Databases and SQL

Course Overview: 

This course offers an in-depth exploration of databases and SQL, essential skills for any data science professional. Students will gain hands-on experience with relational databases, master SQL for querying and manipulating data, and delve into NoSQL databases to understand modern data storage solutions. This module equips learners with the knowledge needed to manage and analyze data efficiently, preparing them for real-world data science challenges.

Course Objectives:  

  1. Understand various types of databases and their use cases.

  2. Gain proficiency in SQL for data manipulation and querying.

  3. Learn advanced SQL techniques, including window functions and Common Table Expressions (CTEs).

  4. Explore NoSQL databases, focusing on MongoDB and Cassandra.

   5. Work with JSON and BSON data formats used in NoSQL databases.

Target Audience: 

This course is designed for aspiring data scientists, data analysts, and IT professionals who want to deepen their knowledge of databases and SQL. It is suitable for individuals with a basic understanding of data science concepts who wish to enhance their skills in database management and querying.

Prerequisites: 

 Basic knowledge of data science concepts.

 Familiarity with Python programming is recommended but not required.

Course Format:  

 Mode: Online/Offline

 Assessment: Quizzes, Assignments, and Final Project

 Certification: Upon successful completion, participants will receive a certificate recognized by industry leaders.

Course Content:

1. Introduction to Databases 

   Types of Databases: Explore relational and non-relational databases, understanding their use cases and advantages.

   Database Management Systems (DBMS): Learn about DBMS components and popular systems like MySQL and PostgreSQL.

2. SQL for Data Science 

   Basic SQL Queries: Learn fundamental SQL commands for data retrieval and manipulation.

  Joins, Subqueries, and Aggregations: Master advanced SQL techniques for combining data and summarizing information.

  Advanced SQL: Window Functions, CTEs: Explore sophisticated SQL features for complex queries and performance optimization.

3. NoSQL Databases 

   Introduction to MongoDB and Cassandra: Understand NoSQL databases, their architecture, and use cases.

   Working with JSON and BSON: Learn to work with JSON and BSON data formats, performing CRUD operations in MongoDB.

Career Outcomes:  

By the end of this course, students will have a strong grasp of both relational and NoSQL databases. They will be able to design, manage, and query databases effectively, making them well-prepared for roles such as Data Scientist, Data Analyst, Database Administrator, and other data-centric positions.

Enrollment: 

Enroll today to enhance your database management and SQL skills and take a significant step forward in your data science career.