Free AI Courses: Learn to Build Smarter, Safer Workflows – No Coding Required

AI is reshaping data science—not by replacing it, but by accelerating and expanding how we work.

From cleaning data and generating code to summarizing results or querying in plain English, AI now supports many stages of the data science workflow. With generative and agentic AI, we’re moving from manual steps to intelligent systems that can automate entire workflows and help us move faster.

This shift brings a new responsibility: trust.

AI models—especially generative ones—can produce results that look convincing but may be wrong, biased, or hard to explain. Evaluating trustworthiness is now a core part of every AI-supported project. It’s not just about performance—it’s about knowing when to trust the output, and when to ask more questions.

That’s why we’ve created a new series of three 30-minute online AI courses designed to give you a better understanding of GenAI and Agentic AI concepts so that you can start augmenting your analytics with AI safely.

The courses are for people who are already familiar with KNIME and want to start integrating AI into their workflows. All you need to get started for free is a KNIME account (create one here).

If you’re not yet using the open source KNIME Analytics Platform, you can download it here. You can find online courses to get you started with KNIME in the KNIME Learning Center. 

Here’s a closer look at the AI courses, what each course offers, and what you’ll be able to do once you complete them.

Learn how to bring GenAI directly into your KNIME workflow. This course gives you a clear path to start enriching your analytics with Large Language Models (LLMs) and automate processes.

This course is ideal if you’re just beginning to explore AI but want to apply it in a practical way to your day-to-day analytics.

Key learnings:

• Understand what LLMs are, their limitations and applications in data analytics
• Authenticate, connect, and prompt LLMs inside KNIME
• Apply techniques to control and optimize the LLM’s responses

You’ll finish with an introductory knowledge of LLMs—and earn a microcredential to show it.

Discover how to start developing AI chatbots and enrich your LLM workflows with Retrieval-Augmented Generation (RAG) pipelines. You’ll learn how to bring in custom data and implement governance strategies to ensure ethical, secure, and trustworthy AI use. All without code.

This course is ideal if you want to go beyond experimentation and start building AI applications you can trust.

Key learnings:

• Understand the fundamentals of AI chatbots and start building them with KNIME
• Recognize the limitations of LLMs and learn techniques to overcome them
• Design and implement RAG systems to integrate your own data into LLM workflows
• Identify risks like bias, hallucinations, data privacy breaches, etc. associated with LLMs and apply governance strategies to ensure responsible use of GenAI

Get hands-on with one of the most exciting fields of AI right now: agentic systems. This course shows you how to build autonomous agents that use tools to solve complex tasks, using your own data.

This course is ideal if you're ready to explore the next level of AI automation and want to build smart, autonomous systems with full data context—again, all without coding.

Key learnings:

• Understand the buildings blocks of agentic AI
• Understand the process of how an agent solves a task
• Build tools that follow the requirements of an agentic AI framework
• Implement agents in KNIME Analytics Platform

Here’s what some previous course attendees have said:

Find more reviews of the course: Access course: GenAI & Data Workflows – Getting Started

Find more reviews of the course: Access course: AI Chatbots, RAG, & Governance with Data Workflows – Getting Started

Find more reviews of the course: Access course: Data-Aware Agentic AI – Getting Started