, Copilot in Excel generated Python code in the background to build an ETS model similar to what would be produced from FORECAST.ETS() using Python's mighty statsmodels library.

BTW - I covered statsmodels in my last two LinkedIn newsletter articles.

I'm betting that the new Copilot in Excel Agent Mode will be able to manipulate worksheets (e.g., generating formulas) directly and will be able to generate forecasts using FORECAST.ETS().

However, I'm also betting the Agent Mode will eventually be smart enough to recognize when a better forecasting technique is available from Python and use that instead.

Which means that the AI-powered future of Microsoft Excel will belong to those professionals who develop Python skills.

Stay healthy and happy data sleuthing!

#Excel #PythonInExcel #MicrosoftExcel

University of Pennsylvania

- Develop and deliver courses based on Generative AI (GenAI) and Large Language Models (LLM 's) to graduate students, faculty, and staff.
- Recommend both new and revised curricula on incorporating other aspects of Artificial Intelligence (AI) to those same groups.
- Provide best practices for learning Artificial Intelligence.

Senior AI Curriculum Advisor 

- Developed curriculum for and teach classes on Artificial Intelligence. 
- Deliver to Graduate School of Education.
- Recruited expert guest lecturer on Generative AI for AI.
- Mentored and consulted students on the use of Artificial Intelligence.

Artificial Intelligence Co-Instructor

The Wharton School

- Provide research direction and mentorship to MBA and undergraduate students.
- Offer peer counseling to fellow graduate students.
- Draft strategy options for review by AI Accountability Institute.

#AI Research Mentor & Peer Advocate

Gartner

Advises clients in strategic challenges with Machine Learning, Artificial Intelligence, and Decision Sciences.  Specializes in areas such as:

- AI Talent/ AI Organization
- Upskilling AI Staff/ AI Literacy
- AI Strategy
- AI Ethics/ Responsible AI
- Measuring AI success
- Maximizing AI profitability
- Model ensembles
- Project management
- Simplifying operations
- Feature engineering
- Data storytelling 
- Working with stakeholders

Director, Data & Analytics/ AI Expert

Analytics-Edge, LLC

•	Created Data Science/ AI curriculum for Cisco Networking Academy: 3.1 million current students, 190 countries, and 6 languages.
•	Developed and delivered the first Data Science curriculum for all of 3M Asia.
•	Created the first Artificial Intelligence course for Harvard Innovation Labs' Experfy spin-off.
•	Provided consulting and training for clients like AARP, Biogen Pharmaceuticals, IBM, Los Angeles Times, Royal Bank of Canada, St. Jude's Children's Research Hospital, T. Rowe Price, and Wells Fargo.

VP- Artificial Intelligence Educator

Booz Allen Hamilton

•	Founded the Strategic Artificial Intelligence Lab (formally Emerging Technologies AI team)
•	Increased VBA Fraud Model Performance by 500% in 8 weeks
•	Lifted sales forecasting model accuracy from 85% to over 91%
•	Raised chatbot satisfaction levels from 27% to over 70%
•	Developed firmwide Introduction to AI training for 10K employees with a 98% approval rate

Lead Artificial Intelligence Solutions Architect

Legg Mason (Acquired by Franklin Templeton)

•	Provided 440% lift in product Cross-Sell performance with breakthrough AI model using champion/ challenger Model Risk Management platform.
•	Slashed Feature Engineering timelines by 80% with CN2 rule induction methodology.
•	Built and tested almost 300 production-ready models using Python, TensorFlow, SageMaker, and various AWS/ pipelines and processes.
•	Designed, authored, and implemented Artificial Intelligence Roadmap for Legg Mason, creating of Strategic Artificial Intelligence Labs.
•	Benchmarked AUM performance, revenue growth, and product performance over 800 separate data elements.
•	Trained over 150 Legg Mason employees on AI methodology across 3 continents.

Lead Data Scientist

Morgan Stanley

•	Designed, created, and implemented a fraud detection model that captured 40% of all fraud within a 2% turndown threshold, outperforming a custom model created by a third-party consulting firm of experts.
•	Developed and executed custom data science training programs for a team of 12 Morgan Stanley employees across two continents.
•	Trained 25 professionals on 2 continents in Machine Learning/ Artificial Intelligence.
•	Implemented custom Python tool to automate Exploratory Data Analysis for all future modeling efforts.
•	Managed a junior executive to become a full Data Scientist in under four months.
•	Wrote and executed Request for Proposal for Anomaly Detection for a $40 billion book of business.

Vice President of Data Science

Various roles 

•	Wide variety of predictive analytics assignments for over 25 clients, including developing almost 100 predictive models for industries such as banking, cellular, healthcare, hospitality, and non-profits.
•	Saved St. Jude Children's Research Hospital approximately 45% on mailing costs using an advanced modeling ensemble approach of an initial filter model, a secondary response model, and a final donation model.
•	Raised Sheraton Hotels’ response rates by more than 50% for destination promotions using advanced analytics to predict direct mail conversion.
•	Built web-based fraud detection models with sub-second decisioning for PayPal, evaluating up to 1 million purchases per day.
•	Created and deployed a unique Customer Analysis Protocol for Alltel Cellular’s marketing division, allowing immediate data mining “triage” for the entire marketing staff. 
•	Chief Data Scientist, Analytics-Edge, 2000 – 2021
•	VP Consumer Lending, Bank of Hawaii, staff of 7, 1997 - 1999
•	VP Credit Cards, CoreStates Bank, $7.8 million budget, staff of 4, 1995 – 1997
•	VP Credit Card Acquisition, Citicorp, Service Excellence Award, 1986 - 1995

Contract Consulting: Vice President of Analytics/ Data Science

81k | Director, Data & Analytics/ AI @ Gartner

#AI pioneer since 1986, currently working with University of Pennsylvania while studying at Harvard GSE. 🥳

Working to make #ArtificialIntelligence friendlier and more ethical!

Provided ROI results for, among others:

- Audi
- Biogen
- Cisco
- Los Angeles Times
- Mercedes
- Morgan Stanley
- Yale University

How may I help YOU??? 🙂

T. Scott Clendaniel

💻 #AI: 𝗦𝘁𝗼𝗽 𝗖𝗼𝗻𝗳𝘂𝘀𝗶𝗻𝗴 𝗨𝘀!

𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝘃𝘀. 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝘃𝘀. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜

Thank heaven for Brij kishore Pandey.  In more ways than one.  In this particular case, we can thank him for brining clarity to the "madness" of why NO ONE in my field can give ANYTHING a normal name.

So here we go.

Generative AI- A prompt goes to a model, which generates a result, such as text, video, or an image.

AI Agents- A goal is established, enabled by a set of code (the "agent"), which utilizes tools to create a final output.

Agentic AI- A process of establishing an objective, which may use one or more sub-agents, leveraging tools and memory, to create a final output.

See?  Brij kishore Pandey saves us again!

#AI #ArtificialIntelligence #Education #GenAI #Training

#AI Education- Transformed for Executives! High ROI, fast results... and learners even think it’s fun!

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