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Duration 5 Days 30 CPD hours This course is intended for In order to be successful in this course you should have incoming hands-on experience with another programming language. This course is not for non-developers or new developers. Possible roles that may attend this course include: Software Developers: Professionals who have been working with other programming languages and want to expand their skillset by learning Java and its object-oriented features. Web Developers: Those who work on web applications and want to enhance their back-end development capabilities with Java. Mobile App Developers: Developers who wish to enter the world of Android app development, where Java is a widely used language for creating mobile applications. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how?it relates to OO programming and the Object Model Learn to use Java exception handling Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Become familiar with the concept of functional programming using Lambda Expressions Process large amounts of data using the Stream API introduced in Java 8 Discover the new Date/Time API Use the JDBC API for database access Work with annotations Take advantage of the Java tooling that is available with the programming environment being used in the class Java 8 Features: Lambda Expressions, Method and Constructor references, The Streams API, Collectors, The Optional class Geared for experienced developers, Basic Java Programming for Developers New to OO, this hands-on, workshop-style course will provide you with an immersive learning experience that will expand your skillset and open doors to new opportunities within the ever-growing technology landscape. Mastering Java and its powerful capabilities will provide you with the competitive edge you need to stand out in today's fast-paced development world. Working in a hands-on learning environment led by our expert coach, you?ll thoroughly explore the foundations of the Java platform, essential programming concepts, and advanced topics, ensuring you acquire a strong understanding of the language and its ecosystem. The object-oriented programming principles taught in this course promote code reusability and maintainability, enabling you to streamline development processes and reduce long-term costs. As you progress through the course, you will also gain familiarity with using an IDE, enhancing your development workflow and collaboration with other Java developers, enabling you to integrate seamlessly into new projects and teams. You?ll also gain practical experience in applying the concepts and techniques learned, solidifying your newly acquired skills and facilitating their direct application in real-world scenarios. You?ll exit this course empowered to create robust, scalable, and efficient Java-based applications that drive innovation and growth for your organization The Java Platform The Java Platform Lifecycle of a Java Program Responsibilities of JVM Documentation and Code Reuse Using the JDK Explain the JDK?s file structure Use the command line compiler to compile a Java class Use the command line Java interpreter to run a Java application class The IntelliJ Paradigm Introduce the IntelliJ IDE The Basics of the IntelliJ interface IntelliJ Projects and Modules Creating and running Java applications Writing a Simple Class Write a Java class that does not explicitly extend another class Define instance variables for a Java class Create object instances Primitives vs Object References Implement a main method to create an instance of the defined class Adding Methods to the Class Write a class with accessor methods to read and write instance variables Write a constructor to initialize an instance with data Write a constructor that calls other constructors of the class to benefit from code reuse Use the this keyword to distinguish local variables from instance variables Object-Oriented Programming Real-World Objects Classes and Objects Object Behavior Methods and Messages Inheritance, Abstraction, and Polymorphism Encapsulation Inheritance Method Overriding Polymorphism Essential Java Programming Essential Java Programming Language Statements Arithmetic operators Operators to increment and decrement numbers Comparison operators Logical operators Return type of comparison and logical operators Use for loops Switch Expressions Switch Expressions and yield Using Strings and Text Blocks Create an instance of the String class Test if two strings are equal Get the length of a string Parse a string for its token components Perform a case-insensitive equality test Build up a string using StringBuffer Contrast String, StringBuffer,and StringBuilder Compact Strings Text Blocks Specializing in a Subclass Constructing a class that extends another class Implementing equals and toString Writing constructors that pass initialization data to parent constructor Using instanceof to verify type of an object reference Pattern matching for instanceof Overriding subclass methods Safely casting references to a more refined type Fields and Variables Discuss Block Scoping Rules Distinguish between instance variables and method variables within a method Explain the difference between the terms field and variable List the default values for instance variables Final and Static fields and methods Local Variable type inference Using Arrays Declaring an array reference Allocating an array Initializing the entries in an array Writing methods with a variable number of arguments Records Data Objects in Java Introduce records as carrier of immutable data Defining records Java Packages and Visibility Use the package keyword to define a class within a specific package Discuss levels of accessibility/visibility Using the import keyword to declare references to classes in a specific package Using the standard type naming conventions Visibility in the Java Modular System Correctly executing a Java application class The Java modular system Defining Modules Inheritance and Polymorphism Write a subclass with a method that overrides a method in the superclass Group objects by their common supertype Utilize polymorphism Cast a supertype reference to a valid subtype reference Use the final keyword on methods and classes to prevent overriding Interfaces and Abstract Classes Define supertype contracts using abstract classes Implement concrete classes based on abstract classes Define supertype contracts using interfaces Implement concrete classes based on interfaces Explain advantage of interfaces over abstract classes Explain advantage of abstract classes over interfaces Static, default and private methods in interfaces Sealed classes Introduce Sealed classes The sealed and permits modifiers Sealed Interfaces Exception Handling Introduction to Exception Handling Introduce the Exception architecture Defining a try/catch blocks Checked vs Unchecked exceptions Exceptions Defining your own application exceptions Automatic closure of resources Suppressed exceptions Handling multiple exceptions in one catch Helpful Nullpointers Enhanced try-with-resources Java Developer's Toolbox Developing applications Introduce the wrapper classes Explain Autoboxing and Unboxing Converting String representations of primitive numbers into their primitive types Defining Enumerations Using static imports Deprecating methods Advanced Java Programming Introduction to Generics Generics and Subtyping Bounded Wildcards Generic Methods Legacy Calls To Generics When Generics Should Be Used Lambda Expressions and Functional Interface Understanding the concept of functional programming Writing lambda expressions Understanding functional interfaces Collections Provide an overview of the Collection API Review the different collection implementations (Set, List and Queue) Explore how generics are used with collections Examine iterators for working with collections Using Collections Collection Sorting Comparators Using the Right Collection Lambda expressions in Collections Bonus Topics: Time Permitting Streams Understanding the problem with collections in Java Thinking of program solutions in a declarative way Use the Stream API to process collections of data Understand the difference between intermediate and terminal stream operations Filtering elements from a Stream Finding element(s) within a Stream Collecting the elements from a Stream into a List takeWhile and dropWhile intermediate operations Collectors Using different ways to collect the items from a Stream Grouping elements within a stream Gathering statistics about numeric property of elements in a stream

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Overview This comprehensive course on Pure Mathematics Fundamentals will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Pure Mathematics 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 Pure Mathematics Fundamentals. It is available to all students, of all academic backgrounds. Requirements Our Pure Mathematics 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 14 sections • 193 lectures • 03:43:00 total length •About Course: 00:02:00 •Quick Guide: 00:01:00 •Topics of Essential Revision - 1: 00:00:00 •Negative numbers and operations on Integers: 00:14:00 •The rules of Indices in Algebra: 00:11:00 •Working with indices Part 1: 00:10:00 •Working with indices Part 2: 00:08:00 •Fractional Indices: 00:12:00 •What are Polynomials?: 00:07:00 •Writing statements in Algebraic Form: 00:06:00 •Simplification using BODMAS: 00:08:00 •Distributive Property: 00:07:00 •Addition of Algebraic expressions: 00:13:00 •Subtraction of Algebraic expressions: 00:12:00 •Multiplication of Algebraic Expressions Part 1: 00:05:00 •Multiplication of Algebraic Expressions Part 2: 00:05:00 •Multiplication of Algebraic Expressions Part 3: 00:06:00 •Division of algebraic expressions Part 1: 00:11:00 •Division of algebraic expressions Part 2: 00:10:00 •Division of algebraic expressions Part 3: 00:07:00 •Topics of Essential Revision - 2: 00:00:00 •Factorization by method of common factor: 00:13:00 •Factorization by regrouping the terms: 00:10:00 •Factorization by difference of two squares: 00:11:00 •Factorization using identity (a + b) ² and (a - b) ²: 00:10:00 •Factorization using identity (a + b + c) ²: 00:05:00 •Factorization by middle term split Part 1: 00:12:00 •Factorization by middle term split Part 2: 00:09:00 •Simultaneous Linear Equations: 00:07:00 •Graphical Method: 00:06:00 •Graphical method Continued: 00:11:00 •Elimination by substitution Method: 00:09:00 •Equating the coefficients Method: 00:11:00 •Cross Multiplication: 00:10:00 •Equations Reducible to Linear Equations-1: 00:08:00 •Equations Reducible to Linear Equations-2: 00:14:00 •Introduction to Quadratic Equations: 00:05:00 •Solving Quadratic Equations by Factorization method: 00:09:00 •Writing in completed square form: 00:07:00 •Solving by completed square method: 00:08:00 •Sketching of Quadratic Graphs: 00:12:00 •Quadratic graphs using Transformations: 00:06:00 •Quadratic inequalities: 00:11:00 •Deriving Quadratic formula: 00:05:00 •Solving problems using Quadratic Formula: 00:06:00 •Nature of Roots Part - 1: 00:05:00 •Nature of roots Part - 2: 00:12:00 •Downloadable Resources: 00:00:00 •Distance formula: 00:18:00 •Mid point formula: 00:05:00 •Gradient of a line: 00:11:00 •Graphing using gradient and y intercept: 00:03:00 •Some standard lines: 00:05:00 •Slope intercept form y = m x +c: 00:06:00 •Point slope form and two point form: 00:11:00 •Intersection of line and parabola: 00:10:00 •Past Papers Problems Part 1: 00:09:00 •Past Papers Problems Part 2: 00:11:00 •Past Papers Problems Part 3: 00:09:00 •Past Papers Problems Part 4: 00:12:00 •Past Papers Problems Part 5: 00:12:00 •Downloadable Resources: 00:00:00 •Sequence and series ( video): 00:08:00 •Arithmetic Sequence: 00:10:00 •General term of an A.P.: 00:07:00 •Finding given term is which term: 00:05:00 •Writing sequence when two terms are known: 00:08:00 •Condition for three terms to be in A.P.: 00:05:00 •Sum to n terms of A.P.: 00:06:00 •Practice Problems 1 (A.P.): 00:09:00 •Practice problems 2 (A.P.): 00:07:00 •Practice problems 3 (A.P.): 00:07:00 •Practice problems 4 (A.P.): 00:11:00 •Geometric Progressions: 00:12:00 •Sum to n terms in G.P.: 00:14:00 •Sum to infinite Terms in G.P.: 00:13:00 •Practice Problems 1 (GP): 00:15:00 •Practice Problems 2 (GP): 00:12:00 •Practice Problems 3 (GP): 00:07:00 •Practice Problems based on AP and GP both: 00:15:00 •Past papers problems 1: 00:17:00 •Past papers problems 2: 00:10:00 •Past papers problems 3: 00:11:00 •Downloadable Resources: 00:00:00 •Geometric Progressions - Resources: 00:00:00 •What is Factorial?: 00:07:00 •n-choose -r problems: 00:07:00 •Properties of n - choose -r: 00:05:00 •Binomial Theorem for positive index: 00:20:00 •Expanding using Binomial Theorem: 00:11:00 •Finding the indicated term in the Binomial expansion: 00:11:00 •Finding the indicated term from end: 00:09:00 •Finding the coefficient for given exponent (index) of the variable: 00:09:00 •Finding the term independent of variable: 00:05:00 •Expanding in increasing and decreasing powers of x: 00:09:00 •Practice problems 1: 00:12:00 •Practice Problems 2: 00:09:00 •Practice problems 3: 00:10:00 •Past papers problems 1: 00:15:00 •Past Paper problems 2: 00:13:00 •Past Paper problems 3: 00:09:00 •Downloadable Resources: 00:00:00 •What is Function?: 00:08:00 •Vertical Line Test: 00:04:00 •Value of a Function Graphically: 00:08:00 •Domain Range of a function Algebraically: 00:14:00 •Domain Range of a function Graphically: 00:07:00 •Even & Odd Functions: 00:07:00 •One to one Function: 00:05:00 •Composite Functions: 00:09:00 •How to draw Rational Functions- 1: 00:05:00 •How to draw Rational Functions- 2: 00:10:00 •Inverse of a function Algebraically: 00:05:00 •Inverse of a function Graphically: 00:09:00 •Practice Problems 1: 00:16:00 •Practice Problems 2: 00:11:00 •Downloadable Resources: 00:00:00 •What is Derivative?: 00:08:00 •Derivation of formula for Derivative: 00:06:00 •Differentiation by definition or First Principle: 00:07:00 •Power Rule: 00:22:00 •Practice Problems on Power Rule 1: 00:07:00 •Practice Problems on Power Rule 2: 00:07:00 •Practice Problems on Power Rule 3: 00:05:00 •Practice Problems on Power Rule 4: 00:13:00 •Practice Problems on Power Rule 5: 00:08:00 •Downloadable Resources: 00:00:00 •Tangents and Normals- Basics: 00:13:00 •Practice- Tangents and Normals Part 1: 00:16:00 •Practice- Tangents and Normals Part 2: 00:13:00 •Practice- Tangents and Normals Part 3: 00:11:00 •Practice- Tangents and Normals Part 4: 00:14:00 •Downloadable Resources: 00:00:00 •Stationary Points - Basics: 00:13:00 •Practice- Increasing Decreasing & Maxima Minima part 1: 00:11:00 •Practice- Increasing Decreasing & Maxima Minima part 2: 00:12:00 •Practice- Increasing Decreasing & Maxima Minima part 3: 00:10:00 •Downloadable Resources: 00:00:00 •Concavity-Basics: 00:02:00 •Concavity & Second Derivative: 00:08:00 •Second Derivative Test: 00:09:00 •Practice Problems on second derivative: 00:04:00 •Practice Problem of Maxima Minima using second derivative test Part 1: 00:17:00 •Practice Problem of Maxima Minima using second derivative test Part 2: 00:10:00 •Practice Problem of Maxima Minima using second derivative test Part 3: 00:07:00 •Practice Problem of Maxima Minima using second derivative test Part 4: 00:07:00 •Applications of Maxima and Minima Part 1: 00:09:00 •Applications of Maxima and Minima Part 2: 00:07:00 •Applications of Maxima and Minima Part 3: 00:10:00 •Applications of Maxima and Minima Part 4: 00:09:00 •Applications of Maxima and Minima Part 5: 00:10:00 •Applications of Maxima and Minima Part 6: 00:08:00 •Past Paper Problems on applications of maxima and minima Part 1: 00:09:00 •Past Paper Problems on applications of maxima and minima Part 2: 00:09:00 •Past Paper Problems on applications of maxima and minima Part 3: 00:08:00 •Past Paper Problems on applications of maxima and minima Part 4: 00:07:00 •Chain Rule: 00:12:00 •Rate of change part 1: 00:05:00 •Rate of change part 2: 00:10:00 •Rate of change part 3: 00:07:00 •Past Paper Problems using chain rule -1: 00:06:00 •Past Paper Problems using chain rule -2: 00:07:00 •Past Paper Problems using chain rule - 3: 00:07:00 •Past Paper Problems using chain rule - 4: 00:04:00 •Downloadable Resources: 00:00:00 •What is Integration?: 00:12:00 •Practice Questions 1: 00:06:00 •Practice Questions 2: 00:09:00 •Practice Questions 3: 00:09:00 •Fundamental Theorem of Calculus: 00:09:00 •What is Definite Integration?: 00:10:00 •Finding Definite Integration: 00:09:00 •Practice Questions on Definite Integration 1: 00:10:00 •Practice Questions on Definite Integration 2: 00:10:00 •Practice Questions on Definite Integration 3: 00:15:00 •Area below x-axis: 00:12:00 •Practice Problems on Area below x-axis 1: 00:11:00 •Practice Problems on Area below x-axis 2: 00:13:00 •Practice Problems on Area below x-axis 3: 00:09:00 •Practice Problems on Area below x-axis 4: 00:07:00 •Area between two curves (Basics): 00:15:00 •Practice Problems on Area between two curves 1: 00:06:00 •Practice Problems on Area between two curves 2: 00:13:00 •Practice Problems on Area between two curves 3: 00:12:00 •Practice Problems on Area between two curves 4: 00:10:00 •Practice Problems on Area between two curves 5: 00:13:00 •The Reverse Chain Rule- Indefinite Integration: 00:06:00 •The Reverse Chain Rule- Definite Integration: 00:05:00 •Practice Problems on The Reverse Chain Rule: 00:09:00 •Improper Integrals: 00:06:00 •Volumes by Integration: 00:08:00 •Practice Problems on Volumes by Integration-1: 00:04:00 •Practice Problems on Volumes by Integration-2: 00:04:00

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Dive into the enthralling world of numbers and equations with 'High School Math (Pure Mathematics 1),' a course designed to unravel the mysteries of mathematics. Your journey begins with an Introduction that lays the foundation, not just in terms of concepts but igniting a passion for the beauty of math. As you progress, Functions become more than just equations; they turn into a language that describes the universe. Imagine the elegance of Quadratic Equations unfolding before your eyes, revealing patterns and solutions that were once hidden. Embark on an adventure through Co-ordinate Geometry, where every point and line tells a story of space and dimensions. Sequence and Series will no longer be just about numbers; they will be about the rhythm and flow of mathematical logic. The course takes a deeper dive with the Binomial Theorem, Differentiation, Tangents and Normals, each module building on the last, turning complexity into simplicity. Stationary Points & Curve Sketching, and the Second Derivative Test open new vistas in understanding the nature of graphs. As you master Simultaneous Linear Equations, you're not just solving problems; you're unlocking a new perspective on mathematical relationships. The Essential Revision at the end is your bridge to excellence, consolidating your knowledge and skills. Learning Outcomes Develop a foundational understanding of key mathematical concepts and functions. Master the intricacies of quadratic equations and co-ordinate geometry. Explore and apply the principles of sequences, series, and the binomial theorem. Gain proficiency in differentiation and its practical applications in tangents and normals. Understand and implement techniques in curve sketching, stationary points, and optimisation. Why choose this High School Math (Pure Mathematics 1) course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this High School Math (Pure Mathematics 1) course for? High school students seeking to excel in mathematics. Individuals preparing for college-level math courses. Math enthusiasts looking to deepen their understanding of pure mathematics. Students requiring a comprehensive revision of key mathematical concepts. Anyone aspiring to pursue a career involving advanced mathematics. Career path Mathematician: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Actuarial Analyst: £28,000 - £55,000 Research Scientist (Mathematics): £32,000 - £60,000 Engineering Consultant: £27,000 - £55,000 Academic Tutor (Mathematics): £24,000 - £40,000 Prerequisites This High School Math (Pure Mathematics 1) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This High School Math (Pure Mathematics 1) 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Introduction Introduction 00:03:00 Functions What is Function? 00:07:00 Vertical Line Test 00:04:00 Value of a Function Graphically 00:08:00 Domain Range of a function Algebraically 00:13:00 Domain Range of a function Graphically 00:06:00 Even & Odd Functions 00:07:00 One to one Function 00:05:00 Composite Functions 00:09:00 How to draw Rational Functions- 1 00:04:00 How to draw Rational Functions- 2 00:10:00 Inverse of a function Algebraically 00:05:00 Inverse of a function Graphically 00:09:00 Practice Problems 00:15:00 Practice Problems 00:11:00 Resources Downloads 00:40:00 Quadratic Equations Introduction to Quadratic Equations 00:04:00 Solving Quadratic Equations by Factorization method 00:10:00 Writing in completed square form 00:08:00 Solving by completed square method 00:08:00 Sketching of Quadratic Graphs 00:11:00 Quadratic graphs using Transformations 00:06:00 Quadratic inequalities 00:11:00 Deriving Quadratic formula 00:05:00 Solving problems using Quadratic Formula 00:06:00 Equations reducible to Quadratic 00:07:00 Nature of Roots of Quadratic Equations 00:04:00 Nature of roots continues 00:12:00 Quadratic Equations (Resources) 00:50:00 Co-ordinate Geometry Distance formula 00:15:00 Mid point formula 00:05:00 Gradient of a line 00:10:00 Graphing using gradient and y intercept 00:02:00 Some standard lines 00:04:00 Slope intercept form y = m x +c 00:05:00 Point slope form and two point form 00:10:00 Intersection of line and parabola 00:09:00 Practice Problems from past papers (part 3) 00:12:00 Sequence and series Sequence and series ( video) 00:08:00 Arithmetic Sequence 00:10:00 General term of an A.P. 00:07:00 Finding given term is which term? 00:05:00 Writing sequence when two terms are known 00:08:00 Condition for three terms to be in A.P. 00:05:00 Sum to n terms of A.P. 00:06:00 Practice Problems 1 (A.P.) 00:08:00 Practice problems 3 (A.P.) 00:07:00 Practice problems 4 (A.P.) 00:10:00 Geometric Progressions 00:11:00 Sum to n terms in G.P. 00:14:00 Sum to infinite Terms in G.P. 00:13:00 Practice Problems 1 (GP) 00:13:00 Practice Problems 2 (GP) 00:06:00 Practice Problems based on AP and GP both 00:15:00 Sequence and series Text 1 00:40:00 Sequence and series Text 2 00:55:00 Binomial Theorem What is Factorial? 00:06:00 n-choose -r problems 00:06:00 Properties of n - choose -r 00:05:00 Expanding using Binomial Theorem 00:11:00 Finding the indicated term in the Binomial expansion 00:10:00 Finding the indicated term from end 00:09:00 Finding the coefficient for given exponent (index) of the variable 00:08:00 Finding the term independent of variable 00:05:00 Expanding in increasing and decreasing powers of x 00:09:00 Practice problems 1 00:12:00 Practice Problems 2 00:09:00 Practice problems 3 00:10:00 Past papers problems 1 00:15:00 Past Paper problems 2 00:13:00 Past Paper problems 3 00:09:00 Resources in this section 00:50:00 Differentiation What is Derivative? 00:07:00 Derivation of formula for Derivative 00:06:00 Differentiation by definition or First Principle 00:06:00 Power Rule 00:20:00 Practice Problems on Power Rule 1 00:07:00 Practice Problems on Power Rule 2 00:07:00 Practice Problems on Power Rule 3 00:05:00 Practice Problems on Power Rule 4 00:11:00 Practice Problems on Power Rule 5 00:07:00 Tangents and Normals Tangents and Normals- Basics 00:12:00 Practice- Tangents and Normals Part 1 00:16:00 Practice- Tangents and Normals Part 2 00:13:00 Practice- Tangents and Normals Part 3 00:11:00 Practice- Tangents and Normals Part 4 00:14:00 Stationary Points & Curve Sketching Stationary Points - Basics 00:13:00 Practice- Increasing Decreasing & Maxima Minima part 1 00:11:00 Practice- Increasing Decreasing & Maxima Minima part 2 00:12:00 Practice- Increasing Decreasing & Maxima Minima part 3 00:10:00 Second Derivative Test (Maximum & Minimum Points) Concavity-Basics 00:02:00 Concavity & Second Derivative 00:08:00 Second Derivative Test 00:09:00 Practice Problems on second derivative 00:04:00 Practice Problem of Maxima Minima using second derivative test Part 1 00:17:00 Practice Problem of Maxima Minima using second derivative test Part 2 00:10:00 Practice Problem of Maxima Minima using second derivative test Part 3 00:07:00 Practice Problem of Maxima Minima using second derivative test Part 4 00:07:00 Applications of Maxima and Minima Part 1 00:09:00 Applications of Maxima and Minima Part 2 00:07:00 Applications of Maxima and Minima Part 3 00:10:00 Applications of Maxima and Minima Part 4 00:09:00 Applications of Maxima and Minima Part 5 00:10:00 Applications of Maxima and Minima Part 6 00:08:00 Past Paper Problems on applications of maxima and minima Part 1 00:09:00 Past Paper Problems on applications of maxima and minima Part 2 00:09:00 Past Paper Problems on applications of maxima and minima Part 3 00:08:00 Past Paper Problems on applications of maxima and minima Part 4 00:07:00 Chain Rule 00:12:00 Rate of change part 1 00:05:00 Rate of change part 2 00:10:00 Rate of change part 3 00:07:00 Past Paper Problems using chain rule -1 00:06:00 Past Paper Problems using chain rule - 2 00:07:00 Past Paper Problems using chain rule 3 00:07:00 Past Paper Problems using chain rule -4 00:04:00 Simultaneous Linear equations Graphical Method of solving pair of linear equations 00:10:00 Video lecture on Graphical method 00:05:00 Method of elimination by substitution 00:10:00 Video lecture on substitution method 00:06:00 Method of elimination by equating the coefficients 00:10:00 Video lecture on equating coefficients method 00:09:00 Practice Problems on Linear equation 00:20:00 Essential Revision How to take up this course? 00:10:00 Background of Algebra 00:10:00 Language of Alg ebra 00:10:00 Finding Values of algebraic expressions 00:14:00 Fractional Indices 00:10:00 Higher Indices 00:07:00 Rules of Brackets 00:04:00 Simplification by removing brackets (BODMAS) 00:11:00 Simplifications of Algebraic Fractions 00:07:00 Solving complex Linear Equations in one variable 00:10:00 Factorization by taking out common factor 00:10:00 Factorization by grouping the terms 00:09:00 Factorize using identity a ² - b ² 00:07:00 Factorization by middle term split 00:12:00

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Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

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