Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The SQL for Data Analysis course is a free, beginner-friendly self-paced program designed to help learners understand how to use SQL (Structured Query Language) to work with and analyze data stored in databases. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The SQL for Data Analysis course is a free, beginner-friendly self-paced program designed to help learners understand how to use SQL (Structured Query Language) to work with and analyze data stored in databases.
📋 Course Objectives
1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• Tangible, reproducible Artificial Intelligence work to show supervisors or employers.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to SQL and Databases
What is SQL? • What are Databases and Tables? • Importance of SQL in Data Analysis • Applications of SQL in Business and Technology
Basic SQL Queries
SELECT Statements • Filtering Data using WHERE • Sorting Results using ORDER BY • Selecting Specific Columns
Working with Data
Using Conditions and Logical Operators • Aggregating Data (COUNT, SUM, AVG) • Grouping Data using GROUP BY • Filtering Groups using HAVING
Data Analysis with SQL
Joining Multiple Tables • Combining Data for Analysis • Understanding Relationships Between Tables • Extracting Insights from Data
Applications and Next Steps
SQL in Business Reporting and Analytics • Using SQL in Data Science Workflows • Career Opportunities in Data and Analytics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | SQL |
| Covered Tool / Platform | Databases |
| Covered Tool / Platform | Data Analysis |
| Covered Tool / Platform | Queries |
| Covered Tool / Platform | Data Aggregation |
Frequently Asked Questions
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