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Take the new KNIME L4 Deep Learning exam

August 22, 2023
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Take the L4-DL exam for free with the promo code: L4-DL-Release. The code is valid until December 31, 2023.

AI is the cool kid! From generating images, to creating human-like conversations, to self-driving cars, there’s not much it can’t do.

But AI wouldn’t be the cool kid without deep learning.

As an advanced subset of machine learning, deep learning drives many AI applications and services. Since the early 1950s, when the perceptron and the first artificial multilayer perceptrons were introduced, deep learning architectures have come a long way. As machines’ computational power, speed and capacity have continuously increased, so has the depth of neural architectures and the complexity of the tasks. A few remarkable examples include RNNs with LSTM units for text generation and time series forecasting; CNNs for image classification and styling; autoencoders to learn efficient codings of unlabeled data; and GANs for synthetic image generation.

The complexity of deep learning has cultivated the myth that building deep learning applications requires equally complex coding in scripting languages – where packages such as TensorFlow and Keras can be leveraged.

Low-code, no-code tools like KNIME Analytics Platform debunk this myth by removing the coding barrier and offering a friendly UI for no-code/low-code deep learning pipelines. You can learn about codeless deep learning in KNIME’s L4-DL self-paced course. And now you can validate this knowledge with the new L4-Deep Learning certification exam and complete the learning path on Deep Learning for data scientists. The L4-DL exam was developed in collaboration with Erez Ben-Moshe, Nathaniel Shimoni, who are lecturers at the Reichman University and Ben-Gurion University of the Negev respectively, and Kathrin Melcher, who is a KNIME expert and trainer, and co-authored the book, Codeless Deep Learning with KNIME.

Fig. 1. A codeless KNIME workflow for deep learning

Lately, the need for ever accurate and multipurpose models has led to the proliferation of transformer-based LLMs. These models have billions of parameters and are the result of a long, and data & resource-intensive training process. In 2018, Google’s BERT, achieved SOTA performance in multiple NLU benchmarks. Similarly, in 2023, OpenAI’s GPT-3 and GPT-4 have taken the data science community by storm, becoming the go-to solution for people seeking answers to all sorts of questions, from homework assignments, to code snippets, or just to satisfy curiosity.

KNIME also integrates AI capabilities to help users build KNIME workflows. You can read more about KAI, the artificial chat assistant on What's New in the 5.1 release.

Who can take the L4-DL certification?

Essentially, anyone can take the L4-DL certification – no coding skills are required. You only need to have passed the L1-L3 certification exam.

The L1 certification verifies your fundamental knowledge of data science and analytics using KNIME Analytics Platform. In L2, the focus is on the advanced functionality of KNIME Analytics Platform to create data science applications. The aim of the L3 certification is to validate your knowledge of productionization procedures for data science applications.

The L4-DL certification exam appears in the KNIME LearnUpon store for purchase as soon as you’ve completed the first three levels of certification. When you pass the L4-DL certification exam, you will receive a badge that recognizes your technical skills, which you can share on social media.

Fig. 2 The KNIME badge you get when you pass the L4 deep learning certification exam

What topics does the L4 deep learning exam cover?

The L4-DL certification exam tests your knowledge of:

  • General deep learning concepts

  • Feed-forward neural networks

  • Loss and activation functions

  • Avoiding Overfitting

  • Autoencoders

  • Preprocessing of data for different deep learning applications

  • Recurrent neural networks and sequential data

  • Convolutional neural networks and image data

Note that transformer-based models and LLMs are beyond the scope of the current exam. However, if you are interested in exploring how you can use Google's BERT or consume LLMs in KNIME Analytics Platforms, find more information and download the Redfield BERT Nodes and the KNIME AI extensions, respectively.

Find more information about all certification exams on the KNIME Certification Program page.

How to prepare for the L4 deep learning exam?

The L4-DL self-paced course prepares you for the certification exam. Simply sign in to your KNIME account on LearnUpon and search in the catalog or enroll yourself in the L4-DL Introduction to Deep Learning course through the KNIME Self-Paced Courses webpage.

Fig. 3 Information about the KNIME L4 Deep Learning certification exam

Alternatively, check out the online courses schedule on the KNIME website to see when the next online instructor-led course will take place.

For learners who like reading, the “Codeless Deep Learning with KNIME” is a comprehensive handbook to build, train, and execute various deep neural network architectures using KNIME.

Complete your learning path as a data scientist with deep learning expertise

Good news, when you pass the L4-DL Certification Exam you’ll have completed the Deep Learning learning path for data scientists. This means that you receive an additional badge that validates your specialized deep learning skills.

Fig. 4. The KNIME learning path badge for data scientists with a specialization in deep learning

Share the badge on social media to demonstrate your skills in deep learning with the low-code, no-code KNIME Analytics Platform.


by Roberto Cadili
Roberto is a data scientist on the Evangelism team at KNIME. After completing his Master’s degree in Linguistics and Translation Studies in Italy, he moved to Germany to start a new Bachelor’s degree in Economics and developed a genuine interest in statistics and data analysis. At the University of Konstanz he pursued a Master’s degree in Social and Economic Data Science where he studied different machine learning algorithms and deep learning architectures with an emphasis on Natural Language Processing.
by Schalk Gerber
Schalk Gerber is a curriculum designer on the Evangelism team at KNIME. As a certified instructional designer, he is involved in various aspects of course design, content creation, and certification. With more than 10 years of experience in teaching business ethics and facilitating difficult discussions on topics like sustainability, inequality, and ethical leadership, he now focuses on ‘how’ to communicate the ‘what’ of data literacy to various audiences. He holds a Ph.D. in philosophy on ethics in a joint program from the Vrije Universiteit Amsterdam and Stellenbosch University.
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