Overview Grasp the science of and how it relates to launching a lucrative career. Prepare for future needs by looking …
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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 .
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| 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 | ||
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
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