Knowledge Graph solution development using TigerGraph
What you'll learn
- You will be able to understand and document the use case for knowledge graph solution
- You will be able to Design a Knowledge Graph solution
- You will be able to Design / extract data from Knowledge Graph data sources.
- You will be able to Design / Build key knowledge graph solution components and analytics
- Finally, You will be able to Prototype a graph analytics experience and document your understanding on Knowledge Graph Insights using a class assignment
- We strongly recommend you to start on "Knowledge Graph - Benefit Case" course before starting this course. Knowledge Graph - Benefit Case is also available on Udemy.
"Rapid Prototyping of Knowledge Graph Solutions using TigerGraph" course will help you strategize knowledge graph use cases and help you build or prototype a use case for your knowledge graph engagement. This course includes
- How to define Graph Use Case
- How to set up Sandbox using TigerGraph for your Graph use case
- How to develop and execute structured graph queries
- How to define elastic or higher level graph representation
- Finally how to connect your graph solution with other solution components using Python.
Who this course is for:
- Management, strategy and business analyst professionals
- Architects, technical leads and system analysts from IT organization
- Senior year undergraduate and graduate students in Business, Analytics, and IT
- Vendors, consultants and service providers for Graph Analytics
Ms. Neena Sathi is a Principal at Applied AI Institute, specializing in developing hands-on interactive solution and training contents (videos and class lectures) for various AI and Analytics related topics. She is also a Lecturer at University of California Irvine, where she teaches many courses on Generative AI, Conversation AI and Business Analytics. She had worked as Director/Data Scientist at KPMG Lighthouse labs with specialization in developing / integrating AI solutions associated with enhancing customer experience, back office automation and risk and compliance. Neena is an experienced professional with 30+ years of experience in architecting, designing, and implementing AI and Analytics application for Healthcare, Telco, Media, Retail, Public Services and Accounting Services organizations. She drives AI solutions in prototype to production-level system development for internal and external use cases. She has been affiliated with many universities (Carnegie Mellon University, University Of Phoenix, MIT and University of California, Irvine) for advanced research, teaching and training/curriculam/content development related with many AI and Analytics related topics
She is Master certified integration architect from IBM and Open Group as well as certified Project management professional (PMP) from Project management institute. She is also certified in many Cloud and Cognitive technologies. She has widely presented and published many papers in AAAI, IEEE, WCF, ECF, IBM Information on Demand, IBM Insight, World of Watson, IBM Developer Works and many other journals.