Buscadores MOOCs y Libros. Business Analytics. Big Data. Data Mining. GeoData. Repositorios de datos. Visualization. RamiKrispin/vscode-python: Setting Python Development Environment with VScode and Docker. Aqsa Z. on LinkedIn: #sql #sqldeveloper #sqlserver #sqldatabase #datascience #machinelearning… RamiKrispin/awesome-ds-setting: Data science setting for a new machine. [2023] 700+ Free Google Certifications. From Gmail to Maps, Google offers a ton of useful apps. For instance, this article was originally drafted on Google Docs, like most of our articles at Class Central. What many people don’t know is that Google also offers many online courses — and some of them include free certificates and badges! Indeed, besides offering courses on platforms like Coursera and Udacity, Google itself runs a series of educational platforms with different goals.
For example, the Grow with Google initiative and Google’s Digital Garage offer online courses to help learners gain digital skills or prepare them to run online businesses. Fortunately, hundreds of these courses offer free certificates or badges. In total, we found over 700 courses, covering topics such as digital marketing, Google Analytics, and Google Cloud. Learn proven tactics and strategies from top marketing experts. More Free Certificates You can find all our free certificates articles here. Free Google Analytics Certifications. Julia Programming Applications – What is Julia Used For?
Julia is a high-level, high-performance dynamic programming language. It combines the ease of use of scripting languages like Python with the speed and efficiency of compiled languages like C/C++. Julia has been gaining traction due to its speed, intuitive syntax, and ability to quickly and efficiently solve complex problems. Being a general-purpose language, you can use Julia in many areas and it can perform various tasks. In this article, we will be going through various areas where Julia can be applied. I'll also discuss the various packages you can use to get the most out of the language. Julia Programming Use Cases Machine Learning/AI This is undoubtedly one of the widest applications of Julia.
The MLJ.jl is a set of tools that provides a centralized interface to standard machine learning algorithms like clustering, decision trees, and generalized linear models. Julia also provides deep learning frameworks like Flux and Knet, which makes it easier to work with neural networks. Graphics. Tools for Data Science. In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio.
You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Data Science Ethics. Learn SQL Basics for Data Science. Data Science: Foundations using R. What is Data Science? Introduction to R: Basic R syntax. Análisis de datos con programación en R. Using Python for Research. Perform data science with Azure Databricks.
Algoritmos y Programación en R. O'Reilly: Data Quality Framework. Data Science Math Skills. Data Privacy Fundamentals. Innovating with Data and Google Cloud. THIS TERMS OF SERVICE AGREEMENT (THE “AGREEMENT”), ALONG WITH THE PRIVACY POLICY LOCATED AT qwiklab.com/privacy_policy (THE “PRIVACY POLICY”), ESTABLISHES THE TERMS AND CONDITIONS APPLICABLE TO YOUR USE OF THE SERVICE (AS DEFINED BELOW) OFFERED BY CLOUD VLAB INC. (“CLOUD VLAB” OR ‘WE’).
BY CLICKING THE "I ACCEPT" BUTTON DISPLAYED AS PART OF THE REGISTRATION PROCESS OR BY USING THE SERVICE OR ANY PORTION THEREOF, YOU ACCEPT AND AGREE TO BE BOUND BY THE TERMS AND CONDITIONS OF THIS AGREEMENT AND THE PRIVACY POLICY, INCLUDING ALL TERMS INCORPORATED HEREIN BY REFERENCE. IF YOU ARE ENTERING INTO THIS AGREEMENT ON BEHALF OF A COMPANY OR OTHER LEGAL ENTITY, YOU REPRESENT THAT YOU HAVE THE AUTHORITY TO BIND SUCH ENTITY TO THIS AGREEMENT, IN WHICH CASE THE TERMS "YOU" OR "YOUR" SHALL REFER TO SUCH ENTITY. IF YOU DO NOT HAVE SUCH AUTHORITY, OR IF YOU DO NOT AGREE WITH THESE TERMS AND CONDITIONS, YOU MUST SELECT THE "I DECLINE" BUTTON AND MAY NOT USE THE SERVICE. Restrictions and Limitations. How to become a data scientist. How to Become a Data Scientist - Career Advice. Introduction to Computational Thinking and Data Science.
*Note - This is an Archived course* 6.00.2x is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. We have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics, so that they will have an idea of what’s possible when the time comes later in their career to think about how to use computation to accomplish some goal. That said, it is not a “computation appreciation” course. Students will spend a considerable amount of time writing programs to implement the concepts covered in the course. This is a past/archived course. At this time, you can only explore this course in a self-paced fashion. Modern Data Science. AprendeR: Introducción al tratamiento de datos con R y RStudio (UNIVERSIDAD ILLES BALEARS)
El avance de las tecnologías permite recoger un número creciente de conjuntos de datos, cada vez mayores, relacionados con ciencias experimentales, sanidad, economía, ciencias sociales, comunicación, etc. Saber explorar, describir y analizar conjuntos de datos es una competencia cada día más valorada por los empleadores y más necesaria para comprender lo que nos rodea, e imprescindible en un científico. Este curso es una introducción al manejo de R y RStudio en la descripción, análisis y visualización de conjuntos de datos.
R es un entorno de programación estadístico muy potente de código libre, que se ha convertido en herramienta de referencia para empresas como Google o Facebook. Data Science.