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Learn Python, JavaScript, and Microsoft SQL for Data science

Learn Python, JavaScript, and Microsoft SQL for Data science

  • 22 hours
  • Self-paced online
  • Certificate on completion

Part of IT & Software courses

Overview

Welcome to “Learn Python, JavaScript, and Microsoft SQL for Data Science”! This comprehensive course is your ultimate guide to mastering three essential technologies for data science: Python, JavaScript, and Microsoft SQL. Python serves as the primary language for data analysis and machine learning, while JavaScript enables interactive data visualization on the web. Microsoft SQL is a powerful relational database management system widely used for storing and querying data. By combining these three technologies, you’ll gain the skills and knowledge needed to excel in the field of data science.

Interactive video lectures by industry experts

Instant e-certificate and hard copy dispatch by next working day

Fully online, interactive course with Professional voice-over

Developed by qualified first aid professionals

Self paced learning and laptop, tablet, smartphone friendly

24/7 Learning Assistance

Discounts on bulk purchases

Main Course Features:

In-depth coverage of Python fundamentals for data analysis and machine learning

Hands-on projects and exercises to reinforce Python programming skills

Exploration of JavaScript libraries like D3.js for data visualization

Implementation of interactive data visualizations using JavaScript

Thorough understanding of Microsoft SQL for data storage and querying

Writing SQL queries to retrieve and manipulate data in Microsoft SQL Server

Real-world case studies and examples to demonstrate the integration of Python, JavaScript, and SQL in data science projects

Access to a supportive online community for collaboration and assistance

Who Should Take This Course:

Aspiring data scientists seeking to build a strong foundation in essential technologies for data science

Programmers and developers interested in expanding their skill set to include Python, JavaScript, and SQL for data analysis and visualization

Students and professionals aiming to pursue a career in data science or related fields

Learning Outcomes:

Master Python programming for data analysis, machine learning, and data manipulation

Develop interactive data visualizations using JavaScript libraries like D3.js

Utilize Microsoft SQL for data storage, retrieval, and manipulation

Write complex SQL queries to extract insights from relational databases

Integrate Python, JavaScript, and SQL for end-to-end data science projects

Build a portfolio of data science projects showcasing proficiency in Python, JavaScript, and SQL

Debug and troubleshoot code effectively in Python, JavaScript, and SQL environments

Stay updated with the latest trends and advancements in data science and technology.

Certification

Once you’ve successfully completed your course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99). All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.

Assessment

At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.

Curriculum

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