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Data Wrangling & Data Cleaning – Preparing Data for Analytics & AI
Course Prerequisite(s)
- Please note that this course has the following prerequisites which must be completed before it can be accessed
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Data Analysis & Visualization – Turning Data into Insights
About Course
Statistics is the backbone of modern data science and machine learning. It provides the mathematical tools needed to analyze data, identify patterns, make predictions, and support data-driven decision-making.
This course introduces the essential statistical concepts used in data science, including probability, distributions, hypothesis testing, and statistical inference. Learners will explore how statistics helps data scientists interpret data and build reliable models.
Through practical examples and real-world datasets, students will learn how to apply statistical thinking to analyze data and draw meaningful conclusions.
By the end of this course, learners will understand the statistical foundations required for data analytics, machine learning, artificial intelligence, and business intelligence applications.
Benefits of the course
- Understand the role of statistics in data science
- Learn probability concepts used in data analysis
- Understand statistical distributions and data patterns
- Calculate mean, median, variance, and standard deviation
- Perform hypothesis testing and statistical inference
- Understand correlation and regression basics
- Interpret statistical results for business decisions
- Build a strong foundation for machine learning
Course Content
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