Overview

Grasp the science of Statistics & Probability for Data Science & Machine Learning and how it relates to launching a lucrative career. Prepare for future Statistics & Probability for Data Science & Machine Learning needs by looking beyond the ongoing Statistics & Probability for Data Science & Machine Learning impact with Discover Training’s up-to-date Statistics & Probability for Data Science & Machine Learning course .

Discover Training’s Statistics & Probability for Data Science & Machine Learning course gives you a solid foundation in Statistics & Probability for Data Science & Machine Learning in many settings of human development. With industry expert interviews, you’ll gain a greater understanding of Statistics & Probability for Data Science & Machine Learning‘s applications and limitations, as well as how it’s already been efficiently used in the field. Discover Training’s Statistics & Probability for Data Science & Machine Learning course will help you obtain facts and knowledge to strengthen your abilities on both standard Statistics & Probability for Data Science & Machine Learning techniques.

As you progress through the interactive modules of this online program, you will have a strong grasp of Statistics & Probability for Data Science & Machine Learning to identify new opportunities for innovation and drive digital growth within your organization. Enrol in the Statistics & Probability for Data Science & Machine Learning course today and leverage your knowledge tomorrow. 

Description:

Industry professionals developed the content of this online Statistics & Probability for Data Science & Machine Learning course, combining their expertise and in-depth knowledge. The curriculum was developed by Discover Training to assist you in growing in your current role by providing you with the necessary information and concepts. As you progress through the modules of this course, you’ll learn the fundamentals of  Statistics & Probability for Data Science & Machine Learning and explore the essential concepts.

Who is this course for?

This Statistics & Probability for Data Science & Machine Learning course is for you if you want to learn about the revolutionary potential of Statistics & Probability for Data Science & Machine Learning. Whether you are a newbie or a seasoned veteran, a grasp of challenges that Statistics & Probability for Data Science & Machine Learning techniques can tackle would benefit anyone working in the Statistics & Probability for Data Science & Machine Learning sector. This Statistics & Probability for Data Science & Machine Learning training covers crucial subjects that will help you overcome challenges and improve your practices.

Requirements:

Certification

Once the Statistics & Probability for Data Science & Machine Learning course is successfully completed, the learner can obtain the PDF certificate without any cost. The hardcopy version of the certificate is also available for only £9.99. However, anyone ordering the hardcopy certificate from outside the United Kingdom may need to pay an additional delivery charge.

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An outstanding online course with clear explanations and practical examples. I could study at my own pace and still feel fully supported throughout. It’s truly boosted my confidence and career prospects

The course was well-structured, engaging, and easy to follow. The flexibility made it perfect alongside my full-time job. I’ve gained valuable, real-world skills that I can apply immediately.

Excellent learning experience from start to finish. The content was professional, up-to-date, and highly relevant. I would highly recommend it to anyone looking to upskill online.

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

Frequently Asked Questions

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Anyone can enrol, including students, professionals, job seekers, career changers, and organisations. Most courses do not require previous experience, making them accessible to learners at all levels.

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You will have 14 days to revoke your Course purchase from your purchase date. Regrettably, refunds are not allowed after your purchase have been approved, and materials have been posted to the student’s dashboard or accessed.

Yes, learners receive a downloadable digital certificate upon successful completion, suitable for CPD records, CVs, and professional portfolios.

Statistics & Probability for Data Science & Machine Learning
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This course includes:
  • units Number of Units:
    88
  • Lock Access:
    1 Year
  • Duration Duration:
    11 hours, 27 minutes
  • Certificate PDF Certificate
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