This course is designed to provide you with the skills and knowledge necessary to leverage automation and ensure business continuity in cloud environments. You will explore various automation strategies for deploying and maintaining cloud infrastructure and applications. Learn how infrastructure as code simplifies deployment, and delve into version control and continuous integration/continuous deployment pipelines. Gain insights into automation, orchestration, and configuration management to streamline cloud operations. The course shifts the focus to business continuity, a critical aspect for any organization. Discover the role of backups in maintaining continuity, compare different backup types, and explore restore strategies. Additionally, delve into disaster recovery requirements and implementations, and learn how to document DR processes effectively. This course equips you with the expertise to optimize cloud operations and ensure robust business continuity.
In this course, you learn practical skills to explore and visualize data. You will follow a small business owner's data-driven journey to improve company performance to gain skills to prepare data, conduct analysis, and share insights using data visualizations. By the end of this course, you will be able to prepare data and conduct exploratory analysis, investigate relationships in the data by using visualizations, and communicate findings. If you are new to analyzing data, this course is for you. The focus in this course is on practical understanding while avoiding complicated statistical terminology to help you feel supported and encouraged throughout the process. Anybody can be successful in this course regardless or background.
This comprehensive Blogging course will equip you with essential skills to create, manage, and promote a successful blog. You’ll learn to choose the right platforms, develop engaging content, and implement promotion strategies to achieve measurable growth.
By the end of this course, you will be able to:
- Master Blogging Fundamentals: Understand key components and benefits to boost online visibility and authority.
- Select Suitable Platforms: Choose platforms like WordPress, Blogger, or Wix and integrate blogs seamlessly.
- Create and Manage Content: Develop high-quality posts yourself or hire professional writers for consistency.
- Streamline Content Workflow: Plan and organize with content calendars to ensure consistent publishing.
- Promote and Drive Engagement: Use social media and email lists to grow readership and interaction.
- Analyze and Optimize Performance: Track metrics and refine strategies for continuous improvement.
Perfect for aspiring bloggers, marketers, and business owners looking to grow their online presence and audience engagement.
Did you know developers using AI coding tools like GitHub Copilot are significantly more productive and make fewer errors? Join along in this course and become a more efficient and productive developer with the power of AI at your fingertips.
This Short Course is designed to equip developers with the skills to effectively use GitHub Copilot in Visual Studio Code, streamlining their coding process. By mastering Copilot, you'll write code faster and with greater accuracy, directly enhancing your software development capabilities.
With just a 3-hour commitment, you'll master setting up GitHub Copilot with Visual Studio Code, building a Pomodoro timer app, and applying best practices in refactoring, testing, and debugging. This course is designed to make learning easy and enjoyable for you
This course is unique because it combines theoretical knowledge with practical application, allowing you to implement what you've learned in real-world scenarios immediately. Basic coding knowledge in React, JavaScript, HTML, and CSS and familiarity with Visual Studio Code and GitHub are recommended to ensure success.
Data Processing, Exploratory Analysis and Visualization
This course introduces distributed computing frameworks and big data visualization techniques. Learners will explore MapReduce, work with Apache Spark, implement transformations with PySpark, and use Spark SQL for large-scale analysis. The course concludes with building compelling dashboards and reports using Power BI for actionable business insights.
By the end of this course, you will be able to:
- Explain distributed computing and MapReduce concepts
- Process large datasets using Apache Spark and PySpark
- Apply Spark SQL for advanced queries and transformations
- Create dashboards and visualizations using Power BI
Tools & Software:
Apache Spark, PySpark, Azure Databricks, Power BI
Skills:
Distributed computing, Data analysis, PySpark, Spark SQL, Data visualization
Grow with AI: Your AI-driven Growth Marketing strategy
This innovative course explores the transformative role of Artificial Intelligence (AI) in Growth Marketing, equipping participants with the knowledge and skills to leverage AI for crafting innovative marketing strategies and optimizing campaigns. Participants will delve into how AI reshapes marketing approaches and contributes significantly to achieving key business objectives, preparing them to thrive in the dynamic digital marketing landscape.
The course is designed for marketing professionals, marketing strategists, business owners, growth hackers, sales managers, and anyone interested in utilizing AI to drive business growth and enhance customer engagement.
Learners should have a basic understanding of fundamental marketing concepts and a keen interest in leveraging AI for strategic growth.
Conceptos básicos de BigQuery para profesionales de Teradata
Este curso abarca los aspectos fundamentales de BigQuery para profesionales que están familiarizados con los almacenes de datos en la nube basados en SQL en Teradata y quieren comenzar a trabajar en BigQuery. A través de contenido interactivo en las lecciones y labs prácticos, aprenderán a aprovisionar recursos, crear y compartir recursos de datos, transferir datos y optimizar el rendimiento de las consultas en BigQuery. También aprovecharán sus conocimientos de Teradata para conocer las similitudes y diferencias entre Teradata y BigQuery para comenzar a usar almacenes de datos en BigQuery.
In this short, hands-on course, you’ll learn how to build fast, efficient AI training and inference pipelines by optimizing both data loading and computational graphs. You’ll start by creating parallel, high-throughput data pipelines that keep GPUs consistently busy and reduce training bottlenecks. Then you’ll analyze a model’s computational graph to identify and remove redundant operations that slow execution. Through focused lesson videos, practical labs, and guided coach activities, you’ll re-export a streamlined model and validate real latency improvements. By the end, you’ll be able to diagnose performance issues, streamline pipelines, and apply optimization techniques that make AI systems faster, more reliable, and more cost-efficient.
歡迎參加「開始使用 Google Kubernetes Engine」課程。Kubernetes 是位於應用程式和硬體基礎架構之間的軟體層。如果您對這項技術感興趣，這堂課程可以滿足您的需求。有了 Google Kubernetes Engine，您就能在 Google Cloud 中以代管服務的形式使用 Kubernetes。
本課程的目標在於介紹 Google Kubernetes Engine (常簡稱為 GKE) 的基本概念，以及如何將應用程式容器化，以便在 Google Cloud 中執行。課程首先會初步介紹 Google Cloud，隨後簡介容器、Kubernetes、Kubernetes 架構和 Kubernetes 作業。
Linux es un sistema operativo popular que se basa en el sistema operativo de Unix. Tiene muchas distribuciones que tienen diferentes interfaces para instalar software, diferentes interfaces de usuario, etc. Una cosa que todas las 'distros' tienen en común es que todas tienen una interfaz de línea de comandos, o terminal. De hecho, a veces no hay ninguna interfaz de usuario excepto la propia terminal. Un servidor Linux que ejecuta una aplicación web en AWS, por ejemplo, puede contener sólo el software necesario para ejecutar la aplicación, y ninguna interfaz gráfica de usuario en absoluto. Es crucial aprender la línea de comandos de Linux si vas a ser un usuario productivo de Linux y/o administrar un servidor Linux.
En este curso, utilizarás los comandos de Linux para navegar por los directorios de Linux, buscar archivos, buscar patrones, crear archivos y directorios, y eliminar archivos y directorios.
Nota: Este curso está dirigido a personas que buscan iniciarse en el mundo de los sistemas Unix y deseen aprender a manejar la terminal de comandos.
Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.
At the end of this course, you will be able to:
* Recognize different data elements in your own work and in everyday life problems
* Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design
* Identify the frequent data operations required for various types of data
* Select a data model to suit the characteristics of your data
* Apply techniques to handle streaming data
* Differentiate between a traditional Database Management System and a Big Data Management System
* Appreciate why there are so many data management systems
* Design a big data information system for an online game company
This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications.
Hardware Requirements:
(A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size.
Software Requirements:
This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.
