Taught By

Dr. Qingyang Xiao

Dr. Qingyang Xiao is a Senior AI Research Scientist at Johns Hopkins University with a Ph.D. in Applied Mathematics and a Master's degree holder in Data Science & AI from Harvard University. With top security clearance, Dr. Xiao leads classified Department of Defense projects developing AI detection systems, Nash Equilibrium modeling for military operations, and machine learning algorithms for radar and missile systems. His cutting-edge data science work directly supports the Pentagon and National Geospatial-Intelligence Agency in revolutionizing how U.S. military forces engage threats in contested environments. Dr. Xiao has collaborated with major tech companies including Snorkel AI, Amazon, and Outlier AI, bringing valuable industry experience to his mentorship.

Week by Week Curriculum

Week 1

Statistical Thinking for AI Engineers and Data Scientists
Fundamental statistical principles and introductory probability theory

Week 2

Introduction to Python, Google Colab, Jupyter Notebook, and Spyder
Python installation via Anaconda and exploring key development environments

Week 3

Big Data Management Using MySQL
SQL basics and integrating Python with MySQL for scalable data processing

Week 4

Data Handling with Python's Pandas Library
Working with DataFrames and handling various data formats (Excel, CSV, SQL)

Week 5

Data Manipulation Techniques
Data transformation, cleaning, loading/unloading, and integration processes

Week 6

Exploratory Data Analysis in Data Science
Statistical metrics (MSE, RMSE, R-squared) and AI-driven analytical techniques

Week 7

Data Visualization in AI and Data Science
Creating bar charts, histograms, violin plots, and quartile plots

Week 8

Object-Oriented Programming (OOP) in Python
Classes, objects, inheritance, and encapsulation for AI applications

Week 9

Statistical Inference with T-Test and ANOVA
Applying and interpreting T-tests and ANOVA in data-driven research

Week 10

AI Implementation in Stock Market Forecasting
Building and training AI models for financial analytics and forecasting

Data Science PhD Lab with Harvard Scientist

In Partnership With