Acerca de este Curso
4.5
949 calificaciones
187 revisiones
Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark...
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Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
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Fechas límite flexibles

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Clock

Approx. 15 hours to complete

Sugerido: 5 Weeks, 3 - 5 hours per week...
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English

Subtítulos: English...

Habilidades que obtendrás

Machine Learning ConceptsKnimeMachine LearningApache Spark
Stacks
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Clock

Approx. 15 hours to complete

Sugerido: 5 Weeks, 3 - 5 hours per week...
Comment Dots

English

Subtítulos: English...

Programa - Qué aprenderás en este curso

Week
1
Clock
24 minutos para completar

Welcome

...
Reading
2 videos (Total: 14 min)
Video2 videos
Summary of Big Data Integration and Processing10m
Clock
3 horas para completar

Introduction to Machine Learning with Big Data

...
Reading
7 videos (Total: 45 min), 7 readings, 1 quiz
Video7 videos
Categories Of Machine Learning Techniques7m
Machine Learning Process3m
Goals and Activities in the Machine Learning Process10m
CRISP-DM5m
Scaling Up Machine Learning Algorithms5m
Tools Used in this Course5m
Reading7 lecturas
Slides: Machine Learning Overview and Applications25m
Downloading, Installing and Using KNIMEm
Downloading and Installing the Cloudera VM Instructions (Windows)10m
Downloading and Installing the Cloudera VM Instructions (Mac)10m
Instructions for Downloading Hands On Datasets10m
Instructions for Starting Jupyter10m
PDFs of Readings for Week 1 Hands-On10m
Quiz1 ejercicio de práctica
Machine Learning Overview20m
Week
2
Clock
3 horas para completar

Data Exploration

...
Reading
6 videos (Total: 39 min), 5 readings, 2 quizzes
Video6 videos
Data Exploration4m
Data Exploration through Summary Statistics7m
Data Exploration through Plots8m
Exploring Data with KNIME Plots9m
Data Exploration in Spark5m
Reading5 lecturas
Slides: Data Exploration Overview and Terminology10m
Description of Daily Weather Dataset10m
Exploring Data with KNIME Plots40m
Data Exploration in Spark10m
PDFs of Activities for Data Exploration Hands-On Readings10m
Quiz2 ejercicios de práctica
Data Exploration20m
Data Exploration in KNIME and Spark Quiz20m
Clock
3 horas para completar

Data Preparation

...
Reading
8 videos (Total: 42 min), 4 readings, 2 quizzes
Video8 videos
Data Quality4m
Addressing Data Quality Issues4m
Feature Selection5m
Feature Transformation5m
Dimensionality Reduction7m
Handling Missing Values in KNIME5m
Handling Missing Values in Spark5m
Reading4 lecturas
Slides: Data Preparation for Machine Learning30m
Handling Missing Values in KNIME20m
Handling Missing Values in Spark10m
PDFs for Data Preparation Hands-On Readings10m
Quiz2 ejercicios de práctica
Data Preparation25m
Handling Missing Values in KNIME and Spark Quiz20m
Week
3
Clock
4 horas para completar

Classification

...
Reading
8 videos (Total: 60 min), 7 readings, 2 quizzes
Video8 videos
Building and Applying a Classification Model5m
Classification Algorithms2m
k-Nearest Neighbors4m
Decision Trees13m
Naïve Bayes14m
Classification using Decision Tree in KNIME8m
Classification in Spark6m
Reading7 lecturas
Slides: What is Classification?10m
Slides: Classification Algorithms10m
Classification using Decision Tree in KNIME45m
Interpreting a Decision Tree in KNIME20m
Instructions for Changing the Number of Cloudera VM CPUs10m
Classification in Spark45m
PDFs for Classification Hands-On Readings10m
Quiz2 ejercicios de práctica
Classification20m
Classification in KNIME and Spark Quiz16m
Week
4
Clock
3 horas para completar

Evaluation of Machine Learning Models

...
Reading
7 videos (Total: 42 min), 7 readings, 2 quizzes
Video7 videos
Overfitting in Decision Trees3m
Using a Validation Set9m
Metrics to Evaluate Model Performance10m
Confusion Matrix7m
Evaluation of Decision Tree in KNIME3m
Evaluation of Decision Tree in Spark2m
Reading7 lecturas
Slides: Overfitting: What is it and how would you prevent it?10m
Slides: Model evaluation metrics and methods10m
Evaluation of Decision Tree in KNIME30m
Completed KNIME Workflows10m
Evaluation of Decision Tree in Spark20m
Comparing Classification Results for KNIME and Spark10m
PDFs for Evaluation of Machine Learning Models Hands-On Readings10m
Quiz2 ejercicios de práctica
Model Evaluation20m
Model Evaluation in KNIME and Spark Quiz16m
4.5
Direction Signs

60%

comenzó una nueva carrera después de completar estos cursos
Briefcase

83%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Money

25%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por PTJan 9th 2017

The course was the best introduction I had for machine learning. Helped me a lot to understand different concepts from people who already know about the subject and I didn't have any idea.

por PRJul 19th 2018

Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.

Instructores

Mai Nguyen

Lead for Data Analytics
San Diego Supercomputer Center

Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center

Acerca de University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

Acerca del programa especializado Big Data

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. ********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data....
Big Data

Preguntas Frecuentes

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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