Data Science Fullstack


June 1, 2019
8 months to 12 months


Full-stack Data Science Engineering is the integration of data science and data engineering.


A full-stack data scientist has a broad understanding of data science product life-cycle shown as blow:


For Chinese introduction, Please see here:



Career Goal:

Software architect:  a software expert who makes high-level design choices and dictates technology standards.

Full-Stack data scientist:  data science architect who can design application system in big data context, work on complicated data integration, and feature engineering and modeling.


The course is recommended to:

– Young professionals who want to leverage their career

– Students who want to enter the data science job market within 8 to 12 months



  • Data Analytics and Modeling:

Data processing with Pandas and Numpy

Statistics modeling with R

Machine learning with Scikit-Learn

Distributed machine learning

Deep learning

Full-cycle data analytics


  • Data Science Application with big data platform:

Hadoop platform

Spark platform

Hive (SQL) distributed database

Pig big data processing

No-SQL database

Real-time data analytics

Lambda architecture

Data science application design


  • Broad domain knowledge:

Computation algorithms such as searching and sorting

Recommendation system

Finance big data analytics

Supply chain management

GIS (Geographic Information System) big data application

Natural language processing

Healthcare big data analytics