Database and Data Analytics

This course introduces Learners to fundamental data concepts, with practical exercises, in order to progress from an absolute beginner to a skilled user, in both analysis and visualization.

Key Learning outcomes include Basics of SQL, working with Data, Fundamentals of database theory, Creating Tables in SQL, Creating database in SQL, Database design etc.

This Data Analytics course introduces learners in their teenage years to the fundamentals of data analytics through genuine contextual analyses and models.

Key Knowledge Outcome include include Data types, visualization, usage and distribution, statistical inference, Big Data Anatomy, Forecasting, decision making etc

The syllabus includes a comprehensive curriculum, which is designed on the basis of what most industries want from data science and analytics professionals.

Leaners will be introduced to the terms, jargon, history and impact of business intelligence and data analytics, scope and application of data analytics.

Key learning outcomes include Data types, visualization, usage and distribution, statistical inference, Big Data Anatomy, Forecasting, decision making,venture lifecycles, the distinction between data analytics, data science, and AI; assembling an analytics system, and utilizing analytics devices to draw business experiences etc.

At the end of the course, Learners will have acquired the technical knowledge and skills required for an effective data analyst.

In this course leaners will get to know what databases are and why we use them, exploring how to use SQL to search, store, manipulate, and query data using SQL

SQL (Structured Query Language) is a special purpose programming language ideal for managing data in relational database. Majority of the medium or large enterprises use SQL to store and organize their data.

The Coderseries learning methodology enables learners understand SQL in the easiest way possible. 

Course Content

1. 1.    SQL Query Statements
2. 2.    Database Manipulation and Modification
3. 3.    SQL Reporting
4. 4.    Information and Data Models
5. 5.    Relational queries in SQL
6. 6.    Mapping Entities to Tables
7. 7.    Relational Model Concepts