Acerca de este Curso
4.5
2,131 ratings
415 reviews
One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....
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

Sugerido: 4 hours/week

Aprox. 13 horas para completar
Comment Dots

English

Subtítulos: English

Qué aprenderás

  • Check
    Describe machine learning methods such as regression or classification trees
  • Check
    Explain the complete process of building prediction functions
  • Check
    Understand concepts such as training and tests sets, overfitting, and error rates
  • Check
    Use the basic components of building and applying prediction functions

Habilidades que obtendrás

Random ForestMachine Learning (ML) AlgorithmsMachine LearningR Programming
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

Sugerido: 4 hours/week

Aprox. 13 horas para completar
Comment Dots

English

Subtítulos: English

Programa - Qué aprenderás en este curso

1

Sección
Clock
2 horas para completar

Week 1: Prediction, Errors, and Cross Validation

This week will cover prediction, relative importance of steps, errors, and cross validation....
Reading
9 videos (Total: 73 min), 3 readings, 1 quiz
Video9 videos
What is prediction?8m
Relative importance of steps9m
In and out of sample errors6m
Prediction study design9m
Types of errors10m
Receiver Operating Characteristic5m
Cross validation8m
What data should you use?6m
Reading3 lecturas
Welcome to Practical Machine Learning10m
Syllabus10m
Pre-Course Survey10m
Quiz1 ejercicio de práctica
Quiz 110m

2

Sección
Clock
2 horas para completar

Week 2: The Caret Package

This week will introduce the caret package, tools for creating features and preprocessing....
Reading
9 videos (Total: 96 min), 1 quiz
Video9 videos
Data slicing5m
Training options7m
Plotting predictors10m
Basic preprocessing10m
Covariate creation17m
Preprocessing with principal components analysis14m
Predicting with Regression12m
Predicting with Regression Multiple Covariates11m
Quiz1 ejercicio de práctica
Quiz 210m

3

Sección
Clock
1 hora para completar

Week 3: Predicting with trees, Random Forests, & Model Based Predictions

This week we introduce a number of machine learning algorithms you can use to complete your course project....
Reading
5 videos (Total: 48 min), 1 quiz
Video5 videos
Bagging9m
Random Forests6m
Boosting7m
Model Based Prediction11m
Quiz1 ejercicio de práctica
Quiz 310m

4

Sección
Clock
4 horas para completar

Week 4: Regularized Regression and Combining Predictors

This week, we will cover regularized regression and combining predictors. ...
Reading
4 videos (Total: 33 min), 2 readings, 3 quizzes
Video4 videos
Combining predictors7m
Forecasting7m
Unsupervised Prediction4m
Reading2 lecturas
Course Project Instructions (READ FIRST)10m
Post-Course Survey10m
Quiz2 ejercicios de práctica
Quiz 410m
Course Project Prediction Quiz40m
4.5
Direction Signs

34%

comenzó una nueva carrera después de completar estos cursos
Briefcase

83%

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

14%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por ADMar 1st 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

por ASAug 31st 2017

Highly recommend this course. It makes you read a lot, do lot's of practical exercises. The final project is a must do. After finishing this course you can start playing with kaggle data sets.

Instructores

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

Acerca de Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

Acerca del programa especializado Data Science

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

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.

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.