Digital Technology 29
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Data Analytics & Management Data Science COM SCI X 450.3
Big Data Management
4.0 units This course introduces tools for distributed storage and data processing in an open-source framework. It covers NoSQL, the core components of Hadoop, and an overview of Hive. The extent of data being produced and stored by organizations is increasing. In fact, IDC has projected to reach 165 zetta bytes by 2025. Organizations understand that being able to extract and leverage value and gain actionable insights from this big data can give them a tremendous competitive advantage. In this course, students learn tools for distributed storage and data processing to an open-source framework. This course addresses distributed storage and large data set processing focusing on architectures and technologies. Prerequisite(s): COM SCI X 450.1 Introduction to Data Science or prior knowledge in R and Python recommended, or consent of instructor. Reg# 394936 Fee: $1,095 No refund after 1 Jan. MOnline Jan. 8-Mar. 18 Enrollment limited. Enrollment deadline: Jan. 14. 7 & Connie Outwater, Master of Science, Data Analytics specialist, Google Reg# 394935 Fee: $1,095 No refund after 14 Jan. X In-Person 11 mtgs Wednesday, 6:30-9:30pm, Jan. 10-Mar. 20 UCLA Extension Lindbrook Center: 10920 Lindbrook Dr. Enrollment limited. Enrollment deadline: Jan. 16. 7 & Francesco Fabbrocino, MS, Computer Science, UCLA
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COM SCI X 450
COM SCI X 450.1
4.0 units In this this hands-on, exercise-driven course, students will learn the role of data science in decision-making, basic statistics, entry-level Python programming, and data analysis, using tools such as Excel, SPSS, and Python. Designed for absolute beginners, business analysts, and non-technical managers, the curriculum includes problem-solving exercises using pencils, paper, and laptops for assignments during and outside of the class. Prerequisite(s): There are no prerequisites for this course. Reg# 394929 Fee: $1,095 No refund after 12 Jan. MOnline Jan. 8-Mar. 18 Enrollment limited. Enrollment deadline: Jan. 14. 7 & Leon Shpaner Reg# 394928 Fee: $1,095 No refund after 22 Jan. X In-Person 11 mtgs Tuesday, 6-9pm, Jan. 9-Mar. 19 UCLA: School of Public Affairs Bldg. Enrollment limited. Enrollment deadline: Jan. 15. 7 & Stefan Lin
4.0 units Get an introduction to the foundational concepts and techniques behind data science and its applications. Students will learn about programming languages including Python and R, and receive a primer on natural language processing, big data management, and visualization techniques. The course will conclude with an overview of data modeling and machine learning algorithm development. Prerequisite(s): 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 Data Science Fundamentals before taking COM SCI X 450.1 Introduction to Data Science. Reg# 394931 Fee: $1,095 No refund after 12 Jan. MOnline Jan. 8-Mar. 18 Enrollment limited. Enrollment deadline: Jan. 14. 7 & Ali El-Annan Reg# 394930 Fee: $1,095 No refund after 22 Jan. X In-Person 10 mtgs Tuesday, 6-9:30pm, Jan. 9-Mar. 12 UCLA Extension Lindbrook Center: 10920 Lindbrook Dr. Students are required to bring a laptop to class. Enrollment limited. Enrollment deadline: Jan. 15. 7 & Daniel D. Gutierrez, an established leader in the field of data science with specialties in machine learning, AI, deep learning, predictive analytics, data visualization, and analysis. Founder of AMULET Analytics to provide leading-edge data science consulting for companies in a broad cross-section of industries Reg# 394932 Fee: $1,095 No refund after 29 Jan. X In-Person 10 mtgs Monday-Friday, 9am-12pm, Feb. 5-16 UCLA Extension Gayley Center: 1145 Gayley Ave. Enrollment limited. Enrollment deadline:. 7 & William Yu, PhD; economist, UCLA Anderson Forecast; visiting assistant professor of UCLA Anderson School of Management.
Data Science Fundamentals
COM SCI X 450.2
Exploratory Data Analysis and Visualization
4.0 units Data science involves uncovering key intelligence by analyzing historical data to learn what happened in the past, and predictive analytics to forecast what may happen in the future. This iterative process is called exploratory data analysis (EDA). Effective data visualization is also an integral component of the process, and quickly becoming a top business intelligence and analytics technology. In this course, you’ll learn skills including EDA, data analysis techniques, and data exploration, with a specific focus on visualization utilizing Tableau. Recommended: COM SCI X 450.1 Introduction to Data Science or equivalent experience. Reg# 394933 Fee: $1,095 No refund after 12 Jan. MOnline Jan. 8-Mar. 18 Enrollment limited. Enrollment deadline: Jan. 14. 7 & Bianca Cung Reg# 394934 Fee: $1,095 No refund after 21 Jan. Hybrid (In-Person) 4 mtgs Jan. 8-Mar. 18 Monday, 6-9pm, Jan. 8-Feb. 19 UCLA: Math Sciences Enrollment limited. Enrollment deadline: Jan. 14. 7 & Benjamin Winjum
Introduction to Data Science