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EITCA Academy

EITCA Academy

The European Information Technologies Certification Institute - EITCI ASBL

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EITCI Institute ASBL

Brussels, European Union

Governing European IT Certification (EITC) framework in support of the IT professionalism and Digital Society

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Questions and answers designated by tag: Data Science

What is the simplest route to most basic didactic AI model training and deployment on Google AI Platform using a free tier/trial using a GUI console in a step-by-step manner for an absolute begginer with no programming background?

Sunday, 11 May 2025 by EITCA Academy

To begin training and deploying a basic AI model using the Google AI Platform via the web-based GUI, especially as an absolute beginner with no programming background, it is advisable to use Google Cloud’s Vertex AI Workbench and AutoML (now part of Vertex AI) features. These tools are specifically designed for users without coding experience

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, Plain and simple estimators
Tagged under: Artificial Intelligence, AutoML, Cloud Storage, Data Science, No-Code ML, Vertex AI

What are the main requirements and the simplest methods for creating a natural language processing model? How can one create such a model using available tools?

Sunday, 11 May 2025 by Mohammed Khaled

Creating a natural language model involves a multi-step process that combines linguistic theory, computational methods, data engineering, and machine learning best practices. The requirements, methodologies, and tools available today provide a flexible environment for experimentation and deployment, especially on platforms like Google Cloud. The following explanation addresses the main requirements, the simplest methods for natural

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Further steps in Machine Learning, Natural language generation
Tagged under: Artificial Intelligence, Data Science, Google Cloud, Jupyter Notebook, Machine Learning, Model Deployment, Neural Networks, NLP

How to limit bias and discrimination in machine learning models?

Sunday, 04 May 2025 by Michał Bodura

To effectively limit bias and discrimination in machine learning models, it is essential to adopt a multi-faceted approach that encompasses the entire machine learning lifecycle, from data collection to model deployment and monitoring. Bias in machine learning can arise from various sources, including biased data, model assumptions, and the algorithms themselves. Addressing these biases requires

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Artificial Intelligence, Bias Mitigation, Data Science, Ethics, Fairness, Machine Learning

How essential is Python or other programming language knowledge to implement ML in practice?

Friday, 25 April 2025 by Jakub Šváb

To address the question of how necessary Python or any other programming language knowledge is for implementing machine learning (ML) in practice, it is vital to understand the role programming plays in the broader context of machine learning and artificial intelligence (AI). Machine learning, a subset of AI, involves the development of algorithms that allow

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Artificial Intelligence, Cloud Computing, Data Science, Machine Learning, Programming Languages, Python

How does one know which ML model to use, prior to training it?

Tuesday, 15 April 2025 by Mafalda Paes de Carvalho

Selecting the appropriate machine learning model before training is an essential step in the development of a successful AI system. The choice of model can significantly affect the performance, accuracy, and efficiency of the solution. To make an informed decision, one must consider several factors, including the nature of the data, the problem type, computational

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Artificial Intelligence, Data Science, Machine Learning, Model Selection, Supervised Learning, Unsupervised Learning

How to apply the 7 steps of ML in an example context?

Sunday, 23 February 2025 by Ana Abade

Applying the seven steps of machine learning provides a structured approach to developing machine learning models, ensuring a systematic process that can be followed from problem definition to deployment. This framework is beneficial for both beginners and experienced practitioners, as it helps in organizing the workflow and ensuring that no critical step is overlooked. Here,

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, The 7 steps of machine learning
Tagged under: Artificial Intelligence, Data Science, Google Cloud, Machine Learning, Model Deployment, Regression Analysis

Why were AutoML Tables discontinued and what succeeds them?

Friday, 21 February 2025 by Vanhaeren

Google Cloud's AutoML Tables was a service designed to enable users to automatically build and deploy machine learning models on structured data. AutoML Tables were not discontinued in a traditional sense, their capabilities were fully integrated into Vertex AI. This service was a part of Google's broader AutoML suite, which aimed to democratize access to

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Expertise in Machine Learning, AutoML Tables
Tagged under: Artificial Intelligence, Data Science, Google Cloud, Machine Learning, MLOps, Vertex AI

When the reading materials speak about "choosing the right algorithm", does it mean that basically all possible algorithms already exist? How do we know that an algorithm is the "right" one for a specific problem?

Tuesday, 11 February 2025 by M.L. SAVI

When discussing "choosing the right algorithm" in the context of machine learning, particularly within the framework of Artificial Intelligence as provided by platforms like Google Cloud Machine Learning, it is important to understand that this choice is both a strategic and technical decision. It is not merely about selecting from a pre-existing list of algorithms

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Algorithms, Artificial Intelligence, Data Science, Machine Learning, Model Selection, Neural Networks

What are the rules of thumb for adopting a specific machine learning strategy and model?

Friday, 17 January 2025 by Alberto Della Libera

When considering adoption of a specific strategy in the field of machine learning, particularly when utilizing deep neural networks and estimators within the Google Cloud Machine Learning environment, several foundational rules of thumb and parameters should be considered. These guidelines help determine the appropriateness and potential success of a chosen model or strategy, ensuring that

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, Deep neural networks and estimators
Tagged under: Artificial Intelligence, Data Science, Google Cloud, Machine Learning, Model Selection, Neural Networks

How long does it usually take to learn the basics of machine learning?

Friday, 10 January 2025 by Karol Siegmuller

Learning the basics of machine learning is a multifaceted endeavor that varies significantly depending on several factors, including the learner's prior experience with programming, mathematics, and statistics, as well as the intensity and depth of the study program. Typically, individuals can expect to spend anywhere from a few weeks to several months acquiring a foundational

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Artificial Intelligence, Data Science, Google Cloud, Linear Algebra, Machine Learning, Python, Reinforcement Learning, Statistics, Supervised Learning, TensorFlow, Unsupervised Learning
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EITCA Academy is a part of the European IT Certification framework

The European IT Certification framework has been established in 2008 as a Europe based and vendor independent standard in widely accessible online certification of digital skills and competencies in many areas of professional digital specializations. The EITC framework is governed by the European IT Certification Institute (EITCI), a non-profit certification authority supporting information society growth and bridging the digital skills gap in the EU.

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