Learn Python, JavaScript, and Microsoft SQL for Data science

Ready to unlock high-demand tech skills and step into a data-driven future? Master Python, JavaScript, and Microsoft SQL – the must-have languages for data science success.
Join our instructor-led course designed to elevate your career in the UK’s booming data industry.

Data science is one of the fastest-growing fields in the UK, with professionals earning £40k to £90k annually. Companies urgently need experts who can analyse, interpret, and manage data efficiently. This course equips you with essential programming and database skills, making you job-ready for roles like Data Analyst (£35k–£60k), Data Scientist (£50k–£90k), and Database Administrator (£40k–£75k).

From interactive web applications to powerful data analysis, this comprehensive course teaches you three of the most in-demand programming languages—Python, JavaScript, and Microsoft SQL. Whether you want to become a data analyst, software developer, or business intelligence specialist, this course gives you the practical knowledge and hands-on projects to build real-world skills. Designed for beginners and career switchers alike, you’ll progress from basic programming to advanced database querying in a structured, tutor-supported learning environment.

What is Included:

• Learn Python, JavaScript & Microsoft SQL from scratch
• Flexible learning options with lifetime access
• Expert instructor-led curriculum with hands-on projects
• Dedicated tutor support throughout your learning journey
• CPD Accredited – receive a recognised certificate upon completion

What Makes This Course a Smart Career Move?

In today’s global job market, the ability to analyse data, write code, and build scalable digital solutions is no longer optional—it’s essential. This course equips you with three of the most in-demand skills worldwide: programming with Python, scripting with JavaScript, and managing data with Microsoft SQL.

By mastering these core technologies, you’ll be prepared for a wide range of tech-driven roles, from data science and business intelligence to software development and automation. Employers across industries—whether in the UK, Europe, North America, or Asia—are actively looking for professionals who can bridge the gap between raw data and actionable insights. This course helps you build a strong technical foundation, opening doors to international job opportunities and setting you up for long-term career growth in the ever-evolving digital economy.

Enrol now and start your journey into the future of tech!

Reed Courses Certificate of Completion

Digital certificate - Included

• Section 01: JavaScript Introduction 1:13:05

  • 1: Introduction 02:43
  • 2: How to ask great questions 01:21
  • 3: Installing Code Editor 03:48
  • 4: What is JavaScript 08:54
  • 5: Hello World Program 13:32
  • 6: Getting Output 10:56
  • 7: Internal JavaScript 13:28
  • 8: External JavaScript 08:49
  • 9: Inline JavaScript 03:45
  • 10: Async and defer 05:49

• Section 02: JavaScript Basics 39:15

  • 11: Variables 12:40
  • 12: Data Types 09:40
  • 13: Numbers 05:47
  • 14: Strings 05:54
  • 15: String Formatting 05:14

• Section 03: JavaScript Operators 24:12

  • 16: Arithmetic operators 07:14
  • 17: Assignment operators 03:07
  • 18: Comparison operators 06:06
  • 19: Logical operators 07:45

• Section 04: JavaScript Conditional Statements 09:46

  • 20: If-else statement 05:18
  • 21: If-else-if statement 04:28

• Section 05: JavaScript Control Flow Statements 22:10

  • 22: 319 While loop 08:31
  • 23: 320 Do-while loop 02:29
  • 24: 321 For loop 07:56
  • 25: 322 Coding Exercise 01:35
  • 26: 323 Solution for Coding Exercise 01:39

• Section 06: JavaScript Functions 19:22

  • 27: 324 Creating a Function 07:23
  • 28: 325 Function Call() 06:51
  • 29: 326 Function with parameters 05:08

• Section 07: JavaScript Error Handling 21:59

  • 30: 327 Try-catch 05:24
  • 31: 328 Try-catch-finally 16:35

• Section 08: JavaScript Client-Side Validations 20:58

  • 32: 329 On Submit Validation 08:42
  • 33: 330 Input Numeric Validation 12:16

• Section 09: Python Introduction 42:09

  • 34: 601 Introduction to Python 02:16
  • 35: 602 Python vs Other Languages 03:48
  • 36: 603 Why Its Popular 03:33
  • 37: 604 Command Line Basics 06:43
  • 38: 605 Python Installation (Step By Step) 05:47
  • 39: 606 PyCharm IDE Installation 07:56
  • 40: 607 Getting Start PyCharm IDE 04:44
  • 41: 608 First Python Hello World Program 07:22

• Section 10: Python Basic 48:18

  • 42: 609 Variables 16:18
  • 43: 610 Data Types 13:09
  • 44: 611 Type Casting 07:04
  • 45: 612 User Inputs 07:54
  • 46: 613 Comments 03:53

• Section 11: Python Strings 27:22

  • 47: 614 Strings 04:58
  • 48: 615 String Indexing 05:21
  • 49: 616 String Slicing 03:52
  • 50: 617 String Built-in Functions 08:36
  • 51: 618 Formatting String (Dynamic Data) 04:35

• Section 12: Python Operators 31:11

  • 52: 619 Arithmetic Operators 07:48
  • 53: 620 Assignment Operators 04:40
  • 54: 621 Comparison Operators 05:20
  • 55: 622 Logical Operators 02:01
  • 56: 623 AND Operator 04:09
  • 57: 624 OR Operator 02:16
  • 58: 625 NOT Operator 02:52
  • 59: 626 Booleans 02:05

• Section 13: Python Data Structures 1:07:41

  • 60: 627 Arrays in Earler 01:45
  • 61: 628 Lists 05:37
  • 62: 629 Add List Items 02:54
  • 63: 630 Remove List Items 01:16
  • 64: 631 Sort Lists 02:46
  • 65: 632 Join Lists 07:35
  • 66: 633 Tuples 07:43
  • 67: 634 Update tuples 06:58
  • 68: 635 Join tuples 01:50
  • 69: 636 Dictionaries 06:02
  • 70: 637 Add Dictionary Items 04:26
  • 71: 638 Remove Dictionary Items 02:41
  • 72: 639 Nested Disctionaries 04:00
  • 73: 640 Sets 03:39
  • 74: 641 Add Set Items 03:07
  • 75: 642 Remove Set Items 01:27
  • 76: 643 Join Set Items 03:55

• Section 14: Python Conditional Statements 16:07

  • 77: 644 If Statement 03:20
  • 78: 645 If-else Statement 04:08
  • 79: 646 If-elif-else Statement 03:58
  • 80: 647 If Statement Coding Excercise 04:41

• Section 15: Python control flow statements 33:01

  • 81: 648 Flow Charts 06:25
  • 82: 649 While Loops Statement 09:42
  • 83: 650 For Loops Statement 06:18
  • 84: 651 The range() Function 03:37
  • 85: 652 Nested Loops 03:29
  • 86: 653 2D List using Nested Loop 03:30

• Section 16: Python core games 16:54

  • 87: 654 Guessing Game 07:14
  • 88: 655 Car Game 09:40

• Section 17: Python functions 14:10

  • 89: 656 Creating a Function 03:09
  • 90: 657 Calling a Function 06:03
  • 91: 658 Function with Arguments 04:58

• Section 18: Python args, KW args for Data Science 10:06

  • 92: 659 args, Arbitary Arguments 04:05
  • 93: 660 kwargs, Arbitary Keyword Arguments 06:01

• Section 19: Python project 16:52

  • 94: 661 Project Overview 03:29
  • 95: 662 ATM RealTime Project 13:23

• Section 20: Python Object oriented programming [OOPs] 39:21

  • 96: 663 Introduction to Class 06:45
  • 97: 664 Create a Class 09:28
  • 98: 665 Calling a Class Object 07:51
  • 99: 666 Class Parameters - Objects 05:14
  • 100: 667 Access Modifiers(theory) 10:03

• Section 21: Python Methods 45:50

  • 101: 668 Introduction to methods 05:49
  • 102: 669 Create a method 07:13
  • 103: 670 Method with parameters 11:41
  • 104: 671 Method default parameter 06:20
  • 105: 672 Multiple parameters 05:19
  • 106: 673 Method return keyword 04:23
  • 107: 674 Method Over loading 05:05

• Section 22: Python Class and Objects 19:28

  • 108: 675 Introduction to OOPs 04:42
  • 109: 676 Classes and Objects 07:55
  • 110: 677 Class Constructors 06:51

• Section 23: Python Inheritance and Polymorphism 35:42

  • 111: 678 Introduction 04:01
  • 112: 679 Inheritance 13:10
  • 113: 680 Polymorphism 12:43
  • 114: 681 Assessment Test 02:58
  • 115: 682 Solution for Assessment Test 02:50

• Section 24: Python Encapsulation and Abstraction 37:11

  • 116: 683 Introduction 02:52
  • 117: 684 Access Modifiers (public, protected, private) 20:29
  • 118: 685 Encapsulation 06:43
  • 119: 686 Abstraction 07:07

• Section 25: Python OOPs Games 13:15

  • 120: 687 Dice Game 06:24
  • 121: 688 Card and Deck Game Playing 06:51

• Section 26: Python Modules and Packages 45:10

  • 122: 689 PIP command installations 11:32
  • 123: 690 Modules 12:22
  • 124: 691 Built-in Modules 03:13
  • 125: 692 Packages 07:30
  • 126: 693 Reading CSV files 10:33

• Section 27: Python Error Handling 21:33

  • 127: 694 Errors – Types of Errors 07:44
  • 128: 695 Try - Except Exceptions Handling 07:15
  • 129: 696 Try-Except-Finally Blocks 06:34

• Section 28: Microsoft SQL[MS] Introduction 58:13

  • 130: 901 Introduction 03:54
  • 131: 902 Overview of Databases 08:56
  • 132: 903 MSSQL Installation 27:19
  • 133: 904 MSSQL SSMS Installation 07:50
  • 134: 905 Connecting to MS-SQL (Windows Authentication) 04:40
  • 135: 906 Connecting to MS-SQL (SQL Server Authentication) 05:34

• Section 29: MS SQL Statements 1:05:07

  • 136: 907 SQL statement basic 12:53
  • 137: 908 SELECT Statement 16:28
  • 138: 909 SELECT DISTINCT 16:53
  • 139: 910 Column AS Statement 09:12
  • 140: 911 COUNT 09:41

• Section 30: MS SQL Filtering Data 1:06:04

  • 141: 912 SELECT WHERE Clause – One 04:58
  • 142: 913 SELECT WHERE Clause – Two 11:37
  • 143: 914 ORDER BY 09:33
  • 144: 915 TOP in MSSQL 05:38
  • 145: 916 BETWEEN 13:13
  • 146: 917 IN Operator - Condition 08:12
  • 147: 918 LIKE 12:53

• Section 31: MS SQL Functions 1:07:57

  • 148: 919 Overview of GROUP BY 08:12
  • 149: 920 Aggregation Function – SUM() 11:51
  • 150: 921 Aggregation Function – MIN()-MAX() 08:21
  • 151: 922 GROUP BY – One(theory) 10:54
  • 152: 923 GROUP BY – Two(practical) 13:54
  • 153: 924 HAVING 14:45

• Section 32: MS SQL Joins 58:26

  • 154: 925 Overview of JOINS 06:39
  • 155: 926 Introduction to JOINS 07:07
  • 156: 927 AS Statement 03:44
  • 157: 928 INNER Join 12:20
  • 158: 929 Full Outer Join 07:23
  • 159: 930 Left Outer Join 05:58
  • 160: 931 Right Outer Join 07:51
  • 161: 932 Union 07:24

• Section 33: MS SQL Advanced commands 57:14

  • 162: 933 Basic of Advanced SQL Commands 04:20
  • 163: 934 Timestamp 11:39
  • 164: 935 Extract from Timestamp 06:21
  • 165: 936 Mathematical Scalar Functions 11:07
  • 166: 937 String Functions 16:39
  • 167: 938 SubQuery 07:08

• Section 34: MS SQL Structure and Keys 50:39

  • 168: 939 Basic of Database and Tables 09:41
  • 169: 940 Data Types 10:54
  • 170: 941 Select Datatype on SSMS 05:05
  • 171: 942 How to set Primary Key 05:36
  • 172: 943 How to set Foreign Key 12:11
  • 173: 944 Create Table using SQL Script 07:12

• Section 35: MS SQL Queries 21:03

  • 174: 945 Insert 06:28
  • 175: 946 Update 08:01
  • 176: 947 Delete 06:34

• Section 36: MS SQL Structure queries 07:15

  • 177: 948 Alter Table 04:20
  • 178: 949 Drop Table 02:55

• Section 37: MS SQL Constraints 37:08

  • 179: 950 Check Constraint 14:07
  • 180: 951 NOT NULL Constraint 11:46
  • 181: 952 UNIQUE Constraint 11:15

• Section 38: MS SQL Backup and Restore 21:56

  • 182: 953 Overview of Database and Tables 03:31
  • 183: 954 Creating a Database backup using SSMS 10:50
  • 184: 955 Restoring a Database from backup using SSMS 07:35

This course is designed to help you master three core technologies that power data science and analytics: Python, JavaScript, and Microsoft SQL. Whether you're looking to start a new career in tech or want to upskill for better job opportunities, this course provides everything you need to learn programming fundamentals and practical data manipulation.

You’ll start with the basics and move into advanced applications like object-oriented programming in Python, data filtering in SQL, and client-side scripting in JavaScript. With expert guidance and hands-on projects, you'll build the confidence and competence to work in real-world data environments.

Learning Objectives:

• Understand programming fundamentals using Python and JavaScript
• Manipulate and analyse data using Microsoft SQL
• Apply conditional logic, loops, and functions across languages
• Use OOP principles to build scalable applications in Python
• Gain job-ready skills for roles in data analysis and development

Why Should You Take This Course?

This course combines three essential technologies in one learning path, offering exceptional value and versatility. Python dominates the data science space, SQL is vital for managing and querying large datasets, and JavaScript bridges the gap between data and user-facing applications. Learning them together not only sharpens your programming skills but also expands your career opportunities across different tech domains.

Course Curriculum

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

• Aspiring data analysts and developers
• Career switchers seeking practical programming skills
• Graduates looking to enter tech roles
• Professionals aiming to upskill in data science
• Anyone interested in learning Python, JavaScript, or SQL

• No experience required
• Just an internet connection and a compatible device
• Willingness to learn and grow your skills

• Data Analyst (£30k to £45k)
• Business Intelligence Analyst (£35k to £50k)
• Python Developer (£40k to £60k)
• SQL Developer (£35k to £55k)
• Full Stack Developer (£45k to £65k)

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