If you are relatively new to the world of cloud computing, you might have come across a term JSON and not know what it is exactly. JSON stands for JavaScript Object Notation and is widely used to exchange information between clients and servers. Many No-SQL databases also uses the format to store data. In this 1-hour long project-based course, you will learn about the format and structure of JSON, accept and process JSON in your code, and transmit JSON to other processes.
No prior experience with JSON is required but basic to intermediate HTML and JavaScript is required.
Note: You should complete all the other courses in this Specialization before beginning this course.
This six-week long Project course of the Data Mining Specialization will allow you to apply the learned algorithms and techniques for data mining from the previous courses in the Specialization, including Pattern Discovery, Clustering, Text Retrieval, Text Mining, and Visualization, to solve interesting real-world data mining challenges. Specifically, you will work on a restaurant review data set from Yelp and use all the knowledge and skills you’ve learned from the previous courses to mine this data set to discover interesting and useful knowledge. The design of the Project emphasizes: 1) simulating the workflow of a data miner in a real job setting; 2) integrating different mining techniques covered in multiple individual courses; 3) experimenting with different ways to solve a problem to deepen your understanding of techniques; and 4) allowing you to propose and explore your own ideas creatively.
The goal of the Project is to analyze and mine a large Yelp review data set to discover useful knowledge to help people make decisions in dining. The project will include the following outputs:
1. Opinion visualization: explore and visualize the review content to understand what people have said in those reviews.
2. Cuisine map construction: mine the data set to understand the landscape of different types of cuisines and their similarities.
3. Discovery of popular dishes for a cuisine: mine the data set to discover the common/popular dishes of a particular cuisine.
4. Recommendation of restaurants to help people decide where to dine: mine the data set to rank restaurants for a specific dish and predict the hygiene condition of a restaurant.
From the perspective of users, a cuisine map can help them understand what cuisines are there and see the big picture of all kinds of cuisines and their relations. Once they decide what cuisine to try, they would be interested in knowing what the popular dishes of that cuisine are and decide what dishes to have. Finally, they will need to choose a restaurant. Thus, recommending restaurants based on a particular dish would be useful. Moreover, predicting the hygiene condition of a restaurant would also be helpful.
By working on these tasks, you will gain experience with a typical workflow in data mining that includes data preprocessing, data exploration, data analysis, improvement of analysis methods, and presentation of results. You will have an opportunity to combine multiple algorithms from different courses to complete a relatively complicated mining task and experiment with different ways to solve a problem to understand the best way to solve it. We will suggest specific approaches, but you are highly encouraged to explore your own ideas since open exploration is, by design, a goal of the Project.
You are required to submit a brief report for each of the tasks for peer grading. A final consolidated report is also required, which will be peer-graded.
Este curso es una introducción a las metodologías fundamentales para la gestión, planificación y evaluación de sistemas de transporte de pasajeros. Se aprenderán técnicas usadas en la práctica para estimar la demanda, modelar la operación y realizar análisis económicos de proyectos de transporte. Algunos temas estudiados incluyen: modelo clásico de transporte de cuatro etapas, modelo de distribución de viajes gravitacional, modelo de elección discreta logit, teoría de colas, análisis de redes, paradoja de Braess, tarificación por congestión y evaluación social de proyectos de transporte.
In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.
Welcome to the course Oracle Autonomous Database Administration. This course helps DBAs to deploy and administer Autonomous databases, and prepares them for the Oracle Autonomous Database Cloud Specialist Certification.
An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
Architecting Google Kubernetes Engine: Workloads in italiano
In questo corso, ""Architecting with Google Kubernetes Engine: Workloads", imparerai come eseguire le operazioni Kubernetes, creare e gestire i deployment, quali sono gli strumenti di networking di GKE e come fornire archiviazione permanente ai tuoi carichi di lavoro Kubernetes.
Questo è il secondo corso della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Reliable Google Cloud Infrastructure: Design and Process o al corso Hybrid Cloud Infrastructure Foundations with Anthos."
Master the AI tools redefining UI/UX design — and learn to use them the way professionals actually do. In this hands-on course, you'll build real skills across today's most in-demand platforms: Canva AI, Figma AI, Adobe Firefly, and Photoshop AI. From generating brand kits and landing page wireframes to retouching images and automating design workflows, every module delivers practical, portfolio-ready outcomes.
You'll learn to craft precise AI prompts, apply color and typography theory, generate and edit visuals ethically, and connect individual tools into a seamless end-to-end design ecosystem — all the way through to developer handoff.
What makes this course different is its balance. Rather than treating AI as a magic button, it teaches you where human judgment matters most — and how to stay in creative control while AI handles the heavy lifting. Whether you're a working designer looking to modernize your workflow or a newcomer ready to enter the field AI-first, this course gives you the mindset, the methods, and the hands-on practice to move faster, design smarter, and stand out in a rapidly evolving industry.
There are a ever increasing number of options, strategies and solutions for integrating AI solutions into a project. It can feel overwhelming to understand what these options entail let alone understand how to decide what solution best fits a use case.
In this course we aim to give individuals the basic info they need to make basic plans for integrating AI tools into their project.
The course is intended for individuals who have an AI related project in mind or think that they might need to incorporate AI into their project. They are likely the leader who is guiding others in an AI related project and not necessarily the person who will write code or carry out the technical aspects of the project.
In this 1-hour long project-based course, you will gain hands-on experience with one of the hottest web development framework, React. If you have some experience with HTML, CSS, JavaScript and want to start developing with React, this course is for you!
By the end of this course You will understand the fundamental of React and be able to create and build a website with React with ease.
En un mundo Volátil, Incierto, Complejo, Hiperconectado y Ambiguo (VUCHA), los ciclos de negocios e innovación se están reduciendo como nunca antes. El ciclo de vida de las empresas se ha reducido a menos de un tercio en los últimos 30 años.
La democratización de la innovación ha abierto posibilidades infinitas para muchas personas, empresas y regiones en todo el mundo. En particular, los emprendedores y las startups están aprovechando las oportunidades generadas por la transformación que se esta produciendo, en este curso en línea entenderás como puedes comenzar a desarrollar esas habilidades innovadoras y de emprendimiento, y así aplicarlas de forma exitosa.
Este curso online se enfoca en comprender las estrategias, las herramientas y los conceptos básicos que los emprendedores utilizan para emprender innovaciones en el mercado y escalar sus emprendimientos, generando valor y disrupción en muchos mercados.
En este curso de administración los estudiantes entenderán:
Como validar un problema y su solución (Problem-Solution Fit)
Como validar si un producto tiene una aceptación en un mercado (Product-Market Fit)
Como escalar sus emprendimientos (Business Model Fit)
This course explores common analytics methods used by marketers such as audience segmentation, clustering and marketing mix modeling. . You'll explore how to use linear regression for marketing planning and forecasting, and how to assess advertising effectiveness through experiments.
By the end of this course you will be able to:
• Understand your audience using analytics and variable descriptions
• Define a target audience using segmentation with K-means clustering
• Use historical data to plan your marketing across different channels
• Use linear regression to forecast marketing outcomes
• Describe marketing mix modeling and apply different attribution models
• Assess advertising effectiveness
• Explain how A/B testing works and how you can use it to optimize ads
• Evaluate experiment results and assess the strength of the experiment
• Optimize your sales funnel
This course is for people who want to learn how to plan, forecast and optimize marketing efforts using marketing mix modeling, attribution models and A/B tests.
