Romeo Kienzler

Romeo Kienzler holds a M. Sc. (ETH) in Information Systems, Bioinformatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.

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Data Engineering and Machine Learning using Spark (Coursera)

Jan 31st 2022
Data Engineering and Machine Learning using Spark (Coursera)
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Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others. In this short course [...]
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Advanced Data Science Capstone (Coursera)

Jan 31st 2022
Advanced Data Science Capstone (Coursera)
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This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and [...]
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Advanced Machine Learning and Signal Processing (Coursera)

Jan 31st 2022
Advanced Machine Learning and Signal Processing (Coursera)
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This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about [...]
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Fundamentals of Scalable Data Science (Coursera)

Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU [...]
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Applied AI with DeepLearning (Coursera)

This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other [...]
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Tools for Data Science (Coursera)

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages [...]
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Building Deep Learning Models with TensorFlow (Coursera)

Jan 24th 2022
Building Deep Learning Models with TensorFlow (Coursera)
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The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply [...]
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Scalable Machine Learning on Big Data using Apache Spark (Coursera)

Jan 24th 2022
Scalable Machine Learning on Big Data using Apache Spark (Coursera)
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This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark. Most real world machine learning work involves very large data sets that go beyond the CPU, memory and storage limitations of a single computer. Apache [...]
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Apache Spark for Data Engineering and Machine Learning (edX)

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Apache Spark for Data Engineering and Machine Learning (edX)
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This short course introduces you to the fundamentals of Data Engineering and Machine Learning with Apache Spark, including Spark Structured Streaming, ETL for Machine Learning (ML) Pipelines, and Spark ML. By the end of the course, you will have hands-on experience applying Spark skills to ETL and ML [...]
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Data Science Tools (edX)

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Data Science Tools (edX)
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Learn about the most popular data science tools, including how to use them and what their features are. In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can [...]
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