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 data-driven artificial intelligence. We’ll learn about recent trends in AI including machine learning, deep learning, and reinforcement learning. Finally, learn how AI will impact you, your career, and our future.
The AI revolution is here! Artificial Intelligence is radically transforming almost every aspect of our world. However, many of us are still in the Stone Age when it comes to this new set of technologies.
In this session, you’ll learn about Deep Reinforcement Learning, a new type of AI that can teach itself how to solve a variety of problems without any human intervention. It can learn to play video games, drive a car, teach a robot to walk, and much more.
You’ll learn what Deep RL is, why it’s important, and how you can use it to solve common business problems. Expect to learn all this, and more, in a way that’s simple and easy to understand.
Data science is revolutionizing the world around us. We’re incorporating artificial intelligence, machine learning, and data-driven decision making into all aspects of business. However, many software developers have yet to learn how to leverage these practices to create better software.
In this presentation, we’ll learn how expert developers are using data science to create better software. We’ll learn how to use data analytics, machine learning, and anticipatory design to create more intelligent software. In addition, we’ll learn how to use data from our dev-ops pipeline to improve our software development practices.
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.
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.
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.
Data Science is transforming the world around us. This new way of making data-driven decisions is disrupting entire industries and re-inventing the way we do business. However, many organizations are still in the dark when it comes to this valuable new set of skills.
In this session, you will learn what data science is and why it’s so important for your business. In addition, you’ll learn how to get started becoming a data-driven organization.
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.
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.
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.
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.
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.
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.
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.