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SLB – Data Science Intern
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Cohere – Research Intern
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Tencent – Data Product Intern
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-------------Day-1 SQL----------

SQL is a standard language for accessing and manipulating databases.

✅What is SQL?
- SQL stands for Structured Query Language
- SQL lets you access and manipulate databases
- SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987

✅ What Can SQL do?
- SQL can execute queries against a database
- SQL can retrieve data from a database
- SQL can insert records in a database
- SQL can update records in a database
- SQL can delete records from a database
- SQL can create new databases
- SQL can create new tables in a database
- SQL can create stored procedures in a database
- SQL can create views in a database
- SQL can set permissions on tables, procedures, and views

✅✅ What Is a SQL Dialect, and Which one Should You Learn?

-----MySQL-----

MySQL is often compared to a handy free tool you might find in a toolbox. Imagine having a gadget that doesn't come with a price tag, yet is loved and recommended by many. That's MySQL for the digital world.



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-------- Day-1 Statistics ---

Day-1 Statistics

✅ What is statistics?

Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. In other words, it is a mathematical discipline to collect, summarize data. Also, we can say that statistics is a branch of applied mathematics.

✅ Why study statistics?
statistics is one of the most important things that you can study.

To be more specific, here are some claims that we have heard on several occasions. (We are not saying that each one of these claims is true!)

- 4 out of 5 dentists recommend Dentine.
- Almost 85% of lung cancers in men and 45% in women are tobacco-related.

- People tend to be more persuasive when they look others directly in the eye and speak loudly and quickly.
- Women make 75 cents to every dollar a man makes when they work the same job.


✅ Common terms in Statistics!


1. Population

A population is a selected individual or group representing the full set of members of a certain group of interest.

2. Sample

A sample is a subset drawn from a larger population. If this drawing is accomplished in such a manner that each member of the population has an equitable chance of selection, the result is referred to as a random sample.

3. Parameters

A parameter is a value which is generated from a population. If I had all the data of all humans on Earth and generated the mean age, this value would be a parameter.

4. Statistics 📈

A statistic is a value which is generated from a sample

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---------Day-2 of SQL-------------


✅ What is a Database?

- Definition: A database is an organized collection of structured information or data, typically stored electronically in a computer system.
- Purpose: Databases are used to store, manage, and retrieve data efficiently.

✅What is DBMS?

- Definition: DBMS (Database Management System) is software that interacts with end-users, applications, and the database itself to capture and analyze data.
- Function: It provides a systematic way to create, retrieve, update, and manage data.


✅ Features of DBMS

1. Data Integrity: Ensures accuracy and consistency of data.
2. Data Security: Protects data from unauthorized access.
3. Data Recovery: Provides mechanisms for data backup and recovery.
4. Data Independence: Separates data from application programs.
5. Concurrency Control: Manages simultaneous data access by multiple users.
6. Data Management: Facilitates data storage, retrieval, and update.

✅ How Can We Interact with DBMS?

- SQL (Structured Query Language): The most common language used to interact with a DBMS for querying, updating, and managing data.

- Database Interfaces: Tools and applications (e.g., phpMyAdmin, pgAdmin) that provide a graphical interface to interact with the database.

- APIs: Application Programming Interfaces that allow software applications to interact with the DBMS programmatically.

✅What is a Query and Why is it Used?

- Definition: A query is a request for data or information from a database table or combination of tables.
- Purpose: Used to extract specific data by filtering, sorting, and presenting it based on certain conditions.



Example of a Query on Amazon

Scenario

Extracting product details for all items in the "Electronics" category with ratings above 4 stars.
- SQL Example:

  SELECT product_name, price, rating 
  FROM products 
  WHERE category = 'Electronics' AND rating > 4;
  

- Usage: This query helps Amazon identify and display high-rated electronic products to customers, enhancing user experience and satisfaction.


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Those who are looking for the tutorials to learn tableau!!


Check out the video 📸 😍😍

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📊 Day-2 of statistics 📈

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👉🏻👉🏻 Statistics have majorly categorised into two types:

✅ Descriptive statistics
✅ Inferential statistics

🎉Descriptive Statistics

In this type of statistics, the data is summarised through the given observations. The summarisation is one from a sample of population using parameters such as the mean or standard deviation.

Descriptive statistics is a way to organise, represent and describe a collection of data using tables, graphs, and summary measures. For example, the collection of people in a city using the internet or using Television.

🎉 Inferential Statistics

This type of statistics is used to interpret the meaning of Descriptive statistics. That means once the data has been collected, analysed and summarised then we use these stats to describe the meaning of the collected data. Or we can say, it is used to draw conclusions from the data that depends on random variations such as observational errors, sampling variation, etc.

Day-3 Sql challenge ✅

To download the Latest Mysql workbench, and server.
Comment “Server” to get the video tutorial link.

✅ What is a Relational Database (RDBMS)?

A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables. In a relational database, each row in the table is a record with a unique ID called the key. The columns of the table hold attributes of the data, and each record usually has a value for each attribute, making it easy to establish the relationships among data points.

✅ Relational terms

we need to know a few important terms. These are:

👉🏻 Relations – Most of us know what a table is from using spreadsheet software. It is a grid made up of rows and columns. Well in relational databases we often refer to these as “relations”.
👉🏻 Tuples – A row in a table is known as a record, or a tuple. A tuple holds all the data on a single item.
👉🏻 Attributes – An individual piece of data in a record is known as a field, or attribute.
Table Record Field
👉🏻 Domains – All the possible allowable values for an attribute. This is slightly different to the data type of the attribute.
👉🏻 Cardinality – How unique an attribute is in terms of its data values. Some attributes will have a wide range of different data values entered.


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Here’s a list of companies that are offering internships in the United States:

Peerlogic – Data Analyst Intern
GuidewireRx – ML Intern
The Centers – Data Analytics Intern
W. R. Berkley – Data Science Intern
Dyania Health – NLP Intern
Royal Cyber – Data Scientist Intern

Search the company name on LinkedIn and apply for these internships

Day-3 of Statistics 📊

✅ What are Types of Data in Statistics?

The data is classified into majorly four categories:

Nominal data
Ordinal data
Discrete data
Continuous data

Nominal Data

Nominal data is one of the types of qualitative information which helps to label the variables without providing the numerical value.

Ordinal Data

Ordinal data/variable is a type of data that follows a natural order. The significant feature of the nominal data is that the difference between the data values is not determined.

Discrete Data

Discrete data can take only discrete values. Discrete information contains only a finite number of possible values.
Example: Number of students in the class

Continuous Data

Continuous data is data that can be calculated. It has an infinite number of probable values that can be selected within a given specific range.

Example: Temperature range


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Day-4 of SQL 😍

DDL (Data Definition Language) consists of SQL commands used to define and modify the structure of database objects. These commands are crucial for creating, altering, and deleting database structures such as tables, indexes, views, and schemas. Common DDL commands include:

CREATE: Used to create new database objects.
ALTER: Used to modify existing database objects.
DROP: Used to delete existing database objects.
TRUNCATE: Used to remove all records from a table, but not the table itself.
RENAME: Used to rename existing database objects.

DML (Data Manipulation Language), on the other hand, consists of SQL commands used to manipulate the data within these database structures. These commands are essential for performing operations like inserting, updating, and deleting data within tables. Common DML commands include:

INSERT: Used to add new records to a table.
UPDATE: Used to modify existing records within a table.
DELETE: Used to remove records from a table.
SELECT: Although often categorized under Data Query Language (DQL), it is sometimes considered a part of DML for retrieving data from a database.

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Day-4 of Statistics 😍

✅ Quantitative Data:

Quantitative data represents information that can be measured and expressed numerically. This type of data is often associated with quantities and involves counting or measuring attributes.

- Measurable and numerical.
- Includes discrete (countable) and continuous (measurable) data.
- Analyzed using measures of central tendency and dispersion.
- Examples: height, weight, number of students.
✅ Qualitative Data:
Qualitative data, also known as categorical data, represents characteristics or attributes that cannot be measured numerically but can be observed and recorded as categories or labels.

- Descriptive and categorical.
- Includes nominal (unordered categories) and ordinal (ordered categories) data.
- Analyzed using frequency distribution and non-parametric methods.
- Examples: gender, eye color, satisfaction ratings.

Understanding the differences between quantitative and qualitative data is crucial for selecting appropriate statistical techniques and accurately interpreting results in any research or data analysis context.

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Day-5 of MYSQL 😍

In MySQL, data types define the kind of data that can be stored in a column. Here's a brief overview of the main MySQL data types:

1. Numeric Data Types
INT: Integer values. (e.g., INT, TINYINT, SMALLINT, MEDIUMINT, BIGINT)
FLOAT: Floating-point numbers for approximate values.
DOUBLE: Double-precision floating-point numbers for more precise values.
DECIMAL: Fixed-point numbers for exact decimal values.

2. Date and Time Data Types
DATE: Dates in YYYY-MM-DD format.
DATETIME: Dates and times in YYYY-MM-DD HH:MM:SS format.
TIMESTAMP: Timestamps for tracking changes, usually in YYYY-MM-DD HH:MM:SS format.
TIME: Time of day in HH:MM:SS format.
YEAR: Year in YYYY format.

3. String Data Types
CHAR: Fixed-length character strings.
VARCHAR: Variable-length character strings.
TEXT: Large text fields. (e.g., TINYTEXT, MEDIUMTEXT, LONGTEXT)
BLOB: Binary large objects for storing binary data. (e.g., TINYBLOB, MEDIUMBLOB, LONGBLOB)

4. Other Data Types
ENUM: Enumerated list of values; each column value must be one of the predefined set.
SET: A set of values, where each column value can be a combination of predefined values.


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Day-5 of statistics 😍😍


A box plot, also known as a box-and-whisker plot, is a graphical representation of the distribution of a dataset. It provides a visual summary of key statistical measures and is particularly useful for identifying the spread, central tendency, and potential outliers in a dataset.

Components of a Box Plot

Box:

- The box represents the interquartile range (IQR), which encompasses the middle 50% of the data. It is bounded by the first quartile (Q1) and the third quartile (Q3).
- The height of the box indicates the variability or spread of the central 50% of the data.

Median:

- The line inside the box represents the median (Q2) of the dataset, which is the middle value when the data is sorted in ascending order. It divides the data into two equal halves.
Whiskers:

- The whiskers extend from the edges of the box to the smallest and largest values within 1.5 times the IQR from Q1 and Q3, respectively.
- They provide an indication of the range of the data.
Outliers:

- Data points that fall outside the whiskers are considered outliers. These are typically represented as individual points or dots beyond the whiskers.
- Outliers are values that significantly deviate from the rest of the data and can indicate variability or anomalies.

Statistical Measures Represented

Minimum: The smallest value in the dataset within the whiskers' range.
Q1 (First Quartile): The median of the lower half of the data (25th percentile).
Median (Q2): The middle value of the dataset (50th percentile).
Q3 (Third Quartile): The median of the upper half of the data (75th percentile).
Maximum: The largest value in the dataset within the whiskers' range.
IQR (Interquartile Range): The range between Q1 and Q3, representing the middle 50% of the data.


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Day-6 of MYSQL 😍😍

👉🏻👉🏻 What is constraint in mysql?
SQL constraints are used to specify rules for the data in a table. Constraints are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the table. If there is any violation between the constraint and the data action, the action is aborted.

👉🏻👉🏻 What is primary and foreign key?
Primary keys serve as unique identifiers for each row in a database table. Foreign keys link data in one table to the data in another table. A foreign key column in a table points to a column with unique values in another table (often the primary key column) to create a way of cross-referencing the two tables. This is a crucial aspect of SQL keys that ensure data integrity and relationships between tables.

If a column is assigned a foreign key, each row of that column must contain a value that exists in the ‘foreign’ column it references. The referenced (i.e. “foreign”) column must contain only unique values – often it is the primary key of its table.

In short:

✅ Primary keys are used to uniquely identify and index each row within a single table.
✅ Foreign keys are used to link rows in two different tables such that a row can only be added or updated in table_a if the value in its foreign key column exists in the relevant column of table_b.


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