Data-X Masterclass, HKBU
May 23-25, 2018
This is the official Github repository for the Masterclass.
High level outline:
- Day 1: Introduction to AI and Overview, Project Setup, Code Samples and Introduction to Data Analytics, Business & Venture Applications, Get Value from your Data
- Day 2: Innovation Leadership, Webscraping, Challenges in Data Science, Project Updates and Architecture, Big Data and Cloud Computing, The Future of Data Strategies, Advanced topics, Reflection and Next Steps
- Day 3: Blockchain Overview, Blockchain Business Use Cases, Project Deliverables, Demo or Die, Staying Connected
Download the Masterclass material
To download this Github repository just press the green
Clone or Download button to the top right.
📝 Masterclass Schedule
To download the material to your computer please Install git and use the Terminal / Command Prompt to clone the repository.
git clone https://github.com/afo/dataXhkbu/
Every time the repository is updated, to get the most recent version,
cd to the cloned
dataXhkbu folder and run:
For more information about Version Control, git, and Github please read this excellent guide: Introduction to git and Github
📧 Contact us
📁 About the Bootcamp
Today, the world is literally reinventing itself with Data and AI. However, neither leading companies nor the world’s top students have the complete knowledge set to participate in this newly developing world. This course provides the tools and understanding to boost any student’s ability to create the emerging data applications of the future. This bootcamp is suitable for individuals interested in hands-on practical understanding of data science and application opportunities in new ventures, industry project areas, and potential support of research with data technologies.
This bootcamp is set of intensive topics selected from the the Applied Data Science with Venture Applications Course at UC Berkeley (IEOR 135/290). The bootcamp is a high paced immersion into data and data science principles in a uniquely practical approach. The program contains theory segments, code samples in Python and in Jupyter Notebooks, and a real-life wide ranging project that can be started with guidance for instructors. The course includes a real life code development project.
List of Dependencies: