Explores the principles, techniques, and best practices of data annotation, equipping one with the skills to effectively label, annotate, and manage data for machine learning and AI Algorithms. 

Importance of Data Annotation Skills

Data Annotation is a rapidly growing and vital career in data science and artificial intelligence.

  1. It is the process of labeling or tagging data with additional information that makes it more meaningful and valuable for machine learning algorithms.
  2. It involves adding metadata to data, including labeling, tagging, or categorizing various aspects of the data, such as objects, features, and attributes.

Key Focus Areas of the Advanced Data Annotation Program

  • Data annotation and AI Intro.
  • Human & Technical Skills for Data Annotation 
  • Lidar Annotation
  • Video Annotation
  • 3D Cuboid Annotations

          and much more…

Enjoy the freedom of flexible work options in an ever-expanding industry.

As a skilled data annotator, you’ll have the flexibility to work remotely or on-site, allowing you to tailor your work environment to suit your lifestyle preferences.

Remote

You'll have the flexibility to work remotely or on-site, allowing you to tailor your work environment to suit your lifestyle preferences.

Data Annotation Career progression

Remote Work – Many data annotation tasks can be performed remotely, offering flexibility & the possibility of working from anywhere in the world.

Career Progression – It is the first step to becoming a data engineer.

 

How much does it cost ?

The Program Fee is  available from our ethical student financing program through our partnership with Chancen International

For more information please contact:

  • recruitment@nextstepfdn.org
    +254 792 791 586
    +254 729 303 826

How to Apply

Get started by completing this online registration form and someone from our team will follow up with you.

Visit this link to register for the Data Annotation program-

PS: (Select “Chancen International” at Partner section of Application Form)