Cebu, Apple One Equicom Tower

11 Floor, Apple One - Equicom , Cebu Ciry, Philippines, 6000

The AppleOne Equicom Tower business center is in a mixed-use development in Cebu City. AppleOne Tower is a 17-Floor building with residential units located at the top of the building, commercial office units and 4 levels of parking spaces. It is a PEZA accredited building catering to many BPO and KPO companies. The business centre is conveniently located with good road links and close to Mactan International airport and is located close to major shopping malls and entertainment facilities. Major corporates based in Cebu City include JP Morgan Chase, NEC, Olympus, Taiyo yuden and Timex.

Explore Our Courses

Milvus: Open-Source Vector Database for AI Applications

 21 Hours
This instructor-led, live training in Cebu (online or onsite) is aimed at beginner-level to intermediate-level data scientists and software developers who wish to learn about Milvus and its practical applications in various AI scenarios. By the end of this training, participants will be able to:
  • Understand the architecture and features of Milvus.
  • Implement vector databases in different AI applications.
  • Perform similarity searches with high accuracy and speed.
  • Apply Milvus to real-world AI challenges.
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Pinecone: Vector Database Solutions for AI

 21 Hours
This instructor-led, live training in Cebu (online or onsite) is aimed at beginner-level to intermediate-level data scientists and software developers who wish to learn how to apply Pinecone to various AI scenarios, from semantic search to personalization. By the end of this training, participants will be able to:
  • Understand the architecture and features of Pinecone.
  • Implement vector databases in different AI applications.
  • Perform similarity searches with high accuracy and speed.
  • Apply Pinecone to real-world AI challenges.
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Mastering Vector Databases for Scalable AI Solutions

 14 Hours
This instructor-led, live training in Cebu (online or onsite) is aimed at intermediate-level to advanced-level data scientists and machine learning engineers who wish to master the use of vector databases for scalable, high-performance AI applications. By the end of this training, participants will be able to:
  • Understand the principles of vector databases.
  • Learn techniques for creating and managing vector embeddings.
  • Explore indexing strategies for high-dimensional data.
  • Develop skills for performing efficient similarity searches.
  • Apply vector database knowledge to machine learning projects.
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Introduction to Vector Databases

 14 Hours
This instructor-led, live training in Cebu (online or onsite) is aimed at beginner-level software developers and database administrators who wish to learn the basics of vector databases, including their structure, operation, and use cases. By the end of this training, participants will be able to:
  • Understand the concept and purpose of vector databases.
  • Recognize the differences between vector and traditional databases.
  • Learn basic techniques for creating and managing vector data.
  • Perform simple similarity searches.
  • Appreciate the role of vector databases in AI applications.
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Upcoming Courses

Mastering Vector Databases for Scalable AI Solutions

2025-05-12 09:30
14 hours
Cebu, Apple One Equicom Tower
105356 PHP (Online)
109656 PHP (Classroom)

Mastering Vector Databases for Scalable AI Solutions

2025-05-26 09:30
14 hours
Cebu, Apple One Equicom Tower
105356 PHP (Online)
109656 PHP (Classroom)

Introduction to Vector Databases

2025-06-09 09:30
14 hours
Cebu, Apple One Equicom Tower
105356 PHP (Online)
109656 PHP (Classroom)

Pinecone: Vector Database Solutions for AI

2025-06-23 09:30
21 hours
Cebu, Apple One Equicom Tower
158034 PHP (Online)
164484 PHP (Classroom)

Pinecone: Vector Database Solutions for AI

2025-07-07 09:30
21 hours
Cebu, Apple One Equicom Tower
158034 PHP (Online)
164484 PHP (Classroom)

Milvus: Open-Source Vector Database for AI Applications

2025-07-21 09:30
21 hours
Cebu, Apple One Equicom Tower
158034 PHP (Online)
164484 PHP (Classroom)

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