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  • Berkeley Global

Data Visualization

COMPSCI X465.1

49692979
Delivery Options Online

Learn to work with data visualization tools in a course that is ideal for working professionals and students. You also learn how to use data characterization to build effective data visualizations. The course curriculum weaves together theoretical and practical elements to support a holistic approach to creating visualizations. You are given a choice of tools to use on various data sets through exercises and lecture examples. You must actively participate in discussions and complete quizzes and homework to succeed in this course. The course capstone is a final project that is tailored to each student's particular skill-development goals. That project can then be added to your growing portfolio of work.

Prerequisites:

Programming experience or interactions with data on a technical side is helpful, but not required.

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Sections

Section 003

Start Anytime

Type: Online, Start Anytime

Instructor:

  • Ali El-Annan

Cost: $995.00

See section 003 Details

Type Online, Start Anytime

Dates
Start Now, you have 180 days to complete this course once enrolled.

Delivery Options

Online

Available for Credit

2 semester units

Section Notes

This continuous enrollment course begins when you enroll. You have a minimum of 60 days and a maximum of 180 days to complete the course. Students must score 70% or more on the final exam / project to pass this course. 

Summer enrollment opens on March 20!

This course applies to the following programs:

Certificate Program in Data Science

Expand or collapse section

Programming

  • Introduction to R: Data Exploration and Visualization
  • Python for Data Analysis and Scientific Computing
  • Introduction to Data Science
  • Introduction to Data Science Using R

Machine Learning

  • Introduction to Machine Learning Using Python
  • Machine Learning and Deep Learning With Spark
  • Practical Machine Learning (With R)
  • Machine Learning With TensorFlow

Core Courses

  • Practical Statistics for Data Scientists Using R
  • Introduction to Big Data
  • Data Science Principles and Practice Using Python
  • Data Visualization

Electives

  • Introduction to Databases
  • Introduction to SQL

Learn More About this Program

Instructional Types

Live Online
Live Online courses provide an interactive learning experience with scheduled synchronous online sessions held via Zoom video conferencing (Pacific Time). Learn more about the Live Online format.
Online, Start Anytime
Continuous enrollment course begins when you enroll. You have a minimum of 90 days and a maximum of 180 days to complete the course.
Online, Fixed Date
Enroll in this course by its start date and complete it by its specified end date. There are no live sessions, but plenty of opportunities to collaborate with your classmates and instructor.
Classroom
Take classes in-person at one of our buildings or partner locations.

English Language Proficiency Requirements

All of our courses are taught in English. If English is not your first language, please use the following test scores as guides in order to be successful:

  • TOEFL: 90
  • IELTS Academic Format: 7
  • DAAD: C1
  • TEM-4 or TEM-8: Level 70
  • Duolingo: 115

Note: You do not need to submit test scores.

Extension

1995 University Ave., Suite 130

Berkeley, CA 94704-7000

extension@berkeley.edu

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The University of California, Berkeley, is accredited by the Western Association of Schools and Colleges (WASC). UC Berkeley Extension—like all other UC Berkeley schools, colleges and departments—is accredited by WASC through the University.

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Course Fee

Ali El-Annan

Ali El-Annan, B.S. in Electrical Engineering and Computer Science from UC Berkeley has taught subjects ranging from data science, data, visualization, computer science to engineering. He has led and built teams across institutions from finance, risk and technology working across multiple departments and divisions. Ali has experience managing multi-billion dollar portfolios, constructing risk strategies and managing various technology and business roadmaps. He currently leads the technology department at a financial institution that includes various divisions such as analytics, data science and more.

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