Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The ‘Text Analytics 2: Visualizing Natural Language Processing’ online course is developed for the students to gain knowledge and expertise with the visualization and interpretation of outputs in text analytics along with the scientific overview of understanding language computations.
This computer science course is provided by the Edx educational platform in collaboration with the University of Canterbury for the classes and modules. This online program is scheduled for a period of approximately six weeks and the candidates are expected to spend a minimum of three to six hours per week to finish the course modules.
The ‘Text Analytics 2: Visualizing Natural Language Processing’ is a self-paced learning program and the students can study independently with the curriculum instructed by faculty from the University of Canterbury such as Jonathan Dunn(Lecturer), Jeanette King(Professor), Tom Coupe(Associate Professor), and Girish Prayag(Professor). The participants will receive a certificate that can be shared online for the benefit of career advancement if they choose the verified mode by paying the course fee. They can also join the self-paced programme free of cost and get limited access to the programme.
The Highlights
- Online mode
- Self-Study
- Six weeks
- 3-6 hours per week
- Free learning
- Video transcripts
- Introductory level program
- Faculty from UC
- Shareable certificate
Programme Offerings
- course videos
- Modules
- Graded Assignments
- tests
- Video transcripts
- English Medium Of Instruction
- Self-paced learning
- course certificate
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 25793 | yes | University of Canterbury, Christchurch |
The ‘Text Analytics 2: Visualizing Natural Language Processing’ certification fee is paid to access the verified track with the certificate and access to the graded assessments.
Text Analytics 2: Visualizing Natural Language Processing fee structure
Audit Track | Nil |
Verified Track | Rs 25,793 |
Eligibility Criteria
Certificate qualifying details
The candidates learning in the ‘Text Analytics 2: Visualizing Natural Language Processing’ certification by Edx will become eligible for the online shareable certificate after successfully completing the course modules, graded assignments, and tests.
What you will learn
The ‘Text Analytics 2: Visualizing Natural Language Processing’ certification syllabus equips the students to gain familiarity with the following aspects by the end of the training,
- Hands-on experience with document similarity and topic models to process huge amounts of data sets.
- Interpretation and visualization of text analytics that includes statistical significance testing.
- Analyze the ethical and scientific foundations of new applications for the purpose of text analytics.
Who it is for
The ‘Text Analytics 2: Visualizing Natural Language Processing’ online certification training is organized for students, individuals, and industry professionals who are keen on enhancing their knowledge of text analytics and visualization.
Admission Details
The learners who wish to join the ‘Text Analytics 2: Visualizing Natural Language Processing’ certification course should register themselves through the Edx website.
Step 1: Get to the course page using the link,
https://www.edx.org/course/text-analytics-2-visualizing-natural-language-processing
Step 2: Find the ‘Enroll Now’ option.
Step 3: Fill in the details for registration.
Step 4: Choose the mode of study.
Step 5: Pay the course fee and join the course.
Application Details
The applicants for the ‘Text Analytics 2: Visualizing Natural Language Processing’ certification classes should register by entering their basic information such as name, email address, user name, and account password or can sign in to Edx using their Facebook, Google, or Apple IDs.
The Syllabus
- Learn how to use machine learning to find out which words and documents have similar meanings.
- Learn how to explain a model using visualization and significance testing.
- Learn how to apply computational linguistics to new problems and new data sets.
Instructors
University of Canterbury, Christchurch Frequently Asked Questions (FAQ's)
Yes, you can learn the course for free.
The course can be completed in six weeks.
There are no prerequisites for this course.
The course is provided by Edx and the University of Canterbury.
You will have to spend at least 3-6 hours per week.