Data Annotation and Preparation

Data Annotation Short Bootcamp

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Artificial Intelligence and Data Science, are the two most important technologies in the world today. And jobs related to these are obviously in demand. The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. Not only find patterns in data but also the data itself for the success of the particular business.

Here comes web scraping. Web scraping is an important skill for any data scientist to have in their toolbox. Web scraping can be used to collect data about products for sale, user posts, images, and pretty much anything else that is useful on the web.

In this course, we aim to make students able to start to learn each and everything involved in web scrapping and will go through them the automotive boots for this purpose. After completing this course, they will be able to scrap data using different techniques, and can earn a handsome amount online or onsite, and will plunge into the field of Data Science or AI.

Prerequisite knowledge

This course requires good understanding of English and the minimum education level should be Metric/FA / FSc / DAE / ICT and above. Good understanding of computer applications would be preferred.

Skills Proficiency

On completion of this training program, the trainee’s skill profile will include:
  1. Working on different types of annotations – image, video, and text
  2. Will learn techniques used to annotate datasets for higher accuracy
  3. Provide services to any data collection business – e.g., agencies doing research, marketing, census, analytics, e-commerce, etc
  4. Earn online doing by doing web scraping and automation jobs

What we offer

Training Material

Projects involved

Jobs opportunities

On completion of this training program, the trainee will have following career options:
  1. Data Annotator
  2. Data Labeler
  3. Digital Data Researcher / Analyst
  4. Freelancer (for dataset development, annotation & automation)

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