Your Path to AI and Data Literacy

Did you know that 47% of leaders point to AI literacy as one of the fastest-growing skills they need from their teams? But as shown in DataCamp’s 2025 report, AI and data literacy go hand-in-hand and you need both to succeed.

Data literacy is the ability to read, work with, analyze, interpret, and communicate with data. AI literacy builds on this by adding the ability to understand AI concepts, work with AI tools, and explain AI outcomes — so you can analyze, build, and trust AI-driven systems.

Together, AI and data literacy enable professionals to work confidently with data and integrate AI into their data work, no matter their background or industry.

At KNIME, we’re making it easier for anyone to build these skills with our free, open-source platform. No matter if you’re new to the field or looking to advance your expertise, our learning paths, tools, and resources are built for practical, hands-on learning.

“We at DataCamp were lucky enough to partner with KNIME on their first curriculum to prepare learners for L1 Certification on KNIME. Being able to explore new opportunities, thinking about what’s next and how our relationship can continue to evolve has been a lovely time.” Carl Rosseel, Director of Education Partnerships, DataCamp

Whether you’re new to working with data or looking to advance your skills in AI and data literacy, this article shows:

• Why learning AI and data literacy skills with an open source data science tool like KNIME Analytics Platform makes learning easier and more accessible
• Information about learning paths for data analysts, data scientists, data engineers, educators, and trainers
• Additional (and fun) learning resources

To gain AI and data literacy skills you need to be able to apply your knowledge and understanding to actual data. The main obstacle to gaining AI and data literacy is how user-friendly the tool is. Coding-based tools, for example, require an extra step to learn to code before these skills can be acquired. 

KNIME Analytics Platform is a free, open-source software that lets you build data science and AI workflows using a visual, code-free interface. Instead of writing lines of code, you use modular building blocks (“nodes”) to access, blend, analyze, and visualize data — step-by-step.

KNIME’s visual workflows make each part of your analysis easy to follow — from reading in the data, to cleaning, analyzing, and visualizing it. You can see exactly what happens to your data at each step.

This visual approach makes it easier for beginners to get started; at the same time, the platform provides connectors to 300+ data sources, integrations with advanced tools like AI, cloud services, scripting languages like Python or R, and all the popular machine learning libraries — that advanced users need. And it's continually evolving. 

K-AI is KNIME’s AI assistant. It acts as an on-demand tutor, providing immediate assistance, which can accelerate the learning process for users of all skill levels.

If you get stuck, you can ask K-AI questions about KNIME functionality, get it to suggest what you need for specific data analysis tasks, and help you to select the best tools for your analysis. It can even auto-generate entire workflows

As an open source tool, KNIME is backed by a huge community of users, contributors, and educators who you can connect with to ask questions, get feedback, and learn from. The open source model doesn't just make learning accessible to anyone, the learning experience is also collaborative and constantly improving. That’s a great environment for learning.

It doesn’t matter if you’re just starting out or wanting to refine advanced workflows, you can connect with others and learn directly from peers, developers, and data science professionals on the KNIME Forum.

The Forum is your place to go for technical support, to meet and exchange ideas with other members of the community online, or tell us your feedback or give us ideas. The feedback and ideas category also includes the ability to vote up a piece of feedback or an idea you think is particularly important. This helps the KNIME team to understand better what the community wants.

In addition to exploring the KNIME Forum for help with any software questions, you’ll also find special interest groups there.

• If you prefer to chat on the Forum in your native language, you’ll find groups there in French, Spanish, Italian, Turkish, and Portuguese.
• If you’re an educator, you can go there to join in discussions with peers about teaching with KNIME.
• If you want to find out about events, knowledge-sharing, courses, or announcements, you can check out the Resources category.

When you’re starting to learn a new skill, it helps if you can access pre-built templates or examples that are relevant to your work or research topic so you don’t have to start from scratch each time.

The KNIME Community Hub is a free, open-access platform where you can discover, download, and share data science and AI workflows. You can explore solutions built by the KNIME team and the global community. Using these pre-built examples, you can learn step-by-step, by reverse-engineering them, and adapting them to your own projects.

You can search for examples by topic, look for entire workflows, or just nodes. Each workflow includes an explanation of what it does, a list of all the nodes it includes, plus links to any documentation or blog posts on the same topic.

Users of open platforms frequently share their latest tools and learnings. That means you’ll get quick access to the latest technologies and can start learning how to use them. KNIME Analytics Platform evolves continuously through community feedback and open collaboration, expanding core functionality with features the community wants.

While core functionality is developed in-house, data scientists and developers from the KNIME community regularly add new features and tech, from industry-specific to sophisticated scientific software integrations. KNIME Community Extensions are a treasure trove of functionality. 

They provide additional functionality you might need, such as access to and processing of complex data types, or the addition of advanced machine learning algorithms.

Openness extends beyond open source code! KNIME’s team and the community regularly share best practices, workflows, and new approaches.

✅ Browse blog posts for insights from thought leaders in data science and AI, and learn how other people are solving data problems with KNIME. Explore the Food for Thought category on the blog for candid remarks and articles about data strategy and data literacy.

✅ Join events online and in-person to network with your peers and learn from keynote speakers and industry leaders.

✅ Learn about best practices by exploring the KNIME Community Hub for 1000s of example solutions to download and use yourself.

✅ Take an instructor-led or free self-paced online courses to upskill yourself.

KNIME courses and certifications cover the most important data and AI skills leaders need from their teams, such as data analysis and manipulation, the skills to build visualizations and dashboards, understand AI concepts, and how to integrate your data and AI reliably. 

The course designers at KNIME understand that different people have different learning needs and preferences, and offer training as self-paced or instructor-led courses, learnathons, onsite hands-on workshops, plus learning resources such as videos, ebooks, cheat sheets, blog articles, and more.

In the KNIME Learning Center, you’ll find a variety of free, self-paced courses covering everything from data wrangling to machine learning and generative AI.

Courses are organized into levels from gaining basic to advanced data literacy and workflow building skills, productionizing data applications, and specializations in data science and AI. You can choose from different learning paths, depending on whether you’re interested in data analytics, data science, data engineering, or teaching KNIME.

If you're working with spreadsheets, dashboards, or reports  — and want to level up your data literacy and automation skills  — the Data Analyst path is a great place to start.

Recommended courses:

These courses start with the basics of workflow building with KNIME and move on to teach you how to create and productionize data apps. The courses are available as free self-paced online courses, or as instructor-led online courses.

• L1-AP: Data Literacy with KNIME Analytics Platform: Basics
• L2.DA: Data Analytics with KNIME Analytics Platform: Advanced
• L3-DA: Productionizing Data Apps
• L4-DA: Data Analytics and Visualization: Specialization

Skills gained:

• Access, blend, clean, and transform data from different sources
• Automate repetitive tasks and visualize insights with dashboards or reports
• Productionize data applications and share with others to consume
• Utilize advanced data extraction and visualization techniques

Find more detailed descriptions about these courses in the KNIME Learning Center.

Learning resources:

• Find out about How to Prepare for the KNIME L1 Certification Exam 
• Keep the Building a KNIME workflow for Beginners cheat sheet handy
• Refer to the Data Visualization cheat sheet for a summary of key functionality
• Need to look up terminology? Bookmark our data science glossary

Next steps:

• Get your new skills certified by the KNIME Certification Program

For professionals looking to build predictive models, perform AI-driven analysis, or automate decision-making, the Data Scientist path focuses on analytics, machine learning, and model deployment.

Recommended courses:

The courses for data scientists begin with workflow building in KNIME and progress to teach how to build, train, and productionize machine learning models. The courses are available as free self-paced online courses, or as instructor-led online courses.

• L1-AP Data Literacy with KNIME Analytics Platform: Basics
• L2-DS Data Science with KNIME Analytics Platform: Advanced
• L3-CD Continuous Deployment and MLOps
• L4-Specialization in either Machine Learning, Deep Learning, Time Series Analysis, Text Processing, or Chemical Data

Skills gained:

• Access, blend, clean, and transform data from different sources
• Automate repetitive tasks and build simple machine learning models
• Productionize your machine learning models with MLOps 
• Specialize in either machine learning, deep learning, NLP, or time series analysis

Find more detailed descriptions about all the courses in the KNIME Learning Center.

Learning resources:

• Find more detailed explanations of the courses about data science productionization and MLOps techniques 
• Find out how you can prepare for the L3 Productionization exam
• Learn more about the topics covered by the L4 Deep Learning exam and how you can prepare
• Find out how you can prepare for the L4 Text Processing exam
• Bookmark the GenAI with KNIME cheat sheet as a handy reference on prompting, LLMs, RAG systems, and more

Next steps:

• Get your new skills certified by the KNIME Certification Program

If you're responsible for managing data pipelines, building infrastructure, or enabling data access across teams, the Data Engineer path offers the tools and techniques to manage complexity and scale.

Recommended courses:

These courses start with basic workflow building in KNIME and advance to teach you how to build, orchestrate, and productionize data pipelines

• L1-AP Data Literacy with KNIME Analytics Platform: Basics
• L2-DE Data Engineering with KNIME Analytics Platform: Advanced
• L3-DE Productionizing Data Pipelines
• L4-DE Data Engineering: Specialization

Skills gained:

• Access, blend, clean, and transform data from different sources
• Automate repetitive tasks and orchestrate pipelines with different data structures 
• Productionize data pipelines to share with others
• Employ best practices for data engineering

Find more detailed descriptions about all the courses in the KNIME Learning Center.

Learning resources:

• Bookmark the Control and Orchestration cheat sheet to reference key functionality quickly
• Use the Data Wrangling cheat sheet to reference the key functionality to access data

Next steps:

• Get your new skills certified by the KNIME Certification Program

Are you an instructor, team lead, or educator helping others learn data literacy and AI skills? KNIME provides resources to support you in delivering workshops, courses, or internal training.

Recommended resources for educators:

• KNIME Educators Alliance: Join a global network of trainers and professors using KNIME in the classroom. Access shared teaching modules and contribute to community knowledge.

Tools for educators – available through the Educators Alliance:

• Slide decks, datasets, and exercises
• Certification exam preparation materials
• Forum for trainers to exchange ideas

Next steps: Become a member of the Educators Alliance to access all resources.

Recommended resources for trainers

• Train the Trainer Program: Prepare to become a  KNIME Certified Trainer Learn instructional design strategies, tools, and best practices, and get feedback from KNIMErs in a practical workshop in preparation for your teaching evaluation.
• See the list of current KNIME certified trainers.

Next steps: Become a Certified KNIME Trainer and help others build data literacy and AI skills in your organization or classroom.

Upskill your AI and data literacy with the learning provider you prefer. For example, you’ll also find courses and webinars about AI and data science with KNIME on the online learning platforms DataCamp and LinkedIn Learning. Read more on KNIME Learning Center Partners. 

One of the best ways to build confidence when you’re learning new skills is through practice. KNIME offers a series of hands-on challenges and events to make learning interactive, goal-oriented, and fun.

The Just KNIME It! challenge is a guided, themed learning experience that takes place over several weeks. It challenges all types of users to solve a new task each week using KNIME. The tasks are rooted in real-world problems from different fields, such as finance, marketing, or healthcare, and come in difficulty levels from easy, to medium, to hard. You can slowly make your way through them as you get more confident in your skills.

The challenge is ideal for beginners and intermediate users looking to reinforce their understanding of AI techniques and workflow design.

Learn more about Just KNIME It!

The Game of Nodes is a KNIME workflow world tournament where teams tackle data analytics challenges to compete for the Golden Node. The challenges cover topics from training predictive models, to web scraping, to designing GenAI solutions, to plotting geospatial maps, and more. Anyone can join. We recommend L2 course proficiency in building workflows.

Get certified in AI and data literacy for free within 90 days. During the 90 days of the challenge, you can take any KNIME Certification Exam free of charge. It’s a great way to kickstart your learning path, build core data literacy skills, and demonstrate your progress with official KNIME certifications.

The challenges and learnathons are designed to help you move from learning concepts to applying them  step by step. Whether you’re learning on your own, or part of a team, they provide a clear path to becoming confident in your use of KNIME for data and AI projects.

Look out for announcements about certification challenges in the Take the 90-day challenge news article.Learn from experts at AI and data literacy events

KNIME webinars come in different flavors to serve different learning needs:

For practitioners: Technical demos and deep dives with data scientists from KNIME and the community. 

These webinars are typically 45 minutes, and range from providing beginner-friendly through to in-depth walkthroughs of techniques to build your AI and data literacy skills. Each webinar includes time at the end for you to ask all your questions. 

For business users: Real-world use cases from teams building data- and AI-powered solutions.

These webinars show how organizations and departments are using data science to become more data-driven. Attend these webinars to get inspired by high-level overviews of how teams are building AI and data science solutions, and see how you could adopt similar solutions in your own work.

Look out for new webinars and catch up on previous events on KNIME Events.

Working with data doesn’t need to be overwhelming. KNIME removes the barriers with a free, open source platform, visual workflows, guided learning paths, and a global community of support