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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

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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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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