Description
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
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
