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• What’s included:

Learn Python, JavaScript, and Microsoft SQL for Data science

• Course Highlights

Python is a general-purpose programming language that is widely used in data science. It is known for its simplicity, readability, and versatility. In this course, you will learn the basics of Python, including variables, data types, operators, conditional statements, control flow statements, functions, and error handling. You will also learn how to use Python for data science tasks such as cleaning, analysis, and visualization.

JavaScript is a scripting language that is primarily used for front-end web development. However, it can also be used for data science tasks such as data visualization and data analysis. In this course, you will learn the basics of JavaScript, including variables, data types, operators, conditional statements, control flow statements, functions, and error handling. You will also learn how to use JavaScript for data science tasks such as data cleaning and data visualization.

Microsoft SQL is a relational database management system (RDBMS) that stores, manages, and retrieves data. It is one of the most popular RDBMSs in the world. In this course, you will learn the basics of Microsoft SQL, including SQL statements, data manipulation statements, data query statements, and data definition statements. You will also learn to use Microsoft SQL to create, read, update, and delete data from a database.

• Course Modules

  • Section 01: JavaScript Introduction
  • Section 02: JavaScript Basics
  • Section 03: JavaScript Operators
  • Section 04: JavaScript Conditional Statements
  • Section 05: JavaScript Control Flow Statements
  • Section 06: JavaScript Functions
  • Section 07: JavaScript Error Handling
  • Section 08: JavaScript Client-Side Validations
  • Section 09: Python Introduction
  • Section 10: Python Basic
  • Section 11: Python Strings
  • Section 12: Python Operators
  • Section 13: Python Data Structures
  • Section 14: Python Conditional Statements
  • Section 15: Python control flow statements
  • Section 16: Python core games
  • Section 17: Python functions
  • Section 18: Python args, KW args for Data Science
  • Section 19: Python project
  • Section 20: Python Object oriented programming [OOPs]
  • Section 21: Python Methods
  • Section 22: Python Class and Objects
  • Section 23: Python Inheritance and Polymorphism
  • Section 24: Python Encapsulation and Abstraction
  • Section 25: Python OOPs Games
  • Section 26: Python Modules and Packages
  • Section 27: Python Error Handling
  • Section 28: Microsoft SQL[MS] Introduction
  • Section 29: MS SQL Statements
  • Section 30: MS SQL Filtering Data
  • Section 31: MS SQL Functions
  • Section 32: MS SQL Joins
  • Section 33: MS SQL Advanced commands
  • Section 34: MS SQL Structure and Keys
  • Section 35: MS SQL Queries
  • Section 36: MS SQL Structure queries
  • Section 37: MS SQL Constraints
  • Section 38: MS SQL Backup and Restore

• See the full course description

Completion of this course does not result in a degree or qualify participants to practice professionally.