MySQL is a database management system used in multiple applications for several purposes. In most cases, it is used in combination with web development and data science. Are you excited every time you manage and manipulate data and dream of having more operations you can use? This course on MySQL and statistics will provide you with insights and broaden your knowledge. The lessons start with the basics of MySQL such its origin, uses, and importance for data analyses. Then, the logic behind SQL and SQL queries along with database management systems (DBMS) will be discussed. The importance of DBMS will be reviewed as well as the differences between relational (SQL) and non-relational (NoSQL) databases. You will also learn which programming language is used in these databases. Next, we discuss the advantages and disadvantages of MySQL and have an overview of what is to be expected as the outcome after data analyses. The detailed process for installing MySQL - from downloading the required applications to installing them on your computer, and using them - will be explained.
We then explore various activities in MySQL where you will learn to start and stop the MySQL server from within the integrated development environment (IDE), as well as using the command prompt. You will make use of several MySQL items such as statements, queries, operators, functions, clauses, variables, tables and the foreign and primary keys to carry out simple data tasks. You will also learn to create MySQL databases and columns, modify tables, arrange, sort, change data, and much more. Afterwards, an analysis of data types will be done and you will experiment with practical examples from several case studies. You will also examine a brief summary of MongoDB such as its importance, benefits, and disadvantages.
Lastly, you will get deeper insights concerning data by exploring data types, range, and classifications, as well as the centre of numerical data and its importance. Several ways to present your data will be explained along with the principles of standard deviation and how to calculate it using ranges of data. You will also compare symmetric and skewed data shapes, and learn about outliers and how to deal with them. Subsequently, we will discuss the distribution of data such as the normal distribution, sampling distribution, as well as T and Z distribution. The confidence level interval will also be broken down with examples showing how to calculate it manually. Additionally, you will study hypothesis testing with examples and case studies. You will learn to calculate P-Values manually and using Microsoft Excel. A bonus lesson on machine learning is included in the latter section of the course. If you’re eager to master data analytics and enhance your MySQL proficiency, then seize this exciting opportunity and sign up today. Start Course Now
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