This tutorial covers: 1. Data and Database: Data are pieces of information, and a database is a collection of logically related data, managed by a Database Management System (DBMS)1. 2. Table Basics: Data in a relational database is stored in tables, which consist of rows (records) and columns (fields)2. 3. SQL: Structured Query Language (SQL) is used to interact with relational databases for data definition, manipulation, retrieval, and control3. 4. Entity Relationship Diagram (ERD): ERDs visually represent the structure of a database, showing entities, attributes, and relationships4.

At the end of this module, you will be able to: 1. Identify the Quantitative and Categorical variable in a dataset. 2. Load data in Python and check whether assigned data types match variable types. 3. Encode categorical variables in Python using categorical encoding and one-hot encoding

An exhaustive tutorial covering the fundamental concepts of Time series analysis using the R package: 1. Basics of time series analysis 2. Working with dates (lubridate) 3. Creating and visualizing time series 4. Time series smoothing and decomposition 5. Time series autocorrelation and white noise

A brief introduction to analytics covering concepts and key terms related to Data Analytics and Data-Science. Chapter 1