SQL for Data Science
February 14, 2025 7:36 pmSQL for
Data Science
Online Course
SQL for Data Science
The 3-Month Certificate Program in SQL for Data Science is designed for aspiring data professionals who want to master SQL and leverage its power for data analysis. SQL (Structured Query Language) is a foundational tool for data scientists, analysts, and engineers, enabling them to work efficiently with databases, perform data manipulation, and extract valuable insights. This course covers everything from basic SQL queries to advanced techniques like joins, window functions, and data cleaning, focusing on practical, real-world applications.
The demand for data-driven decision-making is skyrocketing across industries, and SQL is at the core of most data-related tasks. Data scientists and analysts need a solid grasp of SQL to access, manipulate, and analyze vast amounts of data stored in relational databases. The skills learned in this course are crucial in sectors like finance, healthcare, e-commerce, technology, and consulting.
Graduates of this program can pursue roles such as Data Analyst, Data Scientist, Business Intelligence Analyst, Database Administrator, or SQL Developer. The expertise gained will also help in roles that require data handling, reporting, and database management. With SQL being a critical skill in the data science field, the course will provide excellent career opportunities, both for entry-level roles and advancement in the industry.
Course Fee
₹ 10,000/-
Qualification
Any Degree
Duration
45 days
Course Type
Certification
Our Recognitions Speaks
Creative Mentors was honored for its excellency in animation education industry
WHAT WE TEACH
Here’s a 3-Month Course Curriculum Module-wise for SQL for Data Science. This program is designed to take students from SQL fundamentals to advanced querying techniques, with a focus on data analysis and manipulation, making it especially valuable for those pursuing careers in data science.
Month 1: SQL Fundamentals for Data Science
- Topics Covered:
- Introduction to Databases and SQL
- Types of Databases: Relational vs. Non-Relational
- Setting Up SQL Environment (MySQL, PostgreSQL, or SQL Server)
- Basic SQL Commands: SELECT, FROM, WHERE
- Filtering and Sorting Data
- SQL Operators and Clauses: AND, OR, IN, NOT, BETWEEN, LIKE
- Practical Assignment: Perform data filtering and sorting on a sample dataset using basic SQL queries.
- Topics Covered:
- Topics Covered:
- Using Aggregate Functions: COUNT, SUM, AVG, MIN, MAX
- Grouping Data with GROUP BY
- Filtering Groups with HAVING
- Combining Data with UNION and UNION ALL
- Introduction to Built-in SQL Functions for Data Analysis
- Topics Covered:
Month 2: Advanced SQL Techniques for Data Analysis
- Topics Covered:
- Understanding Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
- Using Self Joins and Cross Joins
- Combining Data from Multiple Tables
- Data Manipulation Commands: INSERT, UPDATE, DELETE
- Using Subqueries for Nested Data Extraction
- Practical Assignment: Use multiple tables to perform data analysis on a relational dataset, leveraging joins and subqueries.
- Topics Covered:
- Topics Covered:
- Working with Window Functions: ROW_NUMBER, RANK, DENSE_RANK, NTILE
- Partitioning Data with PARTITION BY
- Cumulative and Moving Aggregates (e.g., running totals)
- Common Table Expressions (CTEs) for Complex Queries
- Recursive Queries for Hierarchical Data
- Topics Covered:
Month 3: Data Science Applications and Project Development
- Topics Covered:
- Data Cleaning Techniques: Removing Duplicates, Handling Nulls, Formatting
- Data Transformation for Analysis (e.g., date parsing, text manipulation)
- Using CASE Statements for Conditional Logic
- Creating Summary and Pivot Tables
- Introduction to Data Normalization and Denormalization
- Practical Assignment: Clean and prepare a messy dataset for analysis, applying data cleaning and transformation techniques.
- Topics Covered:
- Topics Covered:
- Query Optimization Techniques (e.g., indexing, query restructuring)
- Analyzing Query Performance and Execution Plans
- Building a Data-Driven Application: Creating Views and Stored Procedures
- Final Project: Data Analysis Project from Data Collection to Insights
- Presenting Data Analysis Results and Reporting
- Topics Covered:
By the end of this course, students will have a strong foundation in SQL, enabling them to manipulate, clean, and analyze data effectively. They will be able to extract meaningful insights from large datasets, an essential skill for roles such as Data Analyst, Data Scientist, or Business Intelligence Analyst. With practical assignments and a final project, students will gain hands-on experience and build a portfolio, making them competitive candidates for data-focused roles in the industry.
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OUR FACULTY
FROM THE STUDENTS
Direct testimonials from the students who completed the course
ADMISSION PROCESS
Creative Mentors Animation, Gaming and VFX School is looking for dedicated students who want to become tomorrow’s art and design leaders. We seek innovators, storytellers, collaborators, problem solvers, dreamers, leaders—all are welcome here.
