4.2 Read 93 reviews
Overview
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 Practical Machine Learning Course offered by Coursera in partnership Johns Hopkins University 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.
What you will learn
- Describe machine learning methods such as regression or classification trees
- Explain the complete process of building prediction functions
- Understand concepts such as training and tests sets, overfitting, and error rates
- Use the basic components of building and applying prediction functions
Programme Structure
Courses include:
- Prediction, Errors, and Cross Validation
- The Caret Package
- Predicting with trees, Random Forests, & Model Based Predictions
- Regularized Regression and Combining Predictors
Details on Coursera Plus:
- Learn Anything: Explore any interest or trending topic, take prerequisites, and advance your skills
- Save money: Spend less money on your learning if you plan to take multiple courses this year
- Flexible Learning: Learn at your own pace, move between multiple courses, or switch to a different course
- Unlimited Certificates: Earn a certificate for every learning programme that you complete at no additional cost
Key information
Duration
- Part-time
- 1 months
- 2 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Data Science & Big Data Machine Learning View 213 other Short Courses in Machine Learning in United StatesWhat students do after studying
Join for free or log in to access our complete career info list.
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- Audit: free access to course materials except graded items
- Certificate: a trusted way to showcase your skills
- A year of unlimited access with Coursera Plus $399
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
Improve page content