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Data Science Decisions in Time
Coursera
Specialization
Unknown

Data Science Decisions in Time

Johns Hopkins University

Intermediate-level specialization focusing on making confident decisions using streaming data with hypothesis testing and sequential analysis methods in real-time applications.

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About this Course

This specialization is for data scientists, applied mathematics, statisticians, or computer scientists, involved with decision making from data. The four courses build a firm foundation in how decisions can be meaningfully made, with confidence, on data collected in a streaming application. The level is intermediate, assuming basic math and statistics skills

What You'll Learn

  • Apply hypothesis testing to streaming data scenarios
  • Understand decision-making based on sequential testing
  • Use flow control charts and sequential analysis methods

Prerequisites

  • Basic familiarity with the topic and terminology
  • Readiness to practice through applied exercises or case-based work

Instructors

T

Thomas Woolf

Professor

Topics

Probability and Statistics
Data Science
Algorithms
Computer Science
Analytics
Anomaly Detection
Applied Machine Learning
Bayesian Statistics
Bioinformatics
Clinical Trials

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

الاحتمالات والإحصاء
علم البيانات
الخوارزميات
علوم الحاسوب
التحليلات
كشف الشذوذ
تعلم الآلة التطبيقي
الإحصاء البايزي
Bioinformatics
Clinical Trials

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