Search result for Courses taught by Romeo Kienzler
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Data Science Tools
by Romeo Kienzler , Svetlana Levitan , Maureen McElaney- 0.0
7 Weeks
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. This hands-on course will get you up and running with some of the latest and greatest data science tools....
$99
Herramientas de ciencia de datos: uso práctico
by Romeo Kienzler , Svetlana Levitan , Maureen McElaney- 0.0
7 Weeks
Obtén información sobre las herramientas de ciencia de datos más populares (Jupyter Notebooks, RStudio IDE y Watson Studio), aprenderás cómo usarlas y cuáles son sus características. En este curso, aprenderás sobre las herramientas de ciencia de datos como Jupyter Notebooks, RStudio IDE y Watson Studio. ● ● Cómo usar Notebook Jupyter, incluidas sus características y por qué es tan popular...
$39
Tools for Data Science
by Aije Egwaikhide , Svetlana Levitan , Romeo Kienzler- 4.5
Approx. 17 hours to complete
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, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations....
Scalable Machine Learning on Big Data using Apache Spark
by Romeo Kienzler- 3.8
Approx. 7 hours to complete
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. After completing this course, you will be able to:...
Advanced Machine Learning and Signal Processing
by Romeo Kienzler , Nikolay Manchev- 4.5
Approx. 27 hours to complete
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. So you are actually working on a self-created, real dataset throughout the course....
Building Deep Learning Models with TensorFlow
by Samaya Madhavan , JEREMY NILMEIER , Romeo Kienzler , Alex Aklson- 4.4
Approx. 13 hours to complete
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. Learning Outcomes: After completing this course, learners will be able to:...
Advanced Data Science Capstone
by Romeo Kienzler- 4.6
Approx. 9 hours to complete
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 technologies and how they impact model performance and scalability....
Herramientas para la ciencia de datos
by Romeo Kienzler , Svetlana Levitan- 4.4
Approx. 16 hours to complete
¿Cuáles son algunas de las herramientas de ciencia de datos más populares, cómo las usa y cuáles son sus características? En este curso, aprenderá sobre Jupyter Notebooks, RStudio IDE, Apache Zeppelin y Data Science Experience. Aprenderá para qué se utiliza cada herramienta, qué lenguajes de programación pueden ejecutar, sus características y limitaciones....
Fundamentals of Scalable Data Science
by Romeo Kienzler- 4.3
Approx. 20 hours to complete
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. In this course we teach you the fundamentals of Apache Spark using python and pyspark. Through this exercise you'll also be introduced to the most fundamental statistical measures and data visualization technologies....
Applied AI with DeepLearning
by Romeo Kienzler , Niketan Pansare , Tom Hanlon , Max Pumperla , Ilja Rasin- 4.4
Approx. 24 hours to complete
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML....