Matthew Renze

Presentations

I enjoy speaking in public about software and technology. Below are some of my past and upcoming public speaking events.

Upcoming

Date Topic Event Location
2017-09-25 Data Science with R Microsoft Ignite Orlando, FL
2017-09-26 Machine Learning with R Microsoft Ignite Orlando, FL
2017-09-28 Data Science (Meetup) Microsoft Ignite Orlando, FL
2017-09-28 Data Science: The Big Picture Prairie Code Des Moines, IA
2017-09-29 Deep Learning: The Future of AI Prairie Code Des Moines, IA
2017-10-03 Deep Learning: The Future of AI Microsoft Developers UAE Dubai, UAE
2017-10-04 Data Science: The Big Picture Dubytes Dubai, UAE
2017-10-25 Data Visualization with R IT/Dev Connections San Francisco, CA
2017-10-26 Exploratory Data Analysis with R IT/Dev Connections San Francisco, CA
2017-11-14 Artificial Intelligence: The Future of Software Devoxx Morocco Casablanca, Morocco

Past

Date Topic Event Location
2017-09-19 Data Science: The Big Picture Pluralsight LIVE Salt Lake City, UT
2017-09-19 Deep Learning: The Future of AI Pluralsight LIVE Salt Lake City, UT
2017-08-04 Data Science: The Big Picture KCDC Kansas City, MO
2017-08-03 Machine Learning with R KCDC Kansas City, MO
2017-07-11 Data Science: The Big Picture Detroit Code Detroit, MI
2017-07-11 Machine Learning with R Detroit Code Detroit, MI
2017-06-17 Data Science: The Big Picture Geek Girl TechCon San Diego, CA
2017-06-15 Visual Snow Syndrome University of Iowa Iowa City, IA
2017-06-08 Clean Architecture DevSum Stockholm, Sweden
2017-06-07 Practical Data Science with R DevSum Stockholm, Sweden
2017-05-20 Clean Architecture Nextbuild Eindhoven, Netherlands
2017-05-17 Exploratory Data Analysis with R SDD Conf London, UK
2017-05-18 Clean Code SDD Conf London, UK
2017-05-18 Clean Architecture SDD Conf London, UK
2017-05-11 Data Visualization with R Devoxx UK London, UK
2017-05-05 Visual Snow Syndrome Newcastle University Newcastle, UK
2017-01-26 Clean Code .NET User Group Las Vegas, NV
2017-01-12 The Mindful Developer CodeMash Sandusky, Ohio
2017-01-11 Practical Data Science with R CodeMash Sandusky, Ohio
2016-11-29 Visual Snow Syndrome (Webinar) Newcastle University Newcastle, UK
2016-11-17 Careers in Software Consulting Iowa State University Ames, IA
2016-10-27 Why Agile? Prairie Code Des Moines, IA
2016-10-21 Clean Architecture Dev Up Conference St. Louis, MO
2016-10-20 Practical Data Science with R Dev Up Conference St. Louis, MO
2016-10-12 Clean Architecture IT/Dev Connections Las Vegas, NV
2016-10-11 Why Agile? IT/Dev Connections Las Vegas, NV
2016-10-06 Exploratory Data Analysis with RTVS Visual Studio Live Washington, DC
2016-10-06 Data Visualization with RTVS Visual Studio Live Washington, DC
2016-09-29 Exploratory Data Analysis with RTVS Visual Studio Live Anaheim, CA
2016-09-29 Data Visualization with RTVS Visual Studio Live Anaheim, CA
2016-09-07 Practical Data Science with R AIM | hdc Omaha, NE
2016-08-15 Practical Data Science with R Private Workshop for AIG New York City, NY
2016-08-10 Clean Architecture That Conference Wisconsin Dells, WI
2016-06-22 Practical Data Science with R KCDC Kansas City, MO
2016-06-23 Data Visualization with R KCDC Kansas City, MO
2016-06-16 Visual Snow Syndrome University of Iowa Iowa City, IA
2016-05-18 Practical Data Science with R Nebraska Code Lincoln, NE
2016-05-20 Clean Architecture Nebraska Code Lincoln, NE
2016-04-11 Why Agile? Prairie Dev Con Winnipeg, Canada
2016-04-12 Exploratory Data Analysis with R Prairie Dev Con Winnipeg, Canada
2016-01-14 Exploratory Data Analysis with R NDC Pluralsight Booth London, UK
2016-01-13 Clean Code NDC London London, UK
2016-01-07 Exploratory Data Analysis with R CodeMash Sandusky, OH
2016-01-07 Why Agile? CodeMash Sandusky, OH
2015-12-07 Clean Architecture Iowa .NET User Group Des Moines, IA
2015-12-05 Clean Architecture Iowa Code Camp Des Moines, IA
2015-10-01 Independent Consulting Panel Iowa .NET User Group Des Moines, IA
2015-09-11 Clean Architecture AIM | hdc Omaha, NE
2015-09-11 Exploratory Data Analysis with R AIM | hdc Omaha, NE
2015-06-26 Clean Code KCDC Kansas City, MO
2015-06-25 Exploratory Data Analysis with R KCDC Kansas City, MO
2014-11-06 Careers in Software Consulting Iowa State University Ames, IA
2014-10-21 Exploratory Data Analysis with R DAMA Iowa Chapter Des Moines, IA
2014-08-12 Exploratory Data Analysis with R That Conference Wisconsin Dells, WI
2014-04-22 Introduction to Agile and Scrum Iowa State University Ames, IA
2014-04-05 Why Agile? Twin Cities Code Camp Minneapolis, MN
2014-03-29 Why Agile? Nebraska Code Camp Lincoln, NE
2013-12-12 Careers in Software Consulting Iowa State University Ames, IA
2013-12-05 Clean Code Iowa .NET User Group Des Moines, IA
2013-10-05 Agile Software Requirements Iowa State University Ames, IA
2013-10-02 Exploratory Data Analysis with R Iowa Code Camp Ankeny, IA
2013-10-16 Why Agile? Agile Iowa Des Moines, IA
2013-06-08 Why Agile? Iowa Code Camp Iowa City, IA
2013-06-08 Transforming Data into Knowledge Iowa Code Camp Iowa City, IA
2013-03-16 Exploratory Data Analysis with R Nebraska Code Camp Lincoln, NE
2012-10-15 Agile Software Requirements Iowa State University Ames, IA
2012-10-15 Careers in Software Consulting Iowa State University Ames, IA
2012-10-27 Transforming Data into Knowledge Iowa Code Camp Des Moines, IA
2012-05-03 Careers in Computer Science Perry High School Career Fair Perry, IA

Presentations

Artificial Intelligence

Artificial Intelligence: The Future of Software

In the very near future, AI technologies will radically transform our economy, our society, and our lives. As a result, the software industry is preparing for a major transition as well. However, most developers do not yet possess the skills necessary to remain relevant in our new data-driven economy. In this session, we will learn about modern Artificial Intelligence and why it’s so important to our future. We’ll also learn how a series of modern technologies including The Internet of Things, Big Data, and Machine Learning are combining to create fully autonomous intelligent systems.

Slides | Code

Clean Architecture

Clean Architecture: Patterns, Practices, and Principles

As software grows more complex, we need to manage this complexity by using various architectural patterns, practices, and principles. In this session, we will learn how software experts keep their architecture clean using a new approach to software architecture. We’ll learn about domain-centric architectures, application layers, CQRS (Command-Query Responsibility Separation), event sourcing, microservices, and more. You can expect to hear practical advice and see real-world examples from over 17 years of architectural experience.

Slides | Code

Clean Code

Clean Code: A Reader-Centered Approach

Clean Code is a philosophy of writing code for the reader of the code rather than for the author or for a machine. Writing code that is clean is extremely important because of the high maintenance cost associated with messy code. In this session, you will learn from industry experts what makes code clean. In addition, you will learn how to write reader-centric code that is simple, readable, understandable, maintainable, and testable.

Slides | Video

Data Science: The Big Picture

Data Science: The Big Picture

Data Science is the practice of transforming data into actionable insight. This set of skills is currently in high demand and commanding significant increases in salary, as data science is fundamentally changing the world around us. However, most of us have not yet learned this valuable set of skills.

In this session, you will learn what data science is and why it’s important. In addition, you’ll learn what you need to know to prepare for our new data-driven economy. Expect to learn about the Internet of Things (IoT), Big Data, machine learning, and how they are converging to create fully-autonomous intelligent systems.

Slides

Data Visualization with R

Data Visualization with R

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for creating professional data visualizations. This session will provide an introduction to the R programming language using RStudio. In addition, we will demonstrate how we can use R to create data visualizations to transform our data into actionable insight.

Slides | Code | Video

Deep Learning: The Future of AI

Deep Learning: The Future of AI

Over the past few years there have been a series of breakthroughs in machine learning that have lead to significant increases in AI capabilities. This has lead to several amazing technologies like machines that can drive cars, detect emotions, and diagnose diseases. These advances are largely the result of deep-learning algorithms like deep neural networks.

In this session, we’ll learn what deep learning is and why it is so important to the future of the software industry. We’ll learn about the current capabilities of deep-learning systems and their predicted future capabilities. In addition, we’ll learn about the tools that allow us to create deep-learning models like TensorFlow, Torch, and the Microsoft Cognitive Toolkit.

Slides

Exploratory Data Analysis with R

Exploratory Data Analysis with R

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for exploratory data analysis. This session will provide an introduction to the R programming language using RStudio. In addition, we will demonstrate how we can use R for exploratory data analysis to transform our data into actionable insight.

Slides | Code | Video

Machine Learning with R

R is a very popular open-source programming language for machine learning. Its interactive programming environment and powerful data analysis capabilities make R an ideal tool for machine learning. This session will provide an introduction to the R programming language using RStudio. In addition, we will demonstrate how we can use R to train a series of machine learning models. Finally, we’ll learn how to deploy these models to production to make predictions given new data.

Slides | Code

The Mindful Developer

The Mindful Developer: The Neuroscience of Successful Software Developers

Does your career as a software developer cause you stress? What are you currently doing to manage the negative health effects of this stress? Software developers are uniquely predisposed to certain stress-related mental-health issues. The key problem is that we evolved to survive in a wilderness context. However, these same survival adaptations are now in direct conflict with our modern high-tech world.

In this session, we will learn about the behavioral neuroscience of mindfulness practices. We’ll discuss practices like meditation, biofeedback, cognitive reappraisal, organized skepticism, and egoless programming. In addition, we will learn how we, as software developers, can use these practices to reduce stress, improve our mental health, and increase our focus. There will be NO new-age nonsense, mystical mumbo-jumbo, or quantum flapdoodle in this session… only research-based science… real science… in plain English.

Slides

Practical Data Science with R

Practical Data Science with R (Workshop)

Data science is the practice of transforming data into knowledge. R is the most popular programming language used by data scientists. In our data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary, as it is revolutionizing the world around us.

In this workshop, we'll learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight. In addition, we'll learn how to transform and clean our data, create and interpret descriptive statistics, data visualizations, and statistical models. We'll also learn how to handle Big Data, make predictions using machine learning algorithms, and deploy R to production.

Materials

Transforming Data into Knowledge

Transforming Data into Knowledge

In an information economy, data is the new oil. However, much like crude oil, data must be refined to provide value. This session will provide a high-level overview of the tools we use to transform raw data into actionable knowledge. Topics will span the entire data pipeline including IoT, data warehousing, big data, data analytics, and machine learning.

Slides

Why Agile?

Why Agile? Economics, Psychology, and Science

Most presentations on Agile practices only cover what Agile is and how Agile practices work. However, in this session, we'll discuss why Agile practices like Scrum, TDD, and refactoring are so effective in terms of economics, psychology, and science. In addition, we'll explain the success of Agile practices with insights from various scientific fields including Information Theory, Network Theory, and Systems Theory. Whether you're still unsold on the value of Agile, actively practicing Agile, or need to convince others of the value of Agile, this presentation is for you.

Slides | Video