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Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content 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 Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 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.

Register on the Python Data Science 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 a digital certificate as a proof of your course completion. The Python Data Science 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 Python Data Science 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 After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. 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 Python Data Science, 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 to Python Data Science Module 01: Introduction to Python Data Science 00:03:00 Module 02: Environment Setup 00:10:00 Unit 02: Data Cleaning Packages Module 01: Numpy package for calculations 00:16:00 Module 02: Panda package for Data cleaning 00:19:00 Unit 03: Data Visualization packages Module 01: Matplotlib Data Visualization Part 1 00:16:00 Module 02: Matplotlib Data Visualization Part 2 00:11:00 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.

48-Hour Knowledge Knockdown! Prices Reduced Like Never Before! Whether you want to pursue higher studies in a top-rated university or wish to land a promising job, one skill is mandatory, and that is English language skills. Without a strong command of English, it is impossible to climb the career ladder. That's why, without wasting time, start working on your English with the Functional Skills English Level 2 course. This Certificate in Functional Skills English at QLS Level 2 course is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 60 CPD points) to make your skill development & career progression more accessible than ever! In this Functional Skills English course, you will be able to establish a solid foundation in grammar. The Functional Skills English course will provide you with lessons on the different areas and rules of grammar. You will be able to enrich your understanding of sentence structure. Moreover, the easy-to-follow modules will help you avoid common mistakes. You will be able to take your skills to the next level by the end of this Functional Skills English course. So why wait? Take a step toward a brighter future and start Functional Skills English - QLS Endorsed & CPD Accredited course with us! After this Functional Skills English course, you will be able to: Enrich your understanding of grammar Develop a clear idea of English sentence structure Build your expertise in punctuation and capitalisation Learn the techniques for identifying and avoiding common mistakes Know how to improve your spelling Why Prefer This Functional Skills English at QLS Level 2 Course? Opportunity to earn a certificate endorsed by the Quality Licence Scheme & another accredited by CPDQS which is completely free. Get a free student ID card! (£10 postal charge will be applicable for international delivery) Innovative and engaging content. Free assessments 24/7 tutor support. Take a step toward a brighter future! *** Course Curriculum *** Here is the curriculum breakdown of the Functional Skills English at QLS Level 2 course: Introduction to the Course Basics of Grammar The Basics of Sentence Structure of Sentence Questions Punctuation and Capitalisation Spelling Common Mistakes and Ways to Improve Assessment Process After completing an online module, you will be given immediate access to a specially designed MCQ test. The results will be immediately analysed, and the score will be shown for your review. The passing score for each test will be set at 60%. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you have completed all of the Certificate in Functional Skills English at QLS Level 2 exams. CPD 60 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Certificate in Functional Skills English at QLS Level 2 course is ideal for Anyone who wishes to elevate their English skills. Aspiring teachers, content writers, journalists, online trainers etc. Students planning to for higher studies can also take this course. Requirements No prior background or expertise is required. Career path The Functional Skills English Level 2 course will help you develop a solid foundation in the English language. After completing this Functional Skills English course, you will be able to explore different career options, such as Teacher (Annual Average Salary £35k) Teacher Assistant (Annual Average Salary £33k) Private Tutor (Annual Average Salary £48k) Content Writer (Annual Average Salary £30k) Certificates Certificate in Functional Skills English at QLS Level 2 Hard copy certificate - Included Show off Your New Skills with a Certificate of Completion After successfully completing the Certificate in Functional Skills English at QLS Level 2, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme andalso you can order CPDQSAccredited Certificate that is recognised all over the UK and also internationally. The certificates will be home-delivered, completely free of cost. CPDQS Accredited Certificate Digital certificate - Included

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

This course is a perfect supplement for ML enthusiasts. If you are only just beginning your adventures in machine learning and want to know the basics of statistics and regression used for machine learning, then go for it. Discover how you can level up and gain confidence to implement statistical methods and regression in machine learning with Python.

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

***With this Algebra Teaching Level 3 course, get a Personal Hygiene Course completely FREE and prevent yourself from being infected by Coronavirus and other contagious diseases.*** Algebra Teaching Level 3 is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Algebra Teaching Level 3 and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 11 hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Numeracy and IT Desire for entrepreneurship Over the age of 16. Assessment The assessment is straightforward, you need to complete the assignment questions that will be provided to you at the end of the course, you can complete the assignment anytime you want. After you complete and submit your assignment, our tutors will assess your assignment and give you feedback if needed.  After your assignment has been assessed and you have passed, you will be qualified and will be able to apply for a course completion certificate. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Introduction Lecture 1 Introduction 00:03:00 Fundamental concepts on Algebraic Expressions 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 Operations on Algebraic Expressions 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 Indices ( Exponents) 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 Multiplication and Division of Algebraic expressions 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 Brackets in Algebra Lecture 25 Rules of brackets 00:04:00 Lecture 26 Simplification by removing brackets 00:11:00 Linear equations in one variable 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 Algebraic Identities Lecture 32 What are Identities? 00:05:00 Lecture 33 Identity ( a + b ) ² 00:13:00 Lecture 34 Identity ( a - b ) ² new 00:07:00 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 Formula : Change of subject of formula Lecture 41 -Changing the subject of formula 00:08:00 Linear Inequalities Lecture 42 - Linear Inequalities 00:12:00 Resolve into factors 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 Algebraic Fractions Lecture 49 -Simplification of algebraic fractions 00:06:00 Coordinate axis - points and Line graph 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 System of simultaneous linear equations in two variables 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 Polynomials 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 Quadratic Polynomials 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 Quadratic Equations 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

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