- Course introduction
Intermediate
Online
3 Weeks
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
The Feature Engineering certification course is of an intermediary level of training which is a hundred percent online course and it can be viewed on the website of Coursera. The programme is within the easy reach of the enrolled students at zero cost. The training is a part of the course named Machine Learning with TensorFlow on Google Cloud Platform Specialization that is available on Coursera. Aspiring participants who join the online course of Feature Engineering will be able to comprehend several features used for distinct functions in order to make an accurate model of machine learning.
In the Feature Engineering online course, students are not limited to follow a particular set of reading materials and they can learn from the external study matter along with the one provided by the platform within the programme. The programme does not limit students with any fixed schedules or deadlines and participants are allowed to set their own study schedules according to their preferences and requirements.
This intermediate level of the programme can be concluded by spending a total of approximately 14 hours. The Feature Engineering certification syllabus of the programme is arranged in a weekly manner and is split up into a total of 4 weeks or 1 month. If the participant successfully completes the curriculum, he or she will be able to receive a certificate for the online course from the platform.
The highlights
- Intermediary level course
- 14 hours of learning
- Free course
- Flexible timings
- 7 days free trial
- Certificate available
- Offered by Coursera
- Online learning
- Financial aid available
- 1-month programme
- No extra charges
Program offerings
- Quizzes
- Practice exercise
- Assignments
- Discussion groups
- Readings
- Video lectures
Course and certificate fees
- Participants will be able to join the course for 7 days for free.
Feature Engineering Fees Details
Particulars | Fee Amount in INR |
Feature Engineering - Audit course | Free |
Feature Engineering - 1 month | Rs.4,051/- |
Feature Engineering - 3 months | Rs.8,103/- |
Feature Engineering - 6 months | Rs.12,155/- |
certificate availability
certificate providing authority
Eligibility criteria
Certification Qualifying Details
At the end of the programme, if a student is able to complete the lessons along with all the quizzes and assignments, he or she will receive a certificate for the programme.
What you will learn
Students will be informed about the following points in the Feature Engineering training-
- Candidates will gain an understanding of preprocessing with the cloud data prep in the programme.
- Learn about cloud data flow and cloud data prep in the Feature Engineering certification.
- Students will be able to make a comparison of needed aspects of a good feature and choose a better option.
- Students will be able to learn the combination techniques and the creation of new features through feature crosses.
- Learners will gain an understanding of the Tensor flow and how to apply the same to transform features.
- Participants will be able to identify the good and bad features through the Feature Engineering programme.
- Know the difference between generalization and memorization.
- Students will gain valuable insights on the analysis phase as well as the transformation phase of Tensor flow transformation.
Admission details
The admission process for getting into the Feature Engineering by Coursera only takes a few steps that are mentioned below-
Step 1- Students must enrol for the subject via the website of the course.
Step 2- Students need to log in or sign up by using the Coursera account.
Step 3- Students need to get enrolled for the subject by clicking on the Enroll option given at the top of the page.
Step 4- Students need to click on the Go to course option given on the redirect page after the enrolment process.
Step 5-Students can access the course as well as study materials by clicking on the ‘Go to course’ option.
The syllabus
Week 1: Module 0: Introduction
Video
Week 1: Module 1: Introduction to Vertex AI Feature Store
Videos
- Introduction
- Feature Store benefits
- Feature Store terminology and concepts
- The Feature Store data model
- Creating a Feature Store
- Serving features: Batch and online
- (Optional) Lab intro: Using Feature Store
- Getting Started with Google Cloud and Qwiklabs
Reading
- Resources: Introduction to Vertex AI Feature Store
Practice Exercise
- Introduction to Vertex AI Feature Store
Week 1: Module 2: Raw Data to Features
Videos
- Introduction
- Overview of feature engineering
- Raw data to features
- Good features versus bad features
- Features should be known at prediction-time
- Features should be numeric
- Features should have enough examples
- Bringing human insight
- Representing features
Reading
- Resources: Raw Data to Features
Practice Exercise
- Raw Data to Features
Week 2: Module 3: Feature Engineering
Videos
- Introduction
- Machine learning versus statistics
- Basic feature engineering
- Lab intro: Performing Basic Feature Engineering in BigQuery ML
- Advanced feature engineering: Feature crosses
- Bucketize and Transform Functions
- (Optional) Lab intro: Advanced Feature Engineering BigQuery ML
- Predict housing prices
- Estimate taxi fare
- Temporal and geolocation features
- Lab intro: Basic Feature Engineering in Keras
- Lab intro: Advanced Feature Engineering in Keras
Reading
- Resources: Feature Engineering
Practice Exercise
- Feature Engineering
Week 3: Module 4: Preprocessing and Feature Creation
Videos
- Introduction
- Apache Beam and Dataflow
- Dataflow terms and concepts
Reading
- Resources: Preprocessing and Feature Creation
Practice Exercise
- Preprocessing and Feature Creation
Week 3: Module 5: Feature Crosses - TensorFlow Playground
Videos
- Introduction
- What is a feature cross
- Discretization
- Lab intro: TensorFlow Playground: Use feature crosses to create a good classifier
- Lab intro: TensorFlow Playground: Too much of a good thing
Reading
- Resources: Feature Crosses - TensorFlow Playground
Practice Exercise
- Feature Crosses - TensorFlow Playground
Week 3: Module 6: Introduction to TensorFlow Transform
Videos
- Introduction
- TensorFlow Transform
- Analyze phase
- Transform phase
- Supporting serving
- Lab Intro: Exploring tf.transform
Reading
- Resources: Introduction to TensorFlow Transform
Practice Exercise
- Introduction to TensorFlow Transform
Week 3: Module 7: Summary
Readings
- Summary
- Resource: All quiz questions
- Resource: All readings
- Resource: All slides
Scholarship Details
Financial aid is available for students who are not able to pay for the course due to financial issues.
How it helps
The Feature Engineering certification course needs to be studied in an online setup as it is thoroughly an online programme. The course can be pursued at no cost for a specific period of time by the students so that they get an idea of the curriculum of the programme. The course covers the aspects of Machine learning with the Tensor flow and includes topics that help the participants be informed about features required for machine learning and which feature should be used for making an accurate machine learning model.
The Feature Engineering certification benefits of the programme include getting a job quickly by the means of sharing the certificate on different social platforms such as LinkedIn. Sharing the certificate on LinkedIn helps the recruiters notice the skills acquired by the candidate and lead the participant to get a job or an internship opportunity. Due to the information gained through the programme, students may also be able to apply for a higher level of training in the same discipline.
The achievement of the certification for the Feature Engineering online course can also be mentioned as a highlight in the resume of CVs of the students so that the weightage of their profile is up to the standard market requirements. Participants who pursue this course will be able to help the students or colleagues who face any issue regarding the subject matter and make a good impression on their colleagues.
Instructors
Google Cloud Training
Instructor
Google Cloud
FAQs
No, the course is not available in the audit mode.
Yes, students can easily apply for the financial aid programme available for the course.
There is no deadline for admission to this programme and students can apply anytime owing to their requirements.
The review of the scholarship application takes a minimum of 15 days.
Students can select the enrol option and then the Start Free Trial option to get started with a free trial of the course.
The entire programme along with all the extra activities will take around a month to get finished.
No, the course is not equal to any university credit.
Yes, this course can be pursued by every participant who is interested.
Students need to complete the programme to apply for the course.
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