Tuition Fee
USD 1,095
Per course
Start Date
Medium of studying
Blended
Duration
2 months
Program Facts
Program Details
Degree
Courses
Major
Data Management | Data Science | Database Management
Area of study
Information and Communication Technologies
Education type
Blended
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
USD 1,095
Intakes
| Program start date | Application deadline |
| 2024-04-01 | - |
| 2024-06-01 | - |
| 2024-06-24 | - |
| 2024-09-01 | - |
About Program
Program Overview
This 10-week course introduces the tools and concepts of distributed storage and data processing in an open-source framework. It covers NoSQL, the core components of Hadoop, and an overview of Hive. Students will gain a high-level understanding of the Hadoop infrastructure, learn different types of NoSQL data stores, and explore different ecosystems within Hadoop. Through hands-on exercises and a group project, students will apply the concepts learned in class to real-world problems.
Program Outline
Outline:
- Overview: 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.
- Objectives: > * Understand the basics of the history and current landscape of big data > * Gain a high-level understanding of the Hadoop infrastructure > * Create a business solution with a group, using Hadoop framework > * Learn different types of NoSQL data stores > * Explore different ecosystems within Hadoop > * Get basic hands-on experience with Hadoop
- Structure: > * The course will be divided into 10 sessions, each covering a different aspect of big data management. > * Sessions will include lectures, discussions, and hands-on exercises. > * Students will also work on a group project to apply the concepts learned in class to a real-world problem.
- Schedule: > * The course will meet once a week for 10 weeks. > * Class will be held from 6:30pm to 9:30pm PT.
- Modules: >
- Module 1: Introduction to Big Data >> * Overview of the history and current landscape of big data >> * Challenges and opportunities of big data >> * Different types of big data >
- Module 2: Hadoop Overview >> * The Hadoop Distributed File System (HDFS) >> * The Hadoop MapReduce framework >> * The Hadoop YARN resource manager >
- Module 3: NoSQL Databases >> * Introduction to NoSQL databases >> * Different types of NoSQL databases >> * Advantages and disadvantages of NoSQL databases >
- Module 4: Hive Overview >> * Introduction to Hive >> * HiveQL language >> * Using Hive to query data in HDFS >
- Module 5: Hands-on Hadoop Project
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About University
UCLA Extension
Overview:
UCLA Extension is a renowned continuing education institution affiliated with the University of California, Los Angeles (UCLA). It offers a wide range of courses, certificates, and specializations designed for professional development, career advancement, and personal enrichment.
Services Offered:
UCLA Extension provides a comprehensive suite of services for its students, including:
Courses:
Hundreds of open-enrollment courses are available in various fields of study, delivered online, in-person, or in a hybrid format.Certificates:
Students can earn certificates in specialized areas, demonstrating their expertise and enhancing their career prospects.Specializations:
Short series of courses designed to quickly equip students with in-demand skills and knowledge in focused areas.Student Services:
UCLA Extension offers comprehensive support services, including enrollment assistance, financial aid, scholarships, transcripts, career services, and international student support.Corporate Education:
Custom programs and corporate training solutions are available to meet the professional development needs of organizations.Student Life and Campus Experience:
Key Reasons to Study There:
UCLA Affiliation:
Students benefit from the prestige and reputation of UCLA, a world-class research university.Industry Experts:
Courses are taught by experienced professionals and industry leaders, providing practical and relevant knowledge.Flexible Learning:
UCLA Extension offers a variety of learning formats, including online, in-person, and hybrid options, catering to diverse schedules and preferences.Career Advancement:
Certificates and specializations can enhance career prospects and open doors to new opportunities.Personal Enrichment:
Courses and programs cater to personal interests and provide opportunities for lifelong learning.Academic Programs:
UCLA Extension offers a wide range of academic programs across various fields, including:
Accounting & Finance
Architecture & Interior Design
Business & Management
Communications
Design & Arts
Digital Technology
Education
Engineering
Entertainment
Environmental Studies & Public Policy
Health Care & Counseling
Humanities & Social Sciences
Landscape Architecture & Horticulture
Legal Programs
Real Estate
Sciences & Math
Writing
Other:
UCLA Extension is accredited by the Western Association of Schools and Colleges (WASC), ensuring the quality and rigor of its programs.
Total programs
1698
Admission Requirements
Outline:
- Overview: 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.
- Objectives: > * Understand the basics of the history and current landscape of big data > * Gain a high-level understanding of the Hadoop infrastructure > * Create a business solution with a group, using Hadoop framework > * Learn different types of NoSQL data stores > * Explore different ecosystems within Hadoop > * Get basic hands-on experience with Hadoop
- Structure: > * The course will be divided into 10 sessions, each covering a different aspect of big data management. > * Sessions will include lectures, discussions, and hands-on exercises. > * Students will also work on a group project to apply the concepts learned in class to a real-world problem.
- Schedule: > * The course will meet once a week for 10 weeks. > * Class will be held from 6:30pm to 9:30pm PT.
- Modules: >
- Module 1: Introduction to Big Data >> * Overview of the history and current landscape of big data >> * Challenges and opportunities of big data >> * Different types of big data >
- Module 2: Hadoop Overview >> * The Hadoop Distributed File System (HDFS) >> * The Hadoop MapReduce framework >> * The Hadoop YARN resource manager >
- Module 3: NoSQL Databases >> * Introduction to NoSQL databases >> * Different types of NoSQL databases >> * Advantages and disadvantages of NoSQL databases >
- Module 4: Hive Overview >> * Introduction to Hive >> * HiveQL language >> * Using Hive to query data in HDFS >
- Module 5: Hands-on Hadoop Project
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