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- Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7

- Level: Level 7
- Modules: 90 Modules
- Duration: 11 hours, 27 minutes
- Students: 18

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you!

In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R.

**Learning Outcomes**

By the end of this course, you will be able to:

- Apply descriptive statistics, distributions, and probability theory to summarise and visualise data
- Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data
- Use Python and R to implement statistical and machine learning methods
- Interpret and communicate the results of your analysis using appropriate metrics and visualisations
- Solve real-world problems and scenarios using statistics and probability

- Unlimited access to the course for a lifetime.
- Opportunity to earn a certificate accredited by the
**CPD Quality Standards**and**CIQ**after completing this course. - Structured lesson planning in line with industry standards.
- Immerse yourself in innovative and captivating course materials and activities.
- Assessments designed to evaluate advanced cognitive abilities and skill proficiency.
- Flexibility to complete the Course at your own pace, on your own schedule.
- Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.
- Unlock career resources for CV improvement, interview readiness, and job success.

This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for:

- Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge
- Students and researchers who want to learn the mathematical foundations of data science and machine learning
- Professionals and managers who want to understand and apply data-driven decision making
- Hobbyists and enthusiasts who want to explore and learn from data
- Anyone who loves statistics and probability and wants to challenge themselves

**Data Scientist**(£35,000 – £55,000)**Machine Learning Engineer**(£40,000 – £60,000)**Statistician**(£35,000 – £55,000)**Data Analyst**(£40,000 – £60,000)**Business Intelligence****Analyst**(£45,000 – £65,000)**Senior Data Analyst**(£50,000 – £70,000)

This **Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7** does not require you to have any prior qualifications or experience. You can just enrol and start learning.This **Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7** was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.

Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10.

The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards.

Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.

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 | ||

Assignment | |||

Assignment – Statistics & Probability for Data Science & Machine Learning | 00:00:00 | ||

Order your QLS Endorsed Certificate | |||

Order your QLS Endorsed Certificate | 00:00:00 |

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