Description
Data Annotation for AI/ML Bootcamp is a course on how to prepare and label high-quality datasets for AI and machine learning applications, published by Udemy Online Academy. Suitable for data annotation enthusiasts, new AI/ML professionals, QA professionals, and anyone looking to get into AI, this course explains why accurately labeled data is essential for training reliable machine learning models and views annotation quality as a fundamental factor in AI performance, not a sideline administrative task. Learners begin by understanding the core concepts, terminology, and purpose of data annotation within the broader AI/ML pipeline, and learn why models are only as good as the labeled data they are trained on. This fundamental understanding shapes how learners approach each subsequent annotation task, connecting labeling decisions to their subsequent impact on model behavior. A significant portion of the bootcamp focuses on image annotation, where learners practice a range of techniques including bounding boxes, polygons, keypoints, ellipses, cuboids, and pixel-level masks.
Covering this range of techniques helps learners understand which annotation style is appropriate for which type of machine vision task, rather than assuming a uniform approach regardless of context. The course then turns to video annotation, teaching learners how to track objects and shapes across video frames, including more advanced capabilities such as merging, splitting, and linking tracked elements as objects move, appear or disappear, or interact within a scene. These skills address data-specific challenges that static image annotation does not cover. Text annotation is considered a standalone discipline, and learners perform classification, named entity recognition, and sequence labeling tasks, essential grounding for natural language processing models. Throughout the bootcamp, learners gain hands-on experience with industry-standard annotation tools and real-world workflows, reflecting how annotation work is actually structured in professional AI/machine learning pipelines. By the end, learners will be equipped with practical and transferable annotation skills across images, video, and text.
What you will learn in Data Annotation for AI/ML Bootcamp:
- Understand the core concepts, terminology, and purpose of data annotation in the AI/ML pipeline
- Apply annotation techniques for images, including bounding boxes, polygons, keypoints, ellipses, cuboids, and pixel level masks
- Track objects and shapes across video frames, including advanced track and merge/split/join functionality
- Perform text annotation tasks such as classification, named entity recognition, and sequence labeling
- and …
Course specifications
Publisher: Udemy
Instructors: Georgi Smarts
Language: English
Level: Introductory to Advanced
Number of Lessons: 50
Duration: 3h 14m
Course topics
Data Annotation for AI/ML Bootcamp Prerequisites
No prior data annotation or coding experience needed. Every tool and workflow is taught from the ground up
A general interest in AI and machine learning is helpful, but no formal ML background is required
Pictures
Data Annotation for AI/ML Bootcamp introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
1.5 GB