(The following topics include but are not limited to)
Topic 1: Statistics
Basic Theory of Statistics
Descriptive statistics and inferential statistics
Parameter estimation and hypothesis testing
Analysis of Variance and Regression Analysis
Non parametric statistical methods
Time series analysis
multivariate statistical analysis 
Bayesian Statistics and Computation
Statistical machine learning
High dimensional data analysis
Spatial Statistics and Geostatistics
Statistical software and algorithms
Statistical modeling and prediction
Statistical Quality Control
Topic 2: Intelligent Computing
Basic Theory of Intelligent Computing
Evolutionary Computation and Genetic Algorithm
Particle Swarm Optimization Algorithm
Ant Colony Algorithm and Its Applications
Simulated Annealing and Taboo Search
Artificial immune system
Fuzzy Computing and Rough Sets
Neural Computing and Deep Learning
Hybrid Intelligent Algorithm
Multi objective intelligent optimization
Constrained optimization and uncertainty
Distributed intelligent computing
Application of Intelligent Computing in Engineering
The application of intelligent computing in finance
Application of Intelligent Computing in Medicine
Standardization of intelligent computing
Topic 3: Data Science
Basic Theory of Data Science
Data collection and preprocessing
Data Storage and Management
Data Exploration and Visualization
Data mining algorithm
Machine Learning and Deep Learning
Big data analysis platform
Data Quality Governance
Data Security and Privacy
Data driven decision-making
Text Analysis and Natural Language Processing
Image and video data analysis
Social Network Analysis
Recommendation System and Personalization
Time Series and Predictive Analysis
Application of Data Science in Finance