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Learner Reviews & Feedback for Code Free Data Science by University of California San Diego

4.3
stars
201 ratings

About the Course

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data. Predicting future trends and behaviors allows for proactive, data-driven decisions. During the class learners will acquire new skills to apply predictive algorithms to real data, evaluate, validate and interpret the results without any pre requisites for any kind of programming. Participants will gain the essential skills to design, build, verify and test predictive models. You Will Learn • How to design Data Science workflows without any programming involved • Essential Data Science skills to design, build, test and evaluate predictive models • Data Manipulation, preparation and Classification and clustering methods • Ways to apply Data Science algorithms to real data and evaluate and interpret the results...

Top reviews

BS

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A lot of extra work must be done to reformat data examples into useful docs. Sometimes the courses require you to look ahead in order to obtain the tools needed for a quiz.

TU

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Knime is the good way to better understand in Data Science

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51 - 58 of 58 Reviews for Code Free Data Science

By Thana U

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Mar 13, 2022

Knime is the good way to better understand in Data Science

By Jeevan A

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Nov 19, 2020

Very clearly explains the basics of using KNIME.

By Surya P S

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Jan 30, 2022

Great Course....simple and clear content...

By kinshuk

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Jun 16, 2021

it was a good and fun course

By ALBERTO C C

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Apr 18, 2023

Es un curso muy básico para personas que no tengan experiencia en programación ni análisis de datos. Está estructurado en 4 módulos. El primero de ellos está orientado a mentalizar de la importancia del Big Data y las principales dificultades. El segundo de ellos permite iniciarse en la herramienta visual KNIME, en mi opinión lo más interesante del curso. El tercer módulo introduce conceptos de manipulación y visualización básicos (filtrar columnas, filas, recodificación de columnas, gráficos, etc.). El último módulo introduce algunas técnicas de Machine Learning como árboles y K-means.

En general me parece que algunos de los documentos (especialmente algunos del primer módulo) que recomienda leer son prescindibles y lo interesante de los mismos lo cuenta en los vídeos que son de menor duración y permiten un aprendizaje más eficiente. Tampoco están bien calibrados los tiempos estimados ya que una de las lecturas es un capítulo de 88 páginas de un libro y estima que se lee en 45 minutos.

Sólo lo recomendaría a alguien que no esté acostumbrado a tratar datos o el módulo 3 a alguien que quiera iniciarse en una herramienta visual que no necesite codificación.

By Raja S T N

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Jun 6, 2024

There are several missing connections across many lecture videos. Some of the undiscussed Nodes of KNIME are directly used in follow up video making it difficult to follow the examples. Moreover, the demonstration of concepts felt more like just reading through the slides. things to improve: 1. always maintain same context or examples for demonstrating the concepts from video to video to help learner follow the concepts and practice 2. make the examples in the video available for download including the lecture slides 3. take it with moderate pace. Don't just read the text on slide. it might just loose the focus of the learner. somehow bring in interactive mode

By Benjamin P

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Feb 24, 2020

good course to get an overall introduction, but content is shown very fast and there is a lot of reading material.

By Evren T

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Sep 29, 2020

Everything more complicated, no one look at discussion forum