245 Programming Fundamentals courses in Glasgow delivered Online

Overview With the ever-increasing demand for Python Programming in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Python Programming may be. Learning about Python Programming or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Python Programming . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Python Programming is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Python Programming course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Python Programming course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Python Programming course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Python Programming , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Python Programming , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Python Programming , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Python Programming course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.    Course Curriculum Module-1-Introduction-to-Python.pdf Introduction-to-Python.pdf 00:00 Module-2-Variables.pdf Variables.pdf 00:00 Module-3-Conditional-Statement.pdf Conditional-Statement.pdf 00:00 Module-4-Loops.pdf Loops.pdf 00:00 Module-5-Functions.pdf Functions.pdf 00:00 Module-6-Objects.pdf Objects.pdf 00:00

Course Overview If you are a JavaScript developer who wants to master TypeScript fundamentals, jumpstart on the road to learning TypeScript with this TypeScript Tutorial For Beginners course.  TypeScript is an open-source programming language which builds on JavaScript. The advantage of Typescript over Javascript is that it adds optimal static typing to the JavaScript language. Many Javascript frameworks use typescript, such as Angular. This course covers a comprehensive set of modules to enhance your understanding of TypeScript fundamentals. It explains what typescript is and gives you a clear understanding of its significance. You will learn how to find the data type of a variable in TypeScript and understand how to define a function type variable typescript. You will also learn how to define objects using classes and use the different access modifiers. In time, you will get to grips with the specific skills to write more scalable applications. Whatever you learn in JavaScript adds value to your understanding of TypeScript. You're already halfway there if you're familiar with Javascript. Enrol right now! Learning Outcomes Understand the variables and data types Explore how to define variables using data types Gain in-depth knowledge of the operators Deepen your understanding of the object oriented principles Know how to create and use arrow functions Familiarise with the flow control statements Understand the variable prefixes Have an in-depth understanding of variable prefixes Who is this course for? The TypeScript Tutorial For Beginners course is incredibly beneficial for professionals interested in understanding the fundamentals of TypeScript. Upgrading skills in this course open doors to tremendous opportunities. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The TypeScript Tutorial For Beginners course provides useful skills to possess and would be beneficial for any related profession or industry such as: TypeScript Developer Full Stack Developer Unit 01: Introduction Module 01: What and why TypeScript 00:02:00 Module 02: TypeScript Playground 00:04:00 Module 03: Install TypeScript 00:02:00 Module 04: Install Visual Studio Code 00:01:00 Unit 02: Variables and Data Types Module 01: Introduction 00:03:00 Module 02: First Program Using Visual Studio Code 00:04:00 Module 03: Use JS in a HTML 00:02:00 Module 04: Strings 00:02:00 Module 05: Boolean 00:01:00 Module 06: Any Type 00:01:00 Module 07: Homogenous Arrays 00:03:00 Module 08: Heterogenous Arrays 00:01:00 Module 09: Using alert confirm and prompt 00:03:00 Module 10: Comments 00:02:00 Module 11: Enum Type 00:05:00 Unit 03: Operators Module 01: Arithmetic 00:03:00 Module 02: Assignment 00:04:00 Module 03: Comparison 00:04:00 Module 04: Logical 00:04:00 Module 05: Ternary 00:03:00 Unit 04: Flow Control Statements Module 01: Introduction 00:01:00 Module 02: IF Else Ladder 00:06:00 Module 03: Switch 00:04:00 Module 04: Break and Case Flow 00:03:00 Module 05: While loop 00:03:00 Unit 05: Objects and Arrays Module 01: Introduction 00:02:00 Module 02: Object Literal 00:03:00 Module 03: For-In Loop 00:02:00 Module 04: Arrays 00:04:00 Module 05: De-Structuring Arrays 00:02:00 Module 06: De-Structuring Objects 00:02:00 Unit 06: Functions Module 01: Introduction 00:02:00 Module 02: First Function 00:03:00 Module 03: Passing a parameter 00:01:00 Module 04: Passing Multiple Parameters 00:02:00 Module 05: Optional Parameters 00:04:00 Module 06: Default Values 00:01:00 Module 07: Function as parameter 00:02:00 Module 08: Returning a function 00:03:00 Module 09: Anonymous Functions 00:02:00 Module 10: Overloading 00:05:00 Module 11: REST PARAMS 00:05:00 Module 12: Using a Type on REST PARAM 00:01:00 Unit 07: Arrow Functions Module 01: Introduction 00:02:00 Module 02: First arrow function 00:03:00 Module 03: Passing Parameters 00:03:00 Module 04: Array of Arrow Functions 00:03:00 Unit 08: Variable Prefixes Module 01: let 00:03:00 Module 02: const 00:02:00 Module 02: const functions 00:02:00 Module 04: declare 00:01:00 Unit 09: Interfaces Module 01: Introduction 00:02:00 Module 02: Define an Object Interface 00:03:00 Module 03: Create and object 00:03:00 Module 04: Defining optional properties 00:01:00 Module 05: Interfaces are only compile time 00:01:00 Module 06: Function Interfaces 00:04:00 Module 07: Return Types in Functional interfaces 00:02:00 Module 08: Adding methods to Object Interfaces 00:02:00 Module 09: Array Interfaces 00:03:00 Module 10: String indexed Array Interfaces 00:03:00 Module 11: Extending interfaces 00:06:00 Unit 10: Classes Module 01: Introduction 00:01:00 Module 02: Create a class 00:03:00 Module 03: Add a constructor 00:04:00 Module 04: Add Function properties 00:02:00 Module 05: Power of TypeScript 00:01:00 Module 06: Using for-in and instanceof 00:04:00 Module 07: Implementing an interface 00:06:00 Unit 11: Inheritance Module 01: Introduction 00:03:00 Module 02: Extending a class 00:05:00 Module 03: Create Child Objects 00:07:00 Module 04: Inheriting Functionality 00:04:00 Module 05: Overriding 00:03:00 Unit 12: Access modifiers, Encapsulation and Static Module 01: Public and readonly 00:02:00 Module 02: Encapsulation 00:01:00 Module 03: Private properties 00:04:00 Module 04: Accessor methods 00:02:00 Module 05: Using Static Properties 00:04:00 Module 06: More about static 00:01:00 Module 07: Static Methods 00:03:00 Unit 13: Type Casting Module 01: String to numeric 00:04:00 Module 02: Using the toString method 00:03:00 Module 03: Object Casting 00:02:00 Unit 14: Modules Module 01: Introduction 00:01:00 Module 02: Using Function Modules 00:04:00 Module 03: Import Aliasing and Alternate Export Syntax 00:02:00 Module 04: Default Exports 00:02:00 Module 05: Class Modules 00:01:00 Module 06: Aliasing class modules 00:02:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Basic Python syntax and principles of Object Orientated Programming. Most attendees are in-work IT Professional. Private individuals are also very welcome. Evening courses also running. Our Style: Hands-on, Practical Location: Online, Instructor-led Download: anaconda.com Duration: 6 weeks, 1 evening per week, 6pm - 8pm Times: arrange a time for your time zone

Overview This comprehensive course on Algebra Fundamentals will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Algebra Fundamentals comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Algebra Fundamentals. It is available to all students, of all academic backgrounds. Requirements Our Algebra Fundamentals is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 17 sections • 83 lectures • 11:02:00 total length •Lecture 1 Introduction: 00:03:00 •Lecture 2 What is Algebra: 00:02:00 •Lecture 3 Simple Equations: 00:05:00 •Lecture 4 What are Polynomials: 00:04:00 •Lecture 5 Terms in Polynomials: 00:03:00 •Lecture 6 Degree of Polynomials: 00:05:00 •Lecture 7 Writing statements to algebraic form: 00:04:00 •Lecture 8 Integers and common mistakes in solving integers: 00:13:00 •Lecture 9 Arrangement of Terms: 00:07:00 •Lecture 10 Powers on integers: 00:04:00 •Lecture11 Simplification using BODMAS: 00:08:00 •Lecture 12 Distributive Properties in Polynomials: 00:04:00 •Lecture 13 Simplify Polynomials: 00:10:00 •Lecture 14 Additions of Polynomials: 00:06:00 •Lecture 15 Subtractions of Polynomials: 00:10:00 •Lecture 16 The rules of Indices in algebra: 00:11:00 •Lecture 17 Fractional indices: 00:10:00 •Lecture 18 Understanding indices (practice questions): 00:07:00 •Lecture 19 Problems from IGCSE Last year papers: 00:09:00 •Lecture 20 Multiplication of monomial to Polynomial: 00:09:00 •Lecture 21 Multiplication of Polynomial by Polynomial: 00:06:00 •Lecture 22 Division of algebraic expression by a monomial: 00:08:00 •Lecture 23 Division of algebraic expression by another polynomial: 00:09:00 •Lecture 24 Division of a polynomial by another polynomial with remainder: 00:11:00 •Lecture 25 Rules of brackets: 00:04:00 •Lecture 26 Simplification by removing brackets: 00:11:00 •Lecture 27 Simplification of algebraic fractions: 00:07:00 •Lecture 28 Rules to solve linear equations in one variable: 00:03:00 •Lecture 29 Solving linear equations in one variable: 00:07:00 •Lecture 30 Solving complex linear equations in one variable: 00:10:00 •Lecture 31 Word problems on linear equations in one variable: 00:13:00 •Lecture 32 What are Identities?: 00:05:00 •Lecture 33 Identity ( a + b ) ²: 00:13:00 •Lecture 35 Identity a² - b² = (a-b) (a +b ) new: 00:07:00 •Lecture 36 -- Standard Identities ( a + b + c ) ² = a ² + b ² + c ² + 2 a b + 2 a c +2 b c old: 00:07:00 •Lecture 37 Identity (x + a) (x + b) Identity Derivation & Application new: 00:08:00 •Lecture 38 Pascal's Triangle _ Identity ( a + b ) ³ new: 00:07:00 •Lecture 39 Identities( a - b ) ³, ( a ³ + b ³) and (a ³ - b ³) new: 00:13:00 •Lecture 40 - Standard Identities a ³ + b ³ + c ³ - 3 a b c: 00:10:00 •Lecture 41 -Changing the subject of formula: 00:08:00 •Lecture 42 - Linear Inequalities: 00:12:00 •Lecture 43 - Factorization by taking out common factor: 00:10:00 •Lecture 44 - Factorization by grouping the terms: 00:09:00 •Lecture 45 - factorize using identity a ² - b ²: 00:07:00 •Lecture 46 - factorize using identity (a + b )² and (a - b )² (2): 00:08:00 •Lecture 47 - factorize using identity ( a + b + c ) ²: 00:05:00 •Lecture 48 - factorization by middle term split: 00:12:00 •Lecture 49 -Simplification of algebraic fractions: 00:06:00 •Lecture 50 All that you need to know about co ordinate axis: 00:04:00 •Lecture 51 Some important facts needed to draw line graph: 00:03:00 •Lecture 52 - How to draw a line graph on coordinate plane: 00:03:00 •Lecture 53 Drawing line graphs: 00:06:00 •Lecture 54 Simultaneous Linear Equations in two variables- intro: 00:03:00 •Lecture 55 Graphical method of solving linear equations: 00:06:00 •Lecture 56 Graphical method - more problems: 00:10:00 •Lecture 57 Method of Elimination by substitution: 00:09:00 •Lecture 58 Method of Elimination by Equating coefficients: 00:11:00 •Lecture 59 Method of Elimination by cross multiplication: 00:07:00 •Lecture 60 Equations reducible to simultaneous linear equations: 00:12:00 •Lecture 61 Word Problems on Linear equations: 00:18:00 •Lecture 62 Polynomials and Zeros of polynomials: 00:10:00 •Lecture 63 Remainder Theorem: 00:04:00 •Lecture 64 Factor Theorem: 00:08:00 •Lecture 65 Practice problems on Remainder and Factor Theorem: 00:09:00 •Lecture 66 Factorization using factor Theorem: 00:10:00 •Lecture 67 Zeros of polynomials α, β & γ: 00:10:00 •Lecture 68 Relation between zeros and coefficients of a polynomials: 00:13:00 •Lecture 69 Finding polynomials if zeros are known: 00:06:00 •Lecture 70 Practice problems on zeros of polynomials: 00:10:00 •Lecture 71Problems solving with α and β (part 1): 00:11:00 •Lecture 72 Problems solving with α and β (part 2): 00:10:00 •Lecture73 what are Quadratic equations: 00:03:00 •Lecture 74 Solutions by factorization method: 00:12:00 •Lecture 75 Solutions by completing square formula: 00:06:00 •Lecture 76 Deriving Quadratic formula: 00:05:00 •Lecture 77 Practice problems by Quadratic formula: 00:07:00 •Lecture 78 Solving complex quadratic equations by Quadratic Formula: 00:11:00 •Lecture 79 Solutions of reducible to Quadratic Formula: 00:09:00 •Lecture 80 Skilled problems on Quadratic Equations: 00:07:00 •Lecture 81 Exponential problems reducible to Quadratic Equations: 00:06:00 •Lecture 82 Nature of Roots of Quadratic Equations: 00:09:00 •Lecture 83 Word problems on quadratic Equations Part 1: 00:13:00 •Lecture 84 Word problems on quadratic Equations Part 2: 00:11:00

Course Overview Find the ultimate Python Developer roadmap by taking this 2021 Python Programming From Beginner to Expert course. Through this course, you will gain the fundamental skills to create your Python programs from scratch. In this step-by-step 2021 Python Programming From Beginner to Expert course, you will learn core Python skills from beginners to advanced features. The training begins by outlining the software installation procedure, guiding you through a series of Python basic data types, Python operators, advanced data types, Python functions and loops. You will learn how to handle errors in Python and comprehend the advanced functions in Python. The skills you develop in the program will enable you to create and run your first Python project. Enroll today and take your Python programming skills to the next level! Learning Outcomes Learn how to install Python on various operating systems Gain in-depth knowledge of the basic data types in Python Strengthen your knowledge of Python operators Learn about Python advanced data types Deepen your understanding of Python advanced functions Learn step-by-step how to handle errors Who is this course for? Anyone interested in learning Python programming and exploring the path to become a Python developer can take this 2021 Python Programming From Beginner to Expert course. This course opens the door for tremendous opportunities. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The 2021 Python Programming From Beginner to Expert course would be beneficial for any related profession or industry such as: Python Developer Python Programmer Product Manager Data Analyst Module 01: Introduction to Python Programming from A-Z Introduction To Python Section Overview 00:05:00 What is Python Programming? 00:10:00 Who is This Course For? 00:05:00 Python Programming Marketplace 00:06:00 Python Job Opportunities 00:05:00 How To Land a Python Job Without a Degree 00:08:00 Python Programmer Job Roles 00:09:00 Python from A-Z Course Structure 00:04:00 Module 02: Getting Familiar with Python Getting Familiar with Python Section Overview 00:06:00 Installing Python on Windows 00:10:00 Anaconda and Jupyter Notebooks Part 1 00:08:00 Anaconda and Jupyter Notebooks Part 2 00:16:00 Comments 00:05:00 Python Syntax 00:02:00 Line Structure 00:03:00 Line Structure Exercise 00:07:00 Joining Lines 00:05:00 Multiple Statements on a Single Line 00:05:00 Indentation 00:08:00 Module 03: Basic Data Types Basic Data Types Section Overview 00:08:00 String Overview 00:10:00 String Manipulation 00:07:00 String Indexing 00:04:00 String Slicing 00:08:00 Printing 00:10:00 Python Variables 00:08:00 Integers and Floats 00:08:00 Booleans 00:05:00 Mini Project 1 : Letter Counter 00:20:00 Module 04: Python Operators Python Operators Section Overview 00:04:00 Comparison Operators 00:09:00 Arithmetic Operators 00:08:00 Assignment Operators 00:04:00 Logical Operators 00:13:00 Identity Operators 00:05:00 Membership Operators 00:02:00 Bitwise Operators 00:08:00 Module 05: Advanced Data Types Python Advanced Data Types Section Overview 00:11:00 Sets 00:06:00 List Overview 00:05:00 List Slicing and Indexing 00:04:00 Tuples 00:02:00 Dictionaries 00:11:00 When to use each one? 00:05:00 Compound Data Types 00:03:00 Module 06: Control Flow Part 1 Control Flow Part 1 Section Overview 00:15:00 Introduction to Control Flow 00:01:00 Basic Conditional Statements 00:14:00 More Conditional Statements 00:05:00 For Loops 00:10:00 While Loops 00:12:00 Module 07: Control Flow Part 2 Control Flow Part 2 Section Overview 00:02:00 Break Statements 00:08:00 Continue Statements 00:05:00 Zip Function 00:07:00 Enumerate Function 00:04:00 List Comprehension 00:04:00 Module 08: Python Functions Python Functions Section Overview 00:03:00 Introduction to Functions 00:05:00 Python help Function 00:03:00 Defining Functions 00:09:00 Variable Scope 00:08:00 Doc Strings 00:04:00 Module 09: User Input and Error Handling User Input and Error Handling Section Overview 00:02:00 Introduction to Error Handling 00:03:00 User Input 00:04:00 Syntax Errors 00:04:00 Exceptions 00:11:00 Handling Exceptions Part 1 00:08:00 Handling Exceptions Part 2 00:08:00 Module 10: Python Advanced Functions Python Advanced Functions Section Overview 00:05:00 Lambda Functions 00:05:00 Functions args and kwargs 00:10:00 Iterators 00:08:00 Generators and Yield 00:12:00 Map Function 00:14:00 Filter Function 00:08:00 Module 11: Python Scripting and Libraries Python Scripting and Libraries Section Overview 00:05:00 What is a script? 00:01:00 What is an IDE? 00:17:00 What is a text editor? 00:12:00 From Jupyter Notebook to VScode Part 1 00:15:00 From Jupyter Notebook to VScode Part 2 00:05:00 Importing Scripts 00:03:00 Standard Libraries 00:04:00 Third Party Libraries 00:06:00 Module 12: NumPy NumPy Section Overview 00:04:00 Introduction to NumPy 00:04:00 Why use NumPy? 00:04:00 NumPy Arrays 00:10:00 Reshaping, Accessing, and Modifying 00:07:00 Slicing and Copying 00:06:00 Inserting, Appending, and Deleting 00:10:00 Array Logical Indexing 00:04:00 Broadcasting 00:08:00 Module 13: Pandas Introduction to Pandas 00:17:00 Pandas Series 00:17:00 Pandas Series Manipulation 00:17:00 Pandas DataFrame 00:17:00 Pandas DataFrame Manipulation 00:13:00 Dealing with Missing Values 00:10:00 Module 14: Introduction to OOP Functional vs OOP 00:06:00 OOP Key Definitions 00:04:00 Create your First Class 00:12:00 How to Create and Use Objects 00:06:00 How to Modify Attributes 00:12:00 Module 15: Advanced OOP Python Decorators 00:27:00 Property Decorator 00:09:00 Class Method Decorator 00:07:00 Static Methods Decorator 00:10:00 Inheritance 00:21:00 Module 16: Starting a Career in Python Python Career Section Overview 00:06:00 Getting Started with Freelancing 00:09:00 Building A Brand 00:12:00 Personal Branding 00:13:00 Importance of Having Website/Blog 00:04:00 Networking Do's and Don'ts 00:04:00 Top Freelance Websites 00:08:00 Creating A Python Developer Resume 00:06:00 Resources Resources - Python Programming Beginner to Expert Course 00:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Javascript Asynchronous Basics is a course that will assist you to become a front-end developer with thorough and

Description: Are you interested in a career in computer science? Programming is the art of writing useful, maintainable, and extensible source codes which can be read or compiled by a computer system to perform a significant task. Take your first step towards learning core programming concepts and equip yourself with the practical knowledge and skills to resolve complicated problems. Discover all you need to know about programming language with this computer science course. By learning the correct programming theory, you will be able to analyse a problem and identify suitable solutions to those problems, which is a key part of web development. Apart from the theories of Algorithm analysis, this computer programming course also teaches the number system, arrays and their advantages, the process of analysing a problem, nodes and their Importance, and various sorting algorithms and their comparisons. There are no entry requirements for this course and you can study from the comfort of your own home. Enrol in this Diploma in Computer Science and Programming course today and learn to write code like an expert. Who is the course for? Anyone who wants to become a Good Programmer Anyone interested in the Computer Science Discipline Anyone who wants to learn how to problem solve like a Computer Scientist Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £14.99 or in PDF format at a cost of £11.99. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction Kurt Anderson - Promo FREE 00:02:00 Kurt Anderson - 1 Introduction 00:01:00 Kurt Anderson - 2 Binary System 00:11:00 Analyzing Algorithms Kurt Anderson - 3 Complexity Introduction 00:02:00 Kurt Anderson - 4 Math Refresher Logarithmic Functions 00:11:00 Kurt Anderson - 5 Math Refresher Factorial Functions.TS 00:03:00 Kurt Anderson - 6 Math Refresher Algebraic Expressions.TS 00:03:00 Kurt Anderson - 7 n-notation 00:18:00 Kurt Anderson - 8 Big O 00:13:00 Kurt Anderson - 9 Big O Real World Example 00:10:00 Arrays Kurt Anderson - 10 How is Data Stored 00:09:00 Kurt Anderson - 11 Fixed Arrays 00:20:00 Kurt Anderson - 12 Circular Arrays 00:08:00 Kurt Anderson - 13 Dynamic Arrays 00:16:00 Kurt Anderson - 14 Array Review 00:08:00 Kurt Anderson - 15 Array Real World Examples 00:06:00 Linked Lists Kurt Anderson - 16 Nodes 00:04:00 Kurt Anderson - 16 Linked List 00:14:00 Kurt Anderson - 17 Linked List Run Times 00:15:00 Kurt Anderson - 18 Doubly Linked Lists 00:08:00 Kurt Anderson - 19 Tail Pointer 00:05:00 Kurt Anderson - 20 Linked List Real World Examples 00:03:00 Kurt Anderson - 21 Linked List Review 00:04:00 Stacks and Queues Kurt Anderson - 22 Stacks 00:10:00 Kurt Anderson - 20 Stack Example 00:11:00 Kurt Anderson - 23 Queues 00:09:00 Kurt Anderson - 24 Queue Examples 00:10:00 Kurt Anderson - 25 Queue and Stack Run Times 00:06:00 Kurt Anderson - 26 Stack and Queues Real World Examples 00:07:00 Sorting Algorithms Kurt Anderson - 27 Sorting Algorithm Introdcution 00:02:00 Kurt Anderson - 28 Bubble Sort 00:10:00 Kurt Anderson - 29 Selection Sort 00:10:00 Kurt Anderson - 30 Insertion Sort 00:09:00 Kurt Anderson - 31 Quick Sort 00:15:00 Kurt Anderson - 32 Quick Sort Run Times 00:10:00 Kurt Anderson - 33 Merge Sort 00:12:00 Kurt Anderson - 34 Merge Sort Run Times 00:08:00 Kurt Anderson - 35 Stable vs Nonstable 00:07:00 Kurt Anderson - 36 Sorting Algorithm Real World Examples 00:04:00 Trees Kurt Anderson - 37 Basics of Trees 00:08:00 Kurt Anderson - 38 Binary Search Tree 00:09:00 Kurt Anderson - 39 BST Run Times 00:08:00 Kurt Anderson - 40 Tree Traversals 00:13:00 Kurt Anderson - 41 Tree Real World Examples 00:05:00 Heaps Kurt Anderson - 42 Heap Introduction 00:04:00 Kurt Anderson - 43 Heap Step by Step 00:12:00 Kurt Anderson - 44 Heap Real World Examples 00:07:00 Conclusion Kurt Anderson - 45 Thank You 00:01:00 Course Certification Order Your Certificates and Transcripts 00:00:00

Register on the JavaScript Functions today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The JavaScript Functions is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The JavaScript Functions Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the JavaScript Functions, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Unit 01: Introduction Introduction 00:02:00 Why use JavaScript functions? 00:06:00 Unit 02: Defining and Invoking Functions Defining and Invoking Functions 00:04:00 Demo: Invoking and Defining JavaScript functions 00:07:00 Alternate ways to define functions 00:01:00 Demo: Alternate ways to define functions 00:04:00 Unit 03: Function Scope What is function scope? 00:03:00 Demo: Exploring Function Scope 00:04:00 Child Function Scope 00:02:00 Demo: Child Function Scope 00:06:00 Unit 04: Composing Functions What is function composition? 00:02:00 Demo: Currying Functions 00:05:00 Factory Functions 00:01:00 Demo: Factory Functions 00:04:00 Unit 05: Asynchronous Functions What are callback functions? 00:01:00 Demo: Callback Functions 00:04:00 Promises, Async and Generators 00:06:00 The 'this' keyword & demo 00:04:00 Self-Invoking Functions & demo 00:03:00 Error Catching & demo 00:04:00 Object Creators & demo 00:03:00 Course Summary 00:02:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00