Getting Digital

Become a Probability & Statistics Master

Develop essential data science & ai skills with expert instruction and practical examples.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of data science & ai
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry Standards
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of data science & ai
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in data science & ai
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

HOW BECOME A PROBABILITY & STATISTICS MASTER IS SET UP TO MAKE COMPLICATED MATH EASY:This 163-lesson course includes video and text explanations of everything from Probability and Statistics, and it includes 45 quizzes (with solutions. ) and an additional 8 workbooks with extra practice problems, to help you test your understanding along the way. Become a Probability & Statistics Master is organized into the following sections:Visualizing data, including bar graphs, pie charts, Venn diagrams, histograms, and dot plotsAnalyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plotsData distributions, including mean, variance, and standard deviation, and normal distributions and z-scoresProbability, including union vs.

intersection and independent and dependent events and Bayes' theoremDiscrete random variables, including binomial, Bernoulli, Poisson, and geometric random variablesSampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervalsHypothesis testing, including inferential statistics, significance levels, type I and II errors, test statistics, and p-valuesRegression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-squareAND HERE'S WHAT YOU GET INSIDE OF EVERY SECTION:Videos: Watch over my shoulder as I solve problems for every single math issue you'll encounter in class. We start from the beginning. I explain the problem setup and why I set it up that way, the steps I take and why I take them, how to work through the yucky, fuzzy middle parts, and how to simplify the answer when you get it.

Notes: The notes section of each lesson is where you find the most important things to remember. It's like Cliff Notes for books, but for math. Everything you need to know to pass your class and nothing you don't.

Quizzes: When you think you've got a good grasp on a topic within a course, you can test your knowledge by taking one of the quizzes. If you pass, great. If not, you can review the videos and notes again or ask for help in the Q & A section.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AI

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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