Informações sobre o curso: Welcome to the Capstone Project for Big Data! In this culminating project, you will build a big data ecosystem using tools and methods form the earlier courses in this specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game "Catch the Pink Flamingo". During the five week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. In the first two weeks, we will introduce you to the data set and guide you through some exploratory analysis using tools such as Splunk and Open Office. Then we will move into more challenging big data problems requiring the more advanced tools you have learned including KNIME, Spark's MLLib and Gephi. Finally, during the fifth and final week, we will show you how to bring it all together to create engaging and compelling reports and slide presentations. As a result of our collaboration with Splunk, a software company focus on analyzing machine-generated big data, learners with the top projects will be eligible to present to Splunk and meet Splunk recruiters and engineering leadership.
Ministrado por: Ilkay Altintas, Chief Data Science Officer
San Diego Supercomputer Center
Ministrado por: Amarnath Gupta, Director, Advanced Query Processing Lab
San Diego Supercomputer Center (SDSC)
| Informações básicas | Curso 6 de 6 no Big Data Specialization |
| Idioma | English |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
- Vídeo: Welcome to the Big Data Capstone Project
- Vídeo: Welcome from Splunk: Rob Reed World Education Evangelist
- Reading: Planning, Preparation, and Review
- Reading: A Game by Eglence Inc. : Catch The Pink Flamingo
- Vídeo: A Summary of Catch the Pink Flamingo
- Vídeo: A Conceptual Schema for Catch the Pink Flamingo
- Reading: Overview of the Catch the Pink Flamingo Data Model
- Reading: Overview of Final Project Design
- Reading: Downloading the Game Data and Associated Scripts
- Reading: Understanding the CSV Files Generated by the Scripts
- Reading: Optional Review of Splunk
- Reading: “Catch the Pink Flamingo” Data Exploration with Splunk
- Reading: Aggregate Calculations Using Splunk
- Reading: Filtering the Data With Splunk
- Reading: Review: Classification Using Decision Tree in KNIME
- Reading: Review: Interpreting a Decision Tree in KNIME
- Reading: Workflow Overview for Building a Decision Tree in KNIME
- Reading: Description of combined_data.csv
- Reading: Informing business strategies based on client base
- Discussion Prompt: Is there only “one way” to cluster a client base?
- Discussion Prompt: How many clusters?
- Discussion Prompt: What kind of criteria might provide actionable information for Eglence Inc.?
- Reading: Practice with PySpark MLlib Clustering
- Reading: Understanding the Simulated Chat Data Generated by the Scripts
- Reading: Graph Analytics of Catch the Pink Flamingo Chat Data Using Neo4j
- Vídeo: Week 5: Bringing It All Together
- Reading: Final project preparation
- Vídeo: Congratulations! Some Final Words...
- Peer Review: Optional 3-minute video: Splunk opportunity
- Reading: Part 2: Help us connect your video to your LinkedIn profile
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
Very simple but a very informative specialization. This is an excellent introduction, you will need to study some topics like machine learning further to get a better understanding. If this was to be extended to a 10 course Specialization I would love to see more on model selection, model interpretation, regression and regularized regression, error analysis and inferential statistics, model assembling and free text analysis.
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Very engaging course. Well designed and delivered. I also liked the breadth and depth of the course. Liked it and continue use the material as reference
dm
What a challenge, I came into this course as a London Black Cab Taxi Driver, I thought the knowledge was hard but this capstone was a challenge more intense than the Knowledge of London!!!