SQL for Data Science

SQL for Data Science

A comprehensive course on SQL using practical examples and calculations. This course is highly suited for beginners

  • Domain : CSE
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A Quick Overview

SQL for Data Science Course is designed to take students from a beginner level to advanced level in the field of SQL. The course is covered in a manner so that SQL capabilities can be utilized for extensive data exploration. Each week thoroughly covers the syntax for SQL commands as well as a hands-on session on the RDBMS tool. Data science domain deals with data and results in the form of decisions that can be used to boost various businesses. It is an art of extracting meaningful insights from the available data. SQL is used everywhere from small to big companies. It is a declarative language where focus is on doing rather than how it is performed. Integration with programming languages like R, Python is easy with SQL. Playing with a large dataset is clearly possible with SQL. This course will teach basic select commands to complex cursors by taking real life dataset examples.

Moreover in this course, students work on real time datasets such as analysing consumer behaviour from an ecommerce data set as Project 1 and Career options of Alumni database as Project 2. Both projects deal with real time data sets and give students complete scope for exploration and thorough understanding of SQL.


COURSE SYLLABUS

1Introduction

  • Introduction to Data Science
  • Applications of Data Science
  • Why is SQL required for Data Science?
  • Database Management System (DBMS)
  • Relational Database Management System (RDBMS)
  • Basic terminology in RDBMS
  • Data Constraints
  • Entity Relationship Model
  • What is SQL
  • Categories of SQL Commands
  • Hands on executing simple SQL statements on RDBMS tool

2Database Creation, Manipulation

  • Detailed SQL Data types
  • Creating database
  • Create Table
  • Using Constraints
  • Insert Table
  • Altering Table structure
  • Dropping Database and Table
  • Delete, Update
  • Hands on importing sample database schema

3Database Selection

  • Select statement
  • Removing Duplicates
  • Use of Alias
  • Use of Where
  • Use of Wildcards
  • Limit clause
  • Arithmetic Operators
  • Mathematical Functions
  • Hands on creating backups and restore for large databases

4Database Selection

  • Generating Strings
  • String Functions
  • Date Functions
  • Conversion Functions

5Database Selection

  • Comparison Operators
  • Logical Operators
  • Order By
  • Group By
  • Aggregate Functions
  • Using aggregate functions with Group by clause
  • Union Operator
  • Sub-query

6Querying Multiple Tables

  • Need to Join Multiple Tables
  • Cartesian Product
  • Inner Join
  • Left Join
  • Right Join
  • Self Join
  • Delete Join
  • Update Join
  • Hands on Joining more than two tables in sample database

7Data Exploration

  • What is Data Exploration?
  • Structure of Data
  • Understanding E-R Diagram
  • How to Use SQL for Data Exploration
  • Significance of
    • Joins
    • Sub queries
    • Inbuilt functions
  • Other important capabilities of SQL for data exploration
  • Hands On
  • Working with NULL values
  • Making trends in Data
  • Identifying Outliers
  • Creating Data Summary

8Index, View, Transaction

  • Creating Index
  • Use of Index
  • Type of Index and Index Strategies
  • Views
  • Views as Weapon for Data Analysis
  • Multi user database
  • What is Transaction
  • Save points
  • Hands on working on Multi user database environment

9Querying with Conditions

  • Querying with Conditions
  • Searched Case Expression
  • Simple Case Expression
  • Applications of Case Expression
  • Common Error Codes
  • Hands on working with Json type data

10Stored Procedures

  • Stored Procedures as friend for Data Analysis
  • Creating Stored Procedures
  • Removing Stored Procedures
  • Altering Stored Procedures
  • Conditional Statements
  • Loops
  • Hands on working with Cursors

11Integrating SQL with Excel

  • Hands on
  • Accessing MySQL data with MS Excel
  • Running SQL statements with Excel
  • Combining Excel and SQL statements for data representation

12Integrating SQL with Python

  • Hands on
  • Working with Python
  • Accessing SQL data with Python
  • Running basic SQL statements with Python
  • Running inbuilt python functions on SQL data


Projects Overview

Project 1

Highlights

The business model Customer to Customer (C2C) allows customers to do business with each other. This model is growing fast with e-commerce platforms where sellers may be required to pay some amount and buyer can buy it without paying anything. E-Commerce website brings the seller and buyer to the same platform. 

Analyzing the user's database will lead to understanding the business perspective. Behavior of the users can be traced in terms of business with exploration of the user’s database. 

Dataset: One .csv file with name users_data with 98913 rows and 27 columns

Tasks to be performed

  1. Create new schema as ecommerce
  2. Import .csv file users_data into MySQL
  3. Run SQL command to see the structure of table
  4. Run SQL command to select first 100 rows of the database
  5. How many distinct values exist in table for the field "country" and "language"
  6. Check whether male users are having maximum followers or female users.
  7. Calculate the total number of users that
    1. Uses Profile Picture in their Profile
    2. Uses Application for Ecommerce platform
    3. Uses Android app
    4. Uses ios app
  8. Calculate the total number of buyers for each country and sort the result in descending order of total number of buyers.
  9. Calculate the average number of sellers for each country and sort the result in ascending order of total number of sellers.
  10. Display name of top 10 countries having maximum products pass rate.
  11. Calculate the number of users on an ecommerce platform for different language choices.
  12. Check the choice of female users about putting the product in a wishlist or to like socially on an ecommerce platform.
  13. Check the choice of male users about being seller or buyer.
  14. Which country is having maximum number of buyers?
  15. List the name of 10 countries having zero number of sellers.
  16. Display record of top 110 users who have used ecommerce platform recently.
  17. Calculate the number of female users those who have not logged in since last 100 days.
  18. Display the number of female users of each country at ecommerce platform.
  19. Display the number of male users of each country at ecommerce platform.
  20. Calculate the average number of products sold and bought on ecommerce platform by male users for each country.

 

Project 2

Highlights

Once a student is passed out from a Institute or College, he/she is known as Alumni of the Institute. Alumni’s career growth plays important role in Institute’s ranking and other networking activities. In this project, career choices of alumni of two Universities will be analyzed with respect to their passing year as well as the course they completed. 

Dataset: Six .csv file (Alumni record of College A and College B) Higher Studies, Self Employed and Service/Job record 

  • College_A_HS ~ Higher Studies Record of College A
  • College_A_SE ~ Self Employed Record of College A
  • College_A_SJ ~ Service/Job Record of College A
  • College_B_HS ~ Higher Studies Record of College B
  • College_B_SE ~ Higher Studies Record of College B
  • College_B_SJ ~ Higher Studies Record of College B

Tasks to be performed

  1. Create new schema as alumni
  2. Import all .csv files into MySQL
  3. Run SQL command to see the structure of six tables
  4. Display first 1000 rows of tables (College_A_HS, College_A_SE, College_A_SJ, College_B_HS, College_B_SE, College_B_SJ) with Python.
  5. Import first 1500 rows of tables (College_A_HS, College_A_SE, College_A_SJ, College_B_HS, College_B_SE, College_B_SJ) into MS Excel.
  6. Perform data cleaning on table College_A_HS and store cleaned data in view College_A_HS_V.
  7. Perform data cleaning on table College_A_SE and store cleaned data in view College_A_SE_V.
  8. Perform data cleaning on table College_A_SJ and store cleaned data in view College_A_SJ_V.
  9. Perform data cleaning on table College_B_HS and store cleaned data in view College_B_HS_V.
  10. Perform data cleaning on table College_B_SE and store cleaned data in view College_B_SE_V.
  11. Perform data cleaning on table College_B_SJ and store cleaned data in view College_B_SJ_V.
  12. Make procedure to use string function/s for converting record of Name, FatherName, MotherName into lower case for views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) 
  13. Import the created views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) into MS Excel and make pivot chart for location of Alumni. 
  14. Make data summary for all six views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) for demographic analysis through SQL. 
  15. Make data summary for views (College_A_SJ_V, College_B_SJ_V) for company choices of Alumni through SQL. 
  16. Make data summary for the decision of being entrepreneur of Alumni of particular domain through SQL. 
  17. Analyze the choice of course after being graduated from College for College A and College B through SQL. (Use the cleaned data only)
  18. Analyze the choice of Institute after being graduated from College for College A and College B through SQL (Use the cleaned data only)
  19. Analyze the choice of higher studies in India and abroad for College A and College B through SQL (Use the cleaned data only)
  20. Calculate the percentage of career choice of College A and College B Alumni (w.r.t Higher Studies, Self Employed and Service/Job) 




Control the World’s Big Problem—Learn SQL

Being a data scientist is that your dream? The SQL for Data Science course covers all the SQL capabilities you need for data exploration. With each passing week, you will gain expertise in Syntax for SQL commands and a hands-on session on the RDBMS tool.

In the modern corporate world, Data Science as a tool is indispensable in providing data for result-oriented business decisions. With this SQL course, you can learn the art of extracting meaningful data and integrating it with programming languages, R and Python. It helps you overcome the ‘how to’ by focusing on getting the job done. Based on real-life dataset examples— the course starts teaching basic select commands before advancing to complex cursors.

Train yourself to interpret and analyze data with the SQL for Data Science certification course. It comes in three packages— Basic, Pro, and Premium only at Rs. 7000, Rs. 10,000, and Rs. 15,000 each for three months to give you two months, four months, and a lifetime’s access. 

Who Should Take the SQL for Data Science Course?

The number of job opportunities arising today for a data scientist is equivalent to the exponential rise of produced data. Students and IT, Software, and Marketing professionals can take part in this offline course. Apart from them, anyone who desires to learn Data Science, be it a fresher or a professional, can go for this course.

Even if you do not have any prior knowledge of SQL, you are eligible for the course provided you have logical and analytical skills. Business consultants and software programmers wanting a transition in their career can also opt for this course. Professionals working on reporting tools, data warehousing, and business intelligence who are keen on pursuing a career in Data Science are eligible for this SQL certification course.

The minimum requirement for this course is basic high school level knowledge of Database Management Systems.

What Will You Learn?

The course will explain the meaning, relationship, and structure of raw data and how to use SQL to shape it for analysis. It includes two real-time projects and will cover topics like SQL Basics, differences between DBMS and RDBMS, Understanding of E-R diagrams, integrating SQL with Python and Excel, Joins, and more.

The topics in this course assist you in exploring and analyzing the data effectively to create queries that are compact and efficient. The hands-on experience will provide an added advantage of being able to practice structured queries. It gives you a chance to manipulate numeric, strings, and date data types with the aid of functions to blend data from multiple sources into fields of the correct format for analysis.

This is a perfect place to find all the various operators like arithmetic, strings, logic, comparison, and aggregates in a single SQL course. The hands-on aspects of the course teach you all the uses of a specific function or constraint, making any difficult query look like a piece of cake.

Skills You Will Gain

  • Learn to create simple yet complex queries. 
  • Integration of Excel with SQL to deal with real-world entities.
  • Combination of Python with SQL to implement real-world problems.
  • Move from basic to advanced queries.
  • Learn more about null values.
  • Learn how to create sub-queries and the important types of joins.

Key Highlights of the Program

  • A merit certificate will be provided to the top 5% of the class. A SQL course completion certificate is given to all learners. 
  • Upskill to work in the corporate world in just three months. After this course, the transition from writing basic queries to effortless complex queries will be seamless. 
  • It helps build a professional portfolio and create an E-verified profile to link to LinkedIn.
  • The hands-on assignments and real-world cases help you gain an industry-like experience.

Career Opportunities after Taking the Course

There is a rapid growth of data, and dealing with such huge amounts of data poses a problem. SQL is considered one of the most important skills one must have to enter into a career in Data Science. This SQL certification course is one of the best for those who want to specialize in Data Science, Data Analytics, or any related field. If you're skilled in SQL, you can land the following jobs:

  • SQL Server Analyst: To create and maintain the database. Experienced professionals develop optimized queries for faster and natural server performance.
  • Database Administrators: Update the server functionality by installing, updating, and repairing the database.
  • Business Data Analyst: They work with SQL developers within the organization to analyze data and make winning decisions. 
  • Database Designer: Digital architects to understand the patterns to access data efficiently and quickly.  
  • Data Scientist: Professionals well versed in SQL to store and analyze customer and industry-related data.

FAQs on SQL for Data Science

  1. What are the prerequisites for joining this course?

         A basic understanding of SQL is necessary.

    2.  Should all data scientists know SQL?

         Yes, SQL is the most essential language for a data scientist. It is SQL that helps in processing, analyzing, and interpreting the data effectively.

  1. What will you learn from this course?
  • To create simple, plain, and meaningful queries instead of complex ones.
  • Difference between DBMS and RDBMS.
  • Use of and the difference between various constraints and functions.
  • Creation of effective procedures.
  1. What is the need for SQL in Data Science?

        Data Science is concerned with large amounts of data that must be stored in databases. SQL is required to function efficiently on a database with such large amounts of data. With the use of simple, short queries, SQL is quite successful in producing results.

  1. How difficult is it to master SQL?

        SQL is a language that is very similar to the English language. A person without any prior knowledge of programming can easily understand and learn SQL.

  1. How long is it going to take you to master SQL?

        As it is a pretty simple language, you can master it in 2-3 months. But it also depends on the tutor, the way he teaches, and the pace at which the learner can grasp the knowledge. 


Flexible Course Fees

Choose the plan that’s right for you

Basic

2 Months Access

$93.87

Per month for 3 months

  • Access Duration : 2 Months
  • Mode of Delivery : Online
  • Project Portfolio : Available
  • Certification : Available
  • Email Support : Available
  • Forum Support : Available
Premium

Lifetime Access

$201.15

Per month for 3 months

  • Access Duration : Lifetime
  • Mode of Delivery : Online
  • Project Portfolio : Available
  • Certification : Available
  • Individual Video Support : 12/ Month
  • Group Video Support : 12/ Month
  • Email Support : Available
  • Forum Support : Available
  • Telephone Support : Available
  • Dedicated Support Engineer : Available

WHO IS THIS COURSE FOR ?


SOFTWARE COVERED

MySQL Workbench, MS Excel, MySQL for Excel Add in, Python, Anaconda

MySQL is an open-source RDBMS tool used to store structured data. The tool enables SQL queries to be run through the GUI interface MySQL Workbench. Dataset can be imported into the tool with different methods. In a similar manner, data can be imported from the MySQL tool into .csv files or other formats.

The integration of MS Excel and MySQL - Microsoft Excel version 2007 or higher version required for installation of add-in MySQL for Excel. With this add-in, two platforms can be integrated and data can be interchanged which allows for innumerous possibilities of playing with data.

The integration of Python and MySQL tools - Python command line and anaconda python distribution are used for data manipulation. The MySQL dataset can be fetched through python code with this integration.


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Certification

  • Top 5% of the class will get a merit certificate
  • Course completion certificates will be provided to all students
  • Build a professional portfolio
  • Automatically link your technical projects
  • E-verified profile that can be shared on LinkedIn

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Frequently Asked Questions

1Who can take your course?

Students are required to have basic knowledge of database management systems.

2What is included in your course?

Learning SQL for data science field, relational database creation, storage, querying, analyzing, splitting and merging, mathematical and other functions required for data manipulation of hands on real world data.

3What will the student gain from your course?

  • Creating, inserting, updating and querying of relational database
  • Methods to understand data patterns
  • Data Cleaning and Computation
  • Using SQL for Data Analysis & Data Visualization

4What software skills are you teaching and how well are these tools used in the industry?

SQL, Relational Database tool, these tools are widely used in industry for database storage.

5What real world application for the tools and techniques will you teach in this course?

  • RDBMS tools are extensively used in Organizations for managing different types of data
  • The course will cover hands on examples with real world data

6Which companies use these techniques and for what?

SQL is standard for storing relational databases in all large enterprises irrespective of its domain. Few big names are Amazon, Flipkart, Microsoft, Google , Ola, Zomato, Paytm

7How is your course going to help me in my path to MS or PhD?

This course will cover SQL basics and hands on with a large dataset for data analysis. Students interested for doing specialization in Data Analytics, Data Science or related fields will get good knowledge of SQL for strong concept building.

8How is this course going to help me get a job?

SQL experts are in very much demand and industry is always looking for the right talent.


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