Presentations - Matthew Renze

Matthew Renze

Presentations

Artificial Intelligence

Artificial Intelligence: The Future of Software

Whether you realize it or not, we are currently entering the era of artificial intelligence. 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. We'll learn why it’s important and how it will impact you, your career, and 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

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 | 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 | Video
The Mindful Developer

The Mindful Developer: The Science of Stress Management

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 | Video

Archived Talks

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 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

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

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