Math Skills For Data Science, ML, And Predictive Modeling

What you'll learn
Interpret Data Like a Pro - Create and analyze charts, histograms, and boxplots to understand trends and make informed decisions.
Compute Key Statistics - Calculate mean, median, mode, range, and standard deviation to summarize and interpret data sets.
Interpret Data Like a Pro - Create and analyze charts, histograms, and boxplots to understand trends and make informed decisions.
Understand Probability Basics - Predict outcomes, calculate risks, and apply probability to everyday scenarios like games, insurance, and decision-making.
Requirements
No advanced algebra or calculus required - this course is designed for non-math majors.
Access to a calculator (scientific or online) for some topics.
Description
Do you think math is all about complicated formulas and endless algebra? Think again!Mathematical Skills for Data Science is a refreshing, real-world approach to mathematics designed for learners who want practical skills, not abstract theory. This course focuses on quantitative literacy-the math you actually use in analyzing data and interpreting it for decision making. This isn't a traditional math class. You won't be buried in algebra or calculus. Instead, you'll learn concepts that matter, from analyzing a study to experiments, to sampling methods-all explained in clear, simple language.By the end of this course, you'll be able to:Make informed financial decisions using interest, annuities, and loans.Analyze data and interpret graphs like a pro.Apply probability and statistics to everyday scenarios.Whether you're a college student, a professional, or simply someone who wants to boost your math confidence for analysis, this course will give you the tools to think critically, solve problems, and make smarter decisions in the real world.Why This Course Is DifferentHands-on learning: Apply math to real-life scenarios like budgeting, planning, and decision-making.No heavy algebra or calculus: Just the essentials for understanding and using math effectively.Engaging topics: From fair elections to fractals and encryption, you'll see math in action everywhere.Critical thinking focus: Learn how to analyze, interpret, and solve problems logically.
College students in liberal arts or social sciences who need a quantitative literacy for data analysis,Adult learners looking to strengthen practical math skills for data analysis,Professionals who want to understand finance, data analysis, and decision-making without heavy math.
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