Developing AI Applications: An Introduction

It’s time to get practical about AI. Move past playing around with chatbots and plugging your data into others’ applications—learn how to create your own! Walk through key AI methods like decision trees, convolutional layers, cluster analysis, and more. Get your hands dirty with simple no-code exercises and then apply that knowledge to more complex (but still beginner-friendly!) examples. With information on installing KNIME and using tools like AutoKeras, ChatGPT, and DALL-E, this guide will let you do more with AI!

• Learn to program your own AI applications—even if you’ve never coded before!
• Get started without code using the KNIME platform and then expand your skills by programming with basic Python
• Work with neural networks, transfer learning, anomaly detection, reinforcement learning, and more

AI Algorithms
Understand the theory and structure behind the most useful AI models and methods and how they can be used to solve problems. Learn about artificial neural networks, anomaly detections, cluster analysis, text and image classification, reinforcement learning, and other algorithms.

Tools and Platforms
Install and use AI platforms like KNIME and Anaconda. See how tools like ChatGPT and libraries like XGBoost can enhance your AI applications.

Practical Exercises
Get step-by-step instructions for creating AI applications, whether you’re implementing them with no code on the KNIME platform or programming them using basic Python.

• Python
• KNIME
• ChatGPT
• DALL-E
• Artificial neural networks (ANN)
• Decision trees
• Convolutional layers
• Transfer learning
• Anomaly detection
• Text and image classification
• Cluster analysis
• Reinforcement learning