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AI– Based Patent Landscape Analysis

   Author: Baturi   |   08 June 2026   |   Comments icon: 0


AI– Based Patent Landscape Analysis
Published 5/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 41m | Size: 1.02 GB
For anyone who wants to work as IP Professional or Patent Researcher


What you'll learn


Introduction to Patent Landscape Analysis and What will be Covered
Case Study 1 - Surgical Staplers using Traditional Patent Searching Method
AI Technologies
5-Step Methodology
Case Study. 2 - Electric Vehicle. Batteries using AI Patent Searching Method
Best Practices

Requirements


No prerequisites

Description


Course Overview
In today's rapidly evolving technological ecosystem, staying ahead of innovation requires advanced tools and modernized methodologies. This fundamental course onPatent Landscape Analysis bridges the gap between traditional intellectual property (IP) practices and cutting-edge artificial intelligence. Designed as a comprehensive, future-focused guide, the course introduces participants to the core concepts of mapping, analyzing, and visualizing patent data to uncover strategic insights, spot emerging technology trends, and identify competitive threats.
Curriculum & Hands-On Case Studies
The curriculum is carefully structured to take learners from foundational principles to advanced analytical applications. A key highlight of this course is its practical approach, anchored bytwo real-world case studies that directly contrast older and newer paradigms
-Case Study 1: Traditional Patent Search Methods: Unpacking the standard workflows involving precise Boolean operators, specific international classification codes (such as CPC and IPC), and manual data cleaning.
-Case Study 2: AI-Based Patent Search & Analysis: Leveraging semantic search, machine learning algorithms, large language models (LLMs), and automated clustering to accelerate data synthesis.
By comparing these two methodologies side-by-side, learners will gain a first-hand understanding of how emerging AI technologies significantly reduce search noise, uncover hidden prior art, and dramatically speed up time-to-insight.
Target Audience
This course is engineered to accommodate a diverse range of educational and professional backgrounds
-Students & Beginners: Individuals looking to break into the intellectual property field and build a robust, future-proof foundation.
-IP Professionals & Patent Attorneys: Practitioners who want to optimize their current search workflows, reduce manual overhead, and responsibly integrate AI tools into their legal or corporate frameworks.
-Patent Researchers & R&D Managers: Scientists and analysts aiming to track competitor movements and align their innovation strategies with global patent trends.
Whether you are completely new to intellectual property or an experienced researcher looking to upskill, this course equips you with the tools necessary to lead AI-driven patent analytics with confidence.

Who this course is for


This course is ideal for Inventors, R&D Managers, Students, Legal Professionals, and anyone involved in the Innovation Process or Intellectual Property Management. Whether you are new to Patent Landscape Analysis or looking to refine your skills, this course will provide you with the knowledge and tools you need. Join this course today and make yourself a part of the booming and highly rewarding IP industry.

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