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SQl+Python for Data Analytics & Business Analytics(19 Hours)

Name: SQl+Python for Data Analytics & Business Analytics(19 Hours)
Rating: 4.1 (20 reviews)

Analyze Data Like a Pro leveraging SQL Server and Python Development, A Practical Guide to Data and Business Analytics

Created byShishir Kumar

Last updated 5/2026

English

What you'll learn

Introduction of SQL Server
Select Statement with Multiple Scenarios
All Types of JOINS (Inner, Left, Right, Full, Cross, Self Joins)
Sub Queries with Multiple Business Scenarios
SQL IN, Between, Like, Not Null, IS NOT NULL
Import and Export Data with Live Scenarios
Delete and Truncate to remove data from Table
Complex SQL Query with Sales Data
Python Basic Script, Comments and Shortcuts
Python Measure Data Type List, Tuple, Set, Dictionary
Python For Loop and While Loop
Python End to End Project

Course content

26 sections • 161 lectures • 20h 31m total length

Course Overview10:21
What is Analyst8:05
Introduction of SQL Server6:10
Datasets and Power Point Downloadable Resource1:31
SQL Server Interface6:26
Server and Database8:15
SQL Table, Record, Field5:35

Sort Data in Ascending or Descending Orders6:57
Sort Data In Ascending Orders3:38
Sort Data in Descending Orders2:55
Explore SQL for data analytics and business analytics by ordering data in descending order, selecting from orders, filtering by product category technology, and sorting by profit.
Sort Data in Ascending or Descending Order on Multiple Fields13:15
Group Field and Sort Data in Ascending or Descending Order8:09

Extract Distinct Data2:16
Group by aggregates data across one or more columns to summarize results and show unique values, often using an aggregate function with examples from the employee table.
Aggregate Data with Group By6:01
Learn to use group by to aggregate data by region, calculating order counts, total profit, and region-wise average, maximum, and minimum profits. Apply aliases to name result columns clearly.
Apply Condition with Having Clause13:54

Extract Data of Max Value5:05
Extract Data of Min Value2:06
Extract Data more than Average Value1:51
Compare Two Tables Data and Extract Matching Data6:06
Extract 3rd Highest Sales6:44
Extract 3rd Lowest Sales8:21
Extract 3rd Largest Value of Grouped Data16:20
Learn to extract the third largest value from grouped data using subqueries, group by, and having in SQL server, with department and region examples.

Requirements

No specific requirement to learn this course. This course will guide you step by step

Description

Embark on a journey to become a proficient SQL user with our comprehensive course designed for beginners and advanced learners alike. Whether you are a database novice or looking to enhance your SQL skills, this course covers everything you need to know about Structured Query Language (SQL) and its application in database management.

1 Foundation of SQL:-

Understanding the fundamentals of relational databases.

Mastering the basics of SQL syntax and structure.

Creating and manipulating database tables.

2 Querying Data:-

Writing powerful SQL queries to retrieve and filter data.

Employing advanced querying techniques for complex data extraction.

3. Data Modification:-

Inserting, updating and deleting records in a table.

Ensuring data integrity through constraints.

4. Joins and Relationships:-

Exploring relationship between tables

Utilizing different types of joins for comprehensive data retrieval.

5 Data Aggregation and Grouping:-

Understanding aggregate functions for summarizing data

Grouping and transforming data for insightful analysis

Python:-

Unlock the power of Python to analyze, interpret, and visualize data for smarter business decisions. This hands-on course is designed to teach you how to use Python effectively for data analytics and business intelligence tasks — even if you’re from a non-programming background.

You will learn how to work with real-world datasets, clean and transform data, perform statistical analysis, generate actionable insights, and build impactful visualizations. From foundational programming concepts to advanced analytics using pandas, NumPy, Matplotlib this course covers everything you need to become a data-driven analyst.

Python basics: syntax, data types, loops, and functions
Data manipulation using pandas and NumPy
Exploratory data analysis (EDA) techniques
Data visualization with Matplotlib and Seaborn
Handling real-world business datasets
Working with Excel, CSV, and SQL using Python
Automating tasks and generating summary reports

By the end of this course, you will have the knowledge and hands-on experience to confidently work with SQL databases, manage data effectively, and optimize database performance and Python Development.

Whether you are pursuing a career in database administration, data analysis BI developer.

Who this course is for:

This course is for them who want to mark career in Data Analytics, Business Analytics, Reporting

SQl+Python for Data Analytics & Business Analytics(19 Hours)

What you'll learn

Explore related topics

Course content

Introduction7 lectures • 46min

SQL Table4 lectures • 24min

Data Insert, Import and Export5 lectures • 31min

Delete and Truncate2 lectures • 15min

Update Data3 lectures • 27min

Select Statement to View Data (Where Clause)3 lectures • 13min

Filter Data with Where Clause (And, Or, IN, Between, LIKE, TOP Operators)6 lectures • 46min

ORDER BY TO SORT DATA5 lectures • 35min

Group By and Having3 lectures • 22min

SQL Sub Query7 lectures • 47min

Requirements

Description

Who this course is for: