Introduction to Data Science

COM SCI X 450.1

This course introduces students to the evolving domain of data science and the foodchain of knowledge domains involved in its application. Students learn a range of challenges and questions that data science helps address.

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What you can learn.

Configure a data science notebook server
Prepare a well-defined problem statement for a new problem
Learn the R programming language
Be introduced to machine learning

About this course:

This course introduces students to the evolving domain of data science and the food chain of knowledge domains involved in its application. Students learn a wide range of challenges, questions, and problems that data science helps address in different domains, including social sciences, finance, health and fitness, and entertainment. The course addresses the key knowledge domains in data science, including data development and management, machine learning and natural language processing, statistical analysis, data visualization, and inference. The course includes case studies that require students to work on real-life data science problems.

Prerequisites

Students are expected to have basic Python programming and basic statistics skills. If you do not have these skills, we suggest taking COM SCI X 450.00 Data Science Fundamentals before taking COM SCI X 450.1 Introduction to Data Science.

Winter 2022 Schedule

January 3 - March 7

This section has no set meeting times.

Enrollment Closed

See Details

Instructor: Ali El-Annan

383454

Fee:

$995.00

Online

Updating...

See Details

Notes

Enrollment limited. Enrollment deadline: January 9, 2022. Internet access required. Materials required.

Refund Deadline

No refunds after January 07, 2022

Course Requirements

Internet access required to retrieve course materials.

January 3 - March 7

This section has no set meeting times.

Enrollment Closed

See Details

Instructor: Ali El-Annan

386322

Fee:

$995.00

Online

Updating...

See Details

Notes

Enrollment limited. Enrollment deadline: January 9, 2022. Internet access required. Materials required.

Refund Deadline

No refunds after January 07, 2022

Course Requirements

Internet access required to retrieve course materials.

January 4 - March 8

Tuesday 6:00PM - 9:30PM PT

Enrollment Closed

See Details

Instructor: Daniel D. Gutierrez

383456

Fee:

$995.00

Remote

Location: Remote Classroom

Updating...

See Details

Notes

Students are required to bring a laptop to class.

Enrollment limited. Enrollment deadline: January 10, 2022. Internet access required. Materials required.

Refund Deadline

No refunds after January 17, 2022

Course Requirements

Internet access required to retrieve course materials.

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

ISBN 1634620968

(Optional) The Art of R Programming: A Tour of Statistical Software Design

ISBN 9781593273842

Schedule

Type

Date

Time

Location

Discussion

Tue Jan 4, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Jan 11, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Jan 18, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Jan 25, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Feb 1, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Feb 8, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Feb 15, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Feb 22, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Mar 1, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

Discussion

Tue Mar 8, 2022

6:00PM PT - 9:30PM PT

Remote Classroom

January 3 - March 14

Monday 6:00PM - 9:00PM PT

Enrollment Closed

See Details

Instructor: Benjamin Winjum

385058

Fee:

$995.00

In-Person

Location: UCLA Extension Lindbrook Center in Westwood

Updating...

See Details

Notes

Students are required to bring a laptop to class.

Enrollment limited. Enrollment deadline: January 10, 2022. Internet access required. Materials required.

Refund Deadline

No refunds after January 16, 2022

Course Requirements

Internet access required to retrieve course materials.

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

ISBN 1634620968

(Optional) The Art of R Programming: A Tour of Statistical Software Design

ISBN 9781593273842

Schedule

Type

Date

Time

Location

Discussion

Mon Jan 3, 2022

6:00PM PT - 9:00PM PT