MSDS Courses
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S01 - Data Structures & Algorithms
C01Searching
Sorting C02Trees
Graphs C03Dynamic
Program
S02 - Advanced Data Algorithms
C04Linear
Program C05Quantum
Algorithms
S03 - Statistical Inference Foundations
C06Probability
Theory C07Parametric
Estimation C08Hypothesis
Testing
S04 - Statistical Modeling for Data Science
C09Linear
Regression C10ANOVA
Experiment C11Nonlinear
Regression
S05 - Data Mining Foundations & Practice
C12DataMining
Pipeline C13DataMining
Method C14DataMining
Projects
S06 - Machine Learning Theory & Practice
C15Supervised
Learning C16Unsupervised
Learning C17Deep
Learning
S07 - Databases for Data Scientists
C18Relational
Database C19SQL
Operation C20Advanced
Database
S08 - Software Architecture for Big Data
C21Software
Fundamentals C22Software
Patterns C23Software
Applications
S09 - Vital Skills for Data Science
C24DataScience
Field C25Cyber
Security C26Ethical
Issues C27Data
Visualization
S10 - Effective Communication
C28Business
Writing C29Graphic
Design C30Public
Presentation C31Project
Capstone
S11 - Quality Improvement Methods
C32Quality
Statistics C33Stability
Capability C34Measurement
System
S12 - Statistical Learning for Data Science
C35Regression
Classification C36Optimization
Methods C37Advanced
Models
S13 - Climate Anomalies Modeling & Predicting
C38Climate
Policies C39Climate
Visualization C40Climate
Prediction
S14 - Text Marketing Analytics
C41Supervised
Analysis C42Unsupervised
Analysis C43Network
Analysis
S15 - Bayesian Statistics
C35Bayesian
Introduction C35Bayesian
Applications C35Bayesian
Modeling
S16
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