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Statistics & Probability for Data Science & Machine Learning

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Statistics & Probability for Data Science & Machine Learning

Overview This course will unlock your full potential and will show you how to excel in a career in . …

$362.69 ex Vat saleend

Level: Intermediate
Duration: 11 hours, 27 minutes
Modules: 88 Modules
Students: 2

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Overview

This Statistics & Probability for Data Science & Machine Learning course will unlock your full potential and will show you how to excel in a career in Statistics & Probability for Data Science & Machine Learning. So upskill now and reach your full potential. Everything you need to get started in Statistics & Probability for Data Science & Machine Learning is available in this course.

Learning and progressing are the hallmarks of personal development. This Statistics & Probability for Data Science & Machine Learning will quickly teach you the must-have skills needed to start in the relevant industry.

In This Statistics & Probability for Data Science & Machine Learning Course, You Will:

Learn strategies to boost your workplace efficiency.
Hone your Statistics & Probability for Data Science & Machine Learning skills to help you advance your career.
Acquire a comprehensive understanding of various Statistics & Probability for Data Science & Machine Learning topics and tips from industry experts.
Learn in-demand Statistics & Probability for Data Science & Machine Learning skills that are in high demand among UK employers, which will help you to kickstart your career.

This Statistics & Probability for Data Science & Machine Learning course covers everything you must know to stand against the tough competition in the Statistics & Probability for Data Science & Machine Learning field.

The future is truly yours to seize with this Statistics & Probability for Data Science & Machine Learning. Enrol today and complete the course to achieve a Statistics & Probability for Data Science & Machine Learning certificate that can change your professional career forever.

Additional Perks of Buying a Course From Institute of Mental Health

Study online — whenever and wherever you want.
One-to-one support from a dedicated tutor throughout your course.
Certificate immediately upon course completion
100% Money back guarantee
Exclusive discounts on your next course purchase from Institute of Mental Health

Enrolling in the Statistics & Probability for Data Science & Machine Learning course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now.

Process of Evaluation

After studying the Statistics & Probability for Data Science & Machine Learning course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.

Certificate of Achievement

Upon successfully completing the Statistics & Probability for Data Science & Machine Learning course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99.

Who Is This Course for?

This Statistics & Probability for Data Science & Machine Learning is suitable for anyone aspiring to start a career in Statistics & Probability for Data Science & Machine Learning; even if you are new to this and have no prior knowledge on Statistics & Probability for Data Science & Machine Learning, this course is going to be very easy for you to understand.

And if you are already working in the Statistics & Probability for Data Science & Machine Learning field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.

Taking this Statistics & Probability for Data Science & Machine Learning course is a win-win for you in all aspects.

This course has been developed with maximum flexibility and accessibility, making it ideal for people who don’t have the time to devote to traditional education.

Requirements

This Statistics & Probability for Data Science & Machine Learning course has no prerequisite.

You don’t need any educational qualification or experience to enrol in the Statistics & Probability for Data Science & Machine Learning course.

Do note: you must be at least 16 years old to enrol.

Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Statistics & Probability for Data Science & Machine Learning course.

Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills.

Course Curriculum

Section 01: Let's get started
	Welcome!	00:02:00
	What will you learn in this course?	00:06:00
	How can you get the most out of it?	00:06:00
Section 02: Descriptive statistics
	Intro	00:03:00
	Mean	00:06:00
	Median	00:05:00
	Mode	00:04:00
	Mean or Median?	00:08:00
	Skewness	00:08:00
	Practice: Skewness	00:01:00
	Solution: Skewness	00:03:00
	Range & IQR	00:10:00
	Sample vs. Population	00:05:00
	Variance & Standard deviation	00:11:00
	Impact of Scaling & Shifting	00:19:00
	Statistical moments	00:06:00
Section 03: Distributions
	What is a distribution?	00:10:00
	Normal distribution	00:09:00
	Z-Scores	00:13:00
	Practice: Normal distribution	00:04:00
	Solution: Normal distribution	00:07:00
Section 04: Probability theory
	Intro	00:01:00
	Probability Basics	00:10:00
	Calculating simple Probabilities	00:05:00
	Practice: Simple Probabilities	00:01:00
	Quick solution: Simple Probabilities	00:01:00
	Detailed solution: Simple Probabilities	00:06:00
	Rule of addition	00:13:00
	Practice: Rule of addition	00:02:00
	Quick solution: Rule of addition	00:01:00
	Detailed solution: Rule of addition	00:07:00
	Rule of multiplication	00:11:00
	Practice: Rule of multiplication	00:01:00
	Solution: Rule of multiplication	00:03:00
	Bayes Theorem	00:10:00
	Bayes Theorem – Practical example	00:07:00
	Expected value	00:11:00
	Practice: Expected value	00:01:00
	Solution: Expected value	00:03:00
	Law of Large Numbers	00:08:00
	Central Limit Theorem – Theory	00:10:00
	Central Limit Theorem – Intuition	00:08:00
	Central Limit Theorem – Challenge	00:11:00
	Central Limit Theorem – Exercise	00:02:00
	Central Limit Theorem – Solution	00:14:00
	Binomial distribution	00:16:00
	Poisson distribution	00:17:00
	Real life problems	00:15:00
Section 05: Hypothesis testing
	Intro	00:01:00
	What is a hypothesis?	00:19:00
	Significance level and p-value	00:06:00
	Type I and Type II errors	00:05:00
	Confidence intervals and margin of error	00:15:00
	Excursion: Calculating sample size & power	00:11:00
	Performing the hypothesis test	00:20:00
	Practice: Hypothesis test	00:01:00
	Solution: Hypothesis test	00:06:00
	T-test and t-distribution	00:13:00
	Proportion testing	00:10:00
	Important p-z pairs	00:08:00
Section 06: Regressions
	Intro	00:02:00
	Linear Regression	00:11:00
	Correlation coefficient	00:10:00
	Practice: Correlation	00:02:00
	Solution: Correlation	00:08:00
	Practice: Linear Regression	00:01:00
	Solution: Linear Regression	00:07:00
	Residual, MSE & MAE	00:08:00
	Practice: MSE & MAE	00:01:00
	Solution: MSE & MAE	00:03:00
	Coefficient of determination	00:12:00
	Root Mean Square Error	00:06:00
	Practice: RMSE	00:01:00
	Solution: RMSE	00:02:00
Section 07: Advanced regression & machine learning algorithms
	Multiple Linear Regression	00:16:00
	Overfitting	00:05:00
	Polynomial Regression	00:13:00
	Logistic Regression	00:09:00
	Decision Trees	00:21:00
	Regression Trees	00:14:00
	Random Forests	00:13:00
	Dealing with missing data	00:10:00
Section 08: ANOVA (Analysis of Variance)
	ANOVA – Basics & Assumptions	00:06:00
	One-way ANOVA	00:12:00
	F-Distribution	00:10:00
	Two-way ANOVA – Sum of Squares	00:16:00
	Two-way ANOVA – F-ratio & conclusions	00:11:00
Section 09: Wrap up
	Wrap up	00:01:00