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
WHY CHOOSE THIS ADVANCED DIPLOMA IN STATISTICS & PROBABILITY FOR DATA SCIENCE &
MACHINE LEARNING AT QLS LEVEL 7 COURSE?
1. Unlimited access to the course for a lifetime.
2. Opportunity to earn a certificate accredited by the CPD Quality
Standards and CIQ after completing this course.
3. Structured lesson planning in line with industry standards.
4. Immerse yourself in innovative and captivating course materials and
activities.
5. Assessments designed to evaluate advanced cognitive abilities and skill
proficiency.
6. Flexibility to complete the Course at your own pace, on your own schedule.
7. Receive full tutor support throughout the week, from Monday to Friday, to
enhance your learning experience.
8. Unlock career resources for CV improvement, interview readiness, and job
success.
WHO IS THIS ADVANCED DIPLOMA IN STATISTICS & PROBABILITY FOR DATA SCIENCE &
MACHINE LEARNING AT QLS LEVEL 7 COURSE FOR?
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
CAREER PATH
* 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)
PREREQUISITES
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.
CERTIFICATION
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.
Endorsed Certificate of Achievement from the Quality Licence Scheme
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.
Endorsement
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.
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 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