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Statistics & Probability for Data Science & Machine Learning Course
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Highlights
On-Demand course
11 hours 27 minutes
All levels
Description
Overview
By enroling in Statistics & Probability for Data Science & Machine Learning, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.
The Statistics & Probability for Data Science & Machine Learning course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Statistics & Probability for Data Science & Machine Learning course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Statistics & Probability for Data Science & Machine Learning Program.
So enrol in our Statistics & Probability for Data Science & Machine Learning course right away if you're keen to envision yourself in a rewarding career.
Description
Enroling in this Statistics & Probability for Data Science & Machine Learning course can improve your Statistics & Probability for Data Science & Machine Learning perspective, regardless of your skill levels in the Statistics & Probability for Data Science & Machine Learning topics you want to master. If you're already a Statistics & Probability for Data Science & Machine Learning expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Statistics & Probability for Data Science & Machine Learning insights that will help you make the most of your time. This Statistics & Probability for Data Science & Machine Learning course will act as a guide for you if you've ever wished to excel at Statistics & Probability for Data Science & Machine Learning.
Why Choose Us?
This course is accredited by the CPD Quality Standards.
Lifetime access to the whole collection of the learning materials.
Online test with immediate results.
Enroling in the course has no additional cost.
You can study and complete the course at your own pace.
Study for the course using any internet-connected device, such as a computer, tablet, or mobile device.
Certificate of Achievement
Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99.
Who Is This Course For?
This Statistics & Probability for Data Science & Machine Learning course is a great place to start if you're looking to start a new career in Statistics & Probability for Data Science & Machine Learning field. This training is for anyone interested in gaining in-demand Statistics & Probability for Data Science & Machine Learning proficiency to help launch a career or their business aptitude.
Requirements
The Statistics & Probability for Data Science & Machine Learning course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Statistics & Probability for Data Science & Machine Learning, without any fuss.
Career Path
This Statistics & Probability for Data Science & Machine Learning training will assist you develop your Statistics & Probability for Data Science & Machine Learning ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a Statistics & Probability for Data Science & Machine Learning professional story and personalise your path to a new career. Furthermore, developing this Statistics & Probability for Data Science & Machine Learning skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.
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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 | ||
Order Your Certificate | |||
Order Your Certificate | 00:00:00 |
About The Provider
NextGen Learning
London, United Kingdom
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