Practical Machine Learning
Learn machine learning along with the application by Coursera.
Online
1,699 INR Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Practical Machine Learning, available on Coursera, is administered by Johns Hopkins University to expose the students to the realm of machine learning along with a thorough practical training with the help of numerous practical applications. Practical Machine Learning Certification Syllabus developed by industry experts and experienced professors will walk the students through concepts of sets, overfitting, regression, classification trees, Naive Bayes, random forests, and error rates.
Practical Machine Learning Certification Course, provided by Coursera, will shed light on numerous topics related to machine learning including algorithms, evaluation, data collection, and feature creation. Practical Machine Learning Certification by Coursera prepared by Jeff Leek, Ph.D., Roger D. Peng, Ph.D., and Brian Caffo, Ph.D. with an emphasis on facilitating the learners to practice the application of machine learning.
The Highlights
- Provided by Coursera
- Approximately 8 hours of programme
- Offered by Johns Hopkins University
- Flexible Deadlines
- Self-Paced Learning Option
- Shareable Certificate
- Financial Aid Available
- 100% Online Course
Programme Offerings
- English videos with multiple subtitles
- practice quizzes
- Graded Assignments with peer feedback
- graded Quizzes with feedback
- Graded Programming Assignments
- Course Videos & Readings
- EMI payment options
- 14 day refund period.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
The fees for the course Practical Machine Learning is -
| Fees components | Amount |
| 1 month | Rs. 1,699 |
| 3 month | Rs. 3,499 |
| 6 month | Rs. 5,199 |
Eligibility Criteria
Certification Qualifying Details
Only by completing the whole aspects of the proceedings of the programme including the course videos, readings, graded assignments, and quizzes, the candidates can get certified with Practical Machine Learning Certification.
What you will learn
After the completion of the Practical Machine Learning Training, the students will learn the following concepts in greater depth:
- Random Forest
- Machine Learning (ML) Algorithms
- Machine Learning
- R Programming
Who it is for
This practical course on Machine Learning suits the ones who want to be seen as ML Engineers in the future.
Admission Details
Step 1 -First, the students will have to register and sign up on https://www.coursera.org/ to get access to the courses provided by Coursera.
Step 2 - After activating the Coursera account, the candidate can sign in.
Step 3 - Then, the candidate can search the ‘Johns Hopkins University’ in the search column, and then, the programmes provided by the Johns Hopkins University will be shown on the screen.
Step 4 - Then, find the course ‘Practical Machine Learning’ in the list and click on it.
Step 5- Then, the page of the course will appear on the screen, and then, click on the option ‘enroll’. The students can enroll either by paying the fee and getting full access to the course or just audit free of cost.
The Syllabus
Videos
- Prediction motivation
- What is prediction?
- Relative importance of steps
- In and out of sample errors
- Prediction study design
- Types of errors
- Receiver Operating Characteristic
- Cross-validation
- What data should you use?
Readings
- Welcome to Practical Machine Learning
- A Note of Explanation
- Syllabus
- Pre-Course Survey
Quiz
- Quiz 1
Videos
- Caret package
- Data slicing
- Training options
- Plotting predictors
- Basic preprocessing
- Covariate creation
- Preprocessing with principal components analysis
- Predicting with Regression
- Predicting with Regression Multiple Covariates
Practice exercises
Quiz 2
Videos
- Predicting with trees
- Bagging
- Random Forests
- Boosting
- Model-Based Prediction
Quiz
Quiz 3
Videos
- Regularized regression
- Combining predictors
- Forecasting
- Unsupervised Prediction
Readings
- Course Project Instructions (READ FIRST)
- Post-Course Survey
Quizzes
- Quiz 4
- Course Project Prediction Quiz
Peer Review
- Prediction Assignment Writeup
Instructors
Johns Hopkins Frequently Asked Questions (FAQ's)
The course can be completed within approximately 8 hours.
The course is tutored by Jeff Leek, Ph.D., the Associate Professor of Biostatistics at Bloomberg School of Public Health, Brian Caffo, Ph.D., the Professor of Biostatistics at Bloomberg School of Public Health, and Roger D. Peng, Ph.D., the Associate Professor of Biostatistics at the Bloomberg School of Public Health.
The subtitles are available in the languages of Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English and Spanish.
The course is completely offered in the online mode.
The programme is offered by Johns Hopkins University.