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Duration: 5 days – 35 hrs.

 

Overview

 

This comprehensive training program combines two essential IT skills – SQL (Structured Query Language) and Python programming. Participants will gain a strong foundation in working with databases, data management, and programming using Python. Whether you’re a beginner or looking to enhance your existing skills, this course is designed to provide you with the knowledge and hands-on experience needed to excel in the IT industry.

 

Objectives

 

  • Write simple scripts in Python
  • Write Complex SQL Statements
  • Clean and process data
  • Analyze Data in both SQL and Dataframes
  • Properly Visualize data using Python

 

Audience

 

  • IT Professionals: IT personnel, including developers, system administrators, and network engineers, who want to enhance their database management and programming capabilities.
  • Data Analysts: Professionals who work with data and want to gain proficiency in using SQL for data retrieval and Python for data analysis and visualization.
  • Software Developers: Developers looking to expand their programming skills to include Python and improve their database interaction using SQL.
  • Database Administrators: DBAs who wish to strengthen their SQL skills for database maintenance, optimization, and management.
  • Web Developers: Web developers interested in using Python for web development and integrating databases with web applications.
  • Business Analysts: Individuals involved in data-driven decision-making who want to use SQL and Python for data manipulation and reporting.
  • Students: Students pursuing degrees in computer science, data science, or related fields who want to gain practical skills in SQL and Python.
  • Entrepreneurs and Startups: Business owners or startup founders who need to manage data, build software, or develop web applications and want to do it themselves.
  • Professionals in Transition: People changing careers or job roles and see SQL and Python as valuable skills for their new path.
  • Anyone Interested in IT: Individuals with a general interest in IT and a desire to learn SQL and Python, regardless of their current profession.

 

Pre- requisites 

  • No prior knowledge of SQL or Python is required. However, basic computer skills and a willingness to learn are recommended.

Course Content

 

Topic Coverage Est. Time
Day 1: SQL Basics
Basic Concepts of SQL T-SQL Statements: 

  • Definition, 
  • ACID Property 
  • T-SQL Statement Languages

Data Types
Database Structures (Databases, Schema, Tables and Rows)

1 HR
Basic SELECT Statements SELECT, Limiting Rows, Unique Values Filtering Aliasing, Sorting 1.5 HRS
Aggregating Data Count, Sum, Min.  Max. Average. Grouping 1.5 HRS
Combining Tables Database Normalization, Wide Data vs Long Data, Self Joins, Cross Joins, LEFT / RIGHT/ INNER / OUTER JOINs, UNION 1.5 HR
Activity 1
  • Use Simple SELECT to review data sets
  • Use Aggregate Functions to get mode, media, mean, total, etc.
  • Combine Data from multiple tables
1.5 HRS
Day 2: Python for Beginners
Introduction to Python Brief background on Python, Introduction to tools and workspaces, Python syntax, and real-life application 1 HR
My First Python Script Input, Output, Comments, Variables, Comments, Type Casting, String Operator, and Mathematical Operators 1.5 HRS
Conditional Statements and Loops Logical Operators, IF statements, nested IF statements, Switch Statements, While Loop, For Loops, Nested Loops and Breaks 1 HR
Other Useful Applications Libraries, Functions, Sets, Local & Global Variables, Lists, Dictionaries, Exception Handling and Reading Files   1.5 HRS
Activity 2 Build a simple game using python 2 HRS
Day 3: Advance SQL
Querying from Memory Subqueries, Common Table Expressions, Temporary Tables, Pivot and Views 1.5 HRS
Activity 3 Re-do Activity 1 with CTE. Subqueries, etc. 1 HR
Window Functions and Native Functions Case Statements, Date Functions, Cast, Conversion, String Operators, Mathematical Operators, Coalesce, NULLIF,  1.5 HRS
Activity 4 Data Cleansing with SQL 1 HR
Loading, Appending, Removing and Updating Data Importing Data Sets, Inserting Records, Delete Records, Updating Records, and Exporting Records 1 HR
Activity 5 Load Data Set and Analyze Data Set 1 HR
Day 4: PANDAS
Loading Data Introduction to Numpy, Pandas; Loading a data frame dictionaries, lists,excel and CSV;; limiting rows; data frame data types;  Sorting and Filtering Dataframes,  2 HRS
Activity 6 Create a data frame using dictionaries and reading files then review them by sorting and filtering 1 HR
Simple Aggregation and Visualization Aggregating and Merging Dataframes; Visualizing Data Frames with Python 2 HRS
Activity 7 Analyzing Data Using Data Frames using CSV records and visualizing them 2 HRS
Day 5: Combination of SQL and Pandas
Dataframes and Databases Connecting Databases and Dataframes; Pivot using Python; Optimizing SQL Scripts (Explain) and Query Structure 1.5 HRS
Activity 8 Re-do Activity 7 but the data source is in a database 1.5 HRS
Review Review all concepts discussed 1 HR
Project Test the skills and concepts of students by analyzing four data sets 3 HRS

 

** Notes:

  1. In addition to Python and SQL, students will also be using github to upload their individual projects.
  2. After every topic, students will be given a quiz to test their understanding of the topic. Sample questions are as follows:

 

A. What are the total sales of Brand X for February 2023 in Pesos?

Data Set:

Year Sales Brand
2023 14000 USD Brand X
2022 15000 USD Brand Z
2023 19000 USD Brand X

…

B. You are about to sort the Brand in Alphabetical Order. Complete the query below:

SELECT Brand, Sales, Year from schema.table ___________

C. If you run the query below, will it result in an error?

SELECT [Brand], “Sales”, Year from table

  1. For learning purposes, Jupyter notebook will be used for Python and Azure Notebook for SQL. In the event Azure is unavailable, we will use third party IDEs.
  1.  Instructor will provision a database for activity 8 and the final project.

 

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Course Outline

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