Exam 1 - CompTIA DataAI Certification
Test your knowledge with 90+ questions from the Mathematics and Statistics section of the CompTIA DataAI (formerly named DataX) certification. Find out if you’re ready to ace the exam — can you apply an appropriate statistical method or concept, as well as explain probability and synthetic modeling concepts and their uses? And much more!
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Skill level
All levels
02
Sections
2
03
Lectures
19
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Instructor
Team Mammoth
What's inside
This course includes.
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2
Sections
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19
Lectures
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19
Quizzes
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Certificate of completion
Included
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Mobile and desktop access
Included
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AI learning assistance
Included
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Course content
Curriculum & lectures.
+ Exam - Probability and synthetic modeling concepts and their uses 8 lectures
Distributions
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Skewness and Kurtosis
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Heteroskedasticity vs. Homoskedasticity
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Probability Density Function (PDF), Probability Mass Function (PMF), and Cumulative Distribution
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Probability, Monte Carlo Simulation, and Bootstrapping
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Bayes' Rule, Expected Value, and Types of Missingness
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Oversampling and Stratification: Handling Imbalance and Ensuring Representation
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Distributions in Synthetic Modeling
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+ Exam - Given a scenario, apply the appropriate statistical method or concept 11 lectures
Hypothesis Testing: Making Inferences
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P-Value, Type I and Type II Errors: Understanding Statistical Significance
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T-Tests: Comparing Means
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Chi-Squared Test: Analyzing Categorical Data
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Analysis of Variance (ANOVA): Comparing Multiple Means
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Confidence Intervals: Estimating Population Parameters
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Regression Performance Metrics: Evaluating Model Fit
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Gini Index, Entropy, and Information Gain: Measuring Impurity and Reduction
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ROC AUC, AIC BIC: Evaluating Model Performance and Complexity
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Performance Metrics
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Central Limit Theorem and Law of Large Numbers: Foundational Concepts
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Ready to start building?
Test your knowledge with 90+ questions from the Mathematics and Statistics section of the CompTIA DataAI (formerly named DataX) certification. Find out if you’re ready to ace the exam — can you apply an appropriate statistical method or concept, as well as explain probability and synthetic modeling concepts and their uses? And much more!