About this Course

49,448 recent views

Learner Career Outcomes

50%

started a new career after completing these courses

67%

got a tangible career benefit from this course

29%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 31 hours to complete
English
Subtitles: English, Korean

Skills you will gain

Information Retrieval (IR)Document RetrievalMachine LearningRecommender Systems

Learner Career Outcomes

50%

started a new career after completing these courses

67%

got a tangible career benefit from this course

29%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 31 hours to complete
English
Subtitles: English, Korean

Offered by

University of Illinois at Urbana-Champaign logo

University of Illinois at Urbana-Champaign

Start working towards your Master's degree

This course is part of the 100% online Master in Computer Science from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

Syllabus - What you will learn from this course

Content RatingThumbs Up90%(2,525 ratings)Info
Week
1

Week 1

2 hours to complete

Orientation

2 hours to complete
2 videos (Total 15 min), 6 readings, 2 quizzes
2 videos
Course Introduction Video11m
6 readings
Welcome to Text Retrieval and Search Engines!10m
Syllabus10m
About the Discussion Forums10m
Updating your Profile10m
Social Media10m
Course Errata10m
2 practice exercises
Orientation Quiz15m
Pre-Quiz30m
4 hours to complete

Week 1

4 hours to complete
6 videos (Total 94 min), 1 reading, 2 quizzes
6 videos
Lesson 1.2: Text Access9m
Lesson 1.3: Text Retrieval Problem26m
Lesson 1.4: Overview of Text Retrieval Methods10m
Lesson 1.5: Vector Space Model - Basic Idea9m
Lesson 1.6: Vector Space Retrieval Model - Simplest Instantiation17m
1 reading
Week 1 Overview10m
2 practice exercises
Week 1 Practice Quiz1h
Week 1 Quiz1h
Week
2

Week 2

4 hours to complete

Week 2

4 hours to complete
6 videos (Total 102 min), 1 reading, 2 quizzes
6 videos
Lesson 2.2: TF Transformation9m
Lesson 2.3: Doc Length Normalization18m
Lesson 2.4: Implementation of TR Systems21m
Lesson 2.5: System Implementation - Inverted Index Construction18m
Lesson 2.6: System Implementation - Fast Search17m
1 reading
Week 2 Overview10m
2 practice exercises
Week 2 Practice Quiz1h
Week 2 Quiz1h
Week
3

Week 3

7 hours to complete

Week 3

7 hours to complete
6 videos (Total 75 min), 2 readings, 3 quizzes
6 videos
Lesson 3.2: Evaluation of TR Systems - Basic Measures12m
Lesson 3.3: Evaluation of TR Systems - Evaluating Ranked Lists - Part 115m
Lesson 3.4: Evaluation of TR Systems - Evaluating Ranked Lists - Part 210m
Lesson 3.5: Evaluation of TR Systems - Multi-Level Judgements10m
Lesson 3.6: Evaluation of TR Systems - Practical Issues15m
2 readings
Week 3 Overview10m
Programming Assignments Overview10m
2 practice exercises
Week 3 Practice Quiz1h
Week 3 Quiz1h
Week
4

Week 4

4 hours to complete

Week 4

4 hours to complete
7 videos (Total 88 min), 1 reading, 2 quizzes
7 videos
Lesson 4.2: Statistical Language Model17m
Lesson 4.3: Query Likelihood Retrieval Function12m
Lesson 4.4: Statistical Language Model - Part 112m
Lesson 4.5: Statistical Language Model - Part 29m
Lesson 4.6: Smoothing Methods - Part 19m
Lesson 4.7: Smoothing Methods - Part 213m
1 reading
Week 4 Overview10m
2 practice exercises
Week 4 Practice Quiz1h
Week 4 Quiz1h

Reviews

TOP REVIEWS FROM TEXT RETRIEVAL AND SEARCH ENGINES

View all reviews

About the Data Mining Specialization

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization....
Data Mining

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, 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. Learn more.

  • This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

More questions? Visit the Learner Help Center.