Course Details
Topic 1 Neo4j Fundamentals
- Basic graph theory and the elements that make a graph
- Graph structures
- Common graph database use cases
- Elements of a Neo4j graph database
- How Neo4j implements index-free-adjacency
- The Movie graph’s data model and data
Topic 2 Cypher Fundamentals
- Reading Data from Neo4j
- Introduction to Cypher
- Retrieving Nodes
- Finding Relationships
- Traversing Relationships
- Filtering Queries
- Writing Data to Neo4j
- Creating Nodes
- Creating a Node
- Creating Relationships
- Updating Properties
- Adding Properties to a Movie
- Merge Processing
- Deleting Data
Topic 3 Importing CSV Data into Neo4j
- Preparing for importing data
- Using the Neo4j Data Importer
- Post-processing for imported data
- Using Cypher to import data
Topic 4 Graph Data Modeling Fundamentals
- What is a graph data model?
- Modeling nodes and creating nodes for an instance model.
- Modeling relationships and creating relationships for an instance model.
- Testing the graph data model.
- Why refactor a graph data model and how labels help.
- Eliminating duplicate data in the graph.
- Using specific relationship types.
- Adding intermediate nodes.
Topic 5 Intermediate Cypher Queries
- Filtering queries
- Controlling results returned
- Working with Cypher data
- Graph traversal
- Pipelining queries
- Subqueries
- Using parameters
Topic 6 Neo4j Graph Data Science
- Basics for how Neo4j GDS works to enable analytics
- How to install GDS and the different licensing options
- Graph projection patterns
Topic 7 Neo4j Applications with Python
- The lifecycle of the Neo4j Driver and how it relates to your application
- How to install and instantiate the Neo4j Python Driver to your Python project
- How read and write transactions work with Neo4j
- Best practices on how to use Neo4j within your Python project.
Course Info
Prerequisite:
Basic Python knowledge is assumedHRDF Funding
Please refer to this video https://youtu.be/Kzpd-V1F9Xs
1- HRD Corp Grant Helper
How to submit grant applications for HRD Corp Claimable Courses
2- Employers are required to apply for the grant at least one week before training commences.
Employers must submit their applications with supporting documents, including invoices/quotations, trainer profiles, training schedule and course content.
3- First, Login to Employer’s e-TRIS account -https://etris.hrdcorp.gov.my
Second, Click Application
4- Click Grant on the left side under Applications
5- Click Apply Grant on the left side under Applications
6- Click Apply
7- Choose a Scheme Code and select HRD Corp Claimable Courses: Skim Bantuan Latihan Khas. Then, click Apply
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29- Once the New Grant Application is successfully submitted, the Grant Officer will evaluate the application accordingly. The application may be queried if additional information is required.
The application status will be updated via the employer’s dashboard, email, and the e-TRiS inbox.
Job Roles
- Database Administrator (specializing in graph databases)
- Data Scientist (working with graph data)
- Neo4j Developer
- Graph Database Consultant
- Data Engineer (focusing on graph technologies)
- Data Architect (implementing graph solutions)
- Backend Developer (integrating graph databases)
- Graph Data Analyst
- Machine Learning Engineer (using graph-based algorithms)
- Data Integration Specialist (for graph databases)
- Recommendation System Developer
- Research Scientist (working on graph theory)
- Social Network Analyst
- Fraud Detection Specialist (using graph patterns)
- Bioinformatics Researcher (using graph databases).
Trainers
Dr. Aanand: Dr. Aanand is a Full Stack Data Scientist who once had a torrid love affair with Physics. He has consulted and published in the area of Public Health, Electricity Markets, Telecom, BFSI, Advertising & Communication Strategies and Digital & Social Media Technologies. He has worked on assignments with international agencies such as International Monetary Fund, World Bank, Royal Netherland Embassy etc. besides MNCs like Tata Consultancy Services, Kie Square Consulting and several government organizations of national importance.
He regularly conducts general training programs in Python (Pandas, NumPy, SciPy, Matplotlib, Bokeh), R (dplyr, rstanarm, knitR, ggplot2), Data Visualization (Tableau, D3.js) and Machine Learnng (Reinforced Learning, Scikit Learn) and specialized training programs on Structural Equation Modeling and SAP Hana.
He holds a doctorate in Operations Research from Indian Institute of Management Ahmedabad and a post graduate in Physics from University of Mumbai. He has advanced training in mathematical programming including optimization, advanced multivariate data analysis, and simulation techniques. When he is not teaching or consulting he can be found meditating or heading for an adventurous trek.
Amir Othman: Amir Othman is a software engineer by profession. Being educated in Bauhaus Universität Weimar and Hochschule Ulm, he brings experiences from different facades of the world.
With expertise in web technology, natural language processing and machine learning, he is a freelance data scientist. Some of his works include two international news aggregator
www.kronologimalaysia.com and www.diezeitachse.de
He also holds an impressive port folio for data visualizations, primarily focusing on web based techniques.
After the realization set in that, I do not want to make it as an electronic engineer, I took the decision to go and try something new out of pure curiosity and thirst for new adventure. It didn't come quite handy but I have changed my major three times. It's not a surprise that I studied artificial intelligence and found myself all over again. I have a strong passion for machine learning and data science, fueled by the drive to learn and the endurance for growth beyond the ordinary.
Syed Muhammad Farrukh Akhtar: Syed Muhammad Farrukh Akhtar has more than 15 years of experience analysis, designing, developing, integrating and managing large applications for diverse industries. He has experience working in Dubai, Pakistan, Germany and Malaysia, strong hands-on experience of software design, development and integration on different platform like IBM J2EE, Oracle and Microsoft .Net, Big data, Hadoop, Spark, HBase, Hive, Sqoop, Flume and NoSQL. He also has expertise in Machine Learning/ Deep Learning with Tensor Flow, Keras and Python, excellent skills in React, Ionic 2, Angular 2, Mobile Apps with React Native and Node.js.
He is highly knowledgeable in object oriented software development, requirements analysis, and database design. Possess deep understanding of Open Source technologies’ applicability in emerging business areas. He possesses excellent knowledge in Rational Unified Process (RUP); Rational Software Architect; data modeling and mapping; and extensible system design using the UML and Visio. Professional experience on J2EE, JMS, Web Sphere, Oracle, Spring, Hibernate, Struts and 3-Tier Web-based Applications Development.