Neo4j Graph Data Science and LLM

Topic 1 Introduction to Neo4J Graph Data Science

• Overview of Neo4j Graph Data Science (GDS)
• How GDS Works
• Graph Catalog
• Cypher Projections

Topic 2 Graph Algorithms

• Path Finding
• Community Detection
• Node Embedding
• Similarity
• Shortest Paths with Cypher
• Weighted Shortest Paths

Topic 3 Graph Machine Learning

• Overview of Graph Machine Learning
• Node Classification Pipeline
• Link Prediction
• Exploratory Analysis
• Handling Missing Values
• Encoding Categorical variables
• Dimensionality reduction
• KMeans algorithm
• Feature normalization
• Optimizing KMeans algorithm
• Nearest neighbor graph
• kNN algorithm

Topic 4 Neo4j and LLM

• Introduction to Neo4j with Generative AI
• Avoiding Hallucination
• Grounding LLMs
• Vectors & Semantic Search
• Vector Indexes
• Introduction to Langchain
• Large Lauguage Models (LLM)
• Chains
• Memory
• Agents
• Retrievers
• Using LLMs for Query Generation
• The Cypher QA Chain
• Conversational Agent

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

• Data Scientist specializing in Graph Databases
• Neo4j Database Administrator
• Graph Data Analyst
• AI and Machine Learning Engineer
• Natural Language Processing Engineer
• Graph Database Consultant
• Data Integration Specialist
• Business Intelligence Analyst
• Network Analysis Researcher
• Recommendation Systems Developer
• AI Application Developer
• Data Architect specializing in Graph Technologies
• Cybersecurity Analyst using Graph Data Science
• Financial Analyst leveraging Graph Databases
• Healthcare Data Analyst
• Social Network Analyst
• Supply Chain Optimization Analyst
• Graph Algorithm Developer
• Software Developer with Neo4j Expertise
• Academic Researcher in Graph Theory and Data Science

Teh Siew Yee: Teh Siew Yee is a seasoned leader in data science and digital transformation, with over 20 years of experience driving organisational strategy, talent development, and the design of data ecosystems across Asia Pacific and global markets. He has successfully led cross-geographical teams and collaborated with industry leaders from the US, UK, China, India, Japan, South Korea, Australia, and beyond, focusing on leveraging data to achieve business objectives and optimize operations.

With expertise spanning predictive modeling, machine learning, deep learning, and IoT, he has hands-on experience in data architecture, engineering, and analytics. He has also developed comprehensive training programs, equipping all levels of an organisation— from C-suite to working-level employees— with the skills needed for digital transformation. His industry experience covers sectors such as tech, education, finance, aerospace, and eCommerce, making him a sought-after expert in data-driven business strategy.

Quah Chee Yong: Quah Chee Yong is a ACTA trainer. Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industries A firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners.