Technology & IT

Advnace Certification in Advance SQL

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Learn from : ANAND DWIVEDI

Python Programing, java, Data science, Data Structure, Computer Networking, Web & mobile technologies, C++, C++ Concepts

   Course Language: English

Course Fee

$109.00

course-image

Course Fee

$109.00

Instructor Bio:

I am an Assistant Professor in Computer Science with a focus on computer programming and software development. I teach core programming languages such as C, C++, Python, and Java, and guide students in developing logical thinking and coding skills. My interests include algorithms, web development, databases, and emerging technologies. I aim to create a hands-on learning environment using tools like Visual Studio Code and GitHub. With a passion for teaching and mentoring, I support student innovation through projects and research. I believe in blending theoretical knowledge with practical application to prepare students for real-world challenges in technology

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Start Date

Course Duration

56 Weeks

Total Number of Classes

20

Course Frequency

DAILY

Post Course Support

  • Assignments
  • Forums
  • Quizzes
  • Resources
  • Recorded Session Videos

Course Description:

This Advanced SQL course enhances your skills in complex queries, joins, subqueries, CTEs, window functions, and performance tuning. It covers transaction control, indexing, views, procedures, and real-world database scenarios. Ideal for aspiring data professionals, it empowers you to manage, analyze, and optimize large-scale relational databases effectively.

Advanced SQL for Data Engineering – Syllabus (6 Points)

  1. Advanced Query Techniques
    Subqueries, nested queries, common table expressions (CTEs), and set operations (UNION, INTERSECT, EXCEPT).

  2. Joins and Data Relationships
    Inner, outer, cross, and self joins; multi-table queries and relational data modeling.

  3. Window and Aggregate Functions
    Use of RANK(), ROW_NUMBER(), LEAD(), LAG(), PARTITION BY, and complex groupings.

  4. Performance Tuning and Indexing
    Query optimization, execution plans, indexes, and best practices for efficient data access.

  5. ETL and Data Transformation
    SQL for Extract, Transform, Load (ETL) processes, data cleaning, and pipeline integration.

  6. Procedures, Transactions, and Security
    Stored procedures, triggers, transactions (ACID), error handling, and user/data access control.

Course Curriculum:

Advanced SQL for Data Engineering – Syllabus (6 Points)

  1. Advanced Query Techniques
    Subqueries, nested queries, common table expressions (CTEs), and set operations (UNION, INTERSECT, EXCEPT).

  2. Joins and Data Relationships
    Inner, outer, cross, and self joins; multi-table queries and relational data modeling.

  3. Window and Aggregate Functions
    Use of RANK(), ROW_NUMBER(), LEAD(), LAG(), PARTITION BY, and complex groupings.

  4. Performance Tuning and Indexing
    Query optimization, execution plans, indexes, and best practices for efficient data access.

  5. ETL and Data Transformation
    SQL for Extract, Transform, Load (ETL) processes, data cleaning, and pipeline integration.

  6. Procedures, Transactions, and Security
    Stored procedures, triggers, transactions (ACID), error handling, and user/data access control.

Earn a Course Completion Certificate

Add this certificate in your LinkedIn Profile, resume or share it on social media platforms. It helps validate the learner’s knowledge and skills, boosting their resume and increasing their employability.