14 Linear Algebra courses delivered Online

Getting Started OTHM Level 3 Foundation Diploma for Higher Education Studies aims for academic and professional development. It helps the learners acquire knowledge regarding the various courses the university provides. This qualification helps the learner to gain deep knowledge about current opportunities and scope of higher education. This qualification helps the learner to opt for the next level of higher education. The qualifications awarded by OTHM at RQF Level 3 represent practical knowledge, skills, capabilities and competencies that are assessed in academic terms as equivalent to GCE AS/A Levels. Key Benefits   Learners can acquire knowledge regarding the various courses offered by the university. This qualification helps the learner to opt for the next level of higher education. It provides a broad introduction to the subject's learner's choice and helps gain valuable academics. The core modules will allow the learners to understand the wider context of their chosen focus area. Learners who complete a foundation course are generally better placed to enter tertiary study and often do so with credits. Key Highlights Are you desirous to know about the scope and current opportunities to improve your skills and knowledge in higher Studies? Then, the OTHM Level 3 Foundation Diploma for Higher Education Studies is the ideal starting point for your career journey. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our OTHM-approved tutors, who would be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The OTHM Level 3 Foundation Diploma for Higher Education Studies can open many career pathways including, but not limited to: Administrative Assistant, with an estimated average salary of £20,369 per annum Junior manager with an estimated average salary of £30,007 per annum Human resource coordinator, with an estimated average salary of £25,000per annum Customer service executive with an estimated average salary of £23,684 per annum Management trainees with an estimated average salary of £22,046 per annum   About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. What is included?   Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform. This facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only). Assessment Time-constrained scenario-based assignments No examinations Entry Requirements Learners must be 18 years or more International students whose first language is not in English, they will need to have score of 5.5 or above in IELTS Examination or equivalent. Progression   Learners completing the OTHM Level 3 Foundation Diploma for Higher Education Studies allow progress to : Wide range of undergraduate programmes, including OTHM Level 4 diplomas. Why gain a OTHM Qualification? Quality, Standards and Recognitions- OTHM qualifications are approved and regulated by Ofqual (Office of the Qualifications and Examinations Regulation); hence, the learners can be very confident about the quality of the qualifications as well. Career Development to increase credibility with employers- All OTHM qualifications are developed to equip learners with the skills and knowledge every employer seeks. The learners pursuing an OTHM qualification will obtain an opportunity to enhance their knowledge and grow key competencies to tackle situations and work projects more effectively, giving learners the potential to get promotions within the workplace. Alternatively, it allows them to progress onto an MBA top-up/Bachelor's degree / Master's degree programme around the World. Flexible study options- All OTHM qualifications have a credit value, which tells you how many credits are awarded when a unit is completed. The credit value will indicate how long it will normally take you to prepare for a unit or qualification. Three different types of qualification are: The award is achieved with 1 - 12 credits The certificate is achieved with 13 - 36 credits The diploma is achieved with at least 37 credits. The OTHM Level 3 Foundation Diploma for Higher Education Studies consists of 6 mandatory units for a combined total of 120 credits, 1200 hours Total Qualification Time (TQT) and 600 Guided Learning Hours (GLH) for the completed qualification. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- Academic English and Study Skills Reference No : R/617/3714 Credit : 20 || TQT : 200 The aim of this unit is to help students develop competence in and awareness of academic English and study skills in in preparation for entry to an undergraduate degree programmes. UNIT2- Foundation Mathematics Reference No : Y/617/3715 Credit : 20 || TQT : 200 This unit aims to consolidate learners' knowledge of mathematics and to introduce more topics in the areas of statistical methods and linear algebra. As the business world embraces the use of bigger data in all areas of operation, the mathematical techniques taught in this module will be necessary to aid in the understanding of data, valuable in enhancing future employment prospects. UNIT3- Foundation Computing Reference No : D/617/3716 Credit : 20 || TQT : 200 This unit aims to provide an introduction to computing and the concepts of hardware and its uses. Learners will gain an understanding of data systems and data presentation, key aspects of computer networks and the importance of ethical and legal issues about computing UNIT4- Society and Culture Reference No : H/617/3717 Credit : 20 || TQT : 200 The aim of this unit is to provide students to a variety of contemporary issues related to society and culture, enabling learners to understand social and cultural literacy by developing their knowledge and understanding of societies and cultures UNIT5- Introduction to Business Reference No : K/617/3718 Credit : 20 || TQT : 200 This unit aims to provide learners with knowledge and understanding of how different forms of business ownership operate. It will cover how businesses are run in terms of their form of ownership, the impact of external factors on business success, understanding the different objectives businesses may have, and the key functional areas within a business that enable it to operate effectively. UNIT6- Foundation Accounting and Economics Reference No : M/617/3719 Credit : 20 || TQT : 200 The aim of this unit is to provide learners an introduction to the fundamentals of accounting and economics. Learners will gain an understanding of financial reports through their preparation, based on the double-entry bookkeeping system which is essential for the management of any organization. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

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

Description: Algebra is an area of mathematics that uses symbols to represent numbers in formulas and equations. Understanding these symbols and how they work together and provide structure to equations allows mathematicians to more efficiently write formulas and solve math problems.  This Algebra for Beginners is an introduction to the basic principles and skills of algebra. Topics include Variables, Grouping Symbols, Equations, Translating Words Into Symbols, and Translating Sentences Into Equations. With this course you will learn to manipulate and solve basic algebraic expressions, solve rational expressions, changing the subject of formulae and using formulae. You will learn to work with integers, decimals and fractions, how to evaluate powers and roots and how to solve single and multi-variable equations and inequalities. Learn how to apply algebra to a wide range of real-world problems and study critical algebraic concepts like functions, domains and ranges. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Algebra for Beginners is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Algebra for Beginners is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction Lecture 1 Intro video Algebra Introduction final 00:02:00 Fundamental concepts on Algebraic Expressions Lecture 2 Terminology used in Algebra 00:05:00 Lecture 3 Language of Algebra 00:06:00 Lecture 4 Practice Questions 00:06:00 Lecture 5 Finding numerical value of an algebraic expression 00:14:00 Operations on Algebraic Expressions Lecture 6 Revision of Directed number ( integers 00:06:00 Lecture 7 Addition and subtraction of monomial expressions 00:06:00 Lecture 8 Addition of algebraic expressions with many terms 00:10:00 Lecture 9 Subtraction of algebraic expressions 00:10:00 Indices ( Exponents) Lecture 10 The rules of Indices in algebra 00:11:00 Lecture 11 Fractional indices 00:10:00 Lecture 12 Understanding indices (practice questions) 00:07:00 Lecture 13 Problems from IGCSE Last year papers 00:05:00 Multiplication and Division of Algebraic expressions Lecture 14 Multiplication of monomial algebraic expressions 00:05:00 Lecture 15 Multiplication of monomial with binomials and trinomials 00:11:00 Lecture 16 Division of algebraic expression by a monomial 00:07:00 Lecture 17 Division of algebraic expression by another polynomial 00:09:00 Lecture 18 Division of a polynomial by another polynomial with remainder 00:11:00 Brackets in Algebra Lecture 19 Rules of brackets 00:04:00 Lecture 20 Simplification by removing brackets 00:11:00 Linear equations in one variable Lecture 21 Simplification of algebraic fractions 00:07:00 Lecture 22 Rules to solve linear equations in one variable 00:03:00 Lecture 23 Solving linear equations in one variable 00:07:00 Lecture 24 Solving complex linear equations in one variable 00:10:00 Lecture 25 Word problems on linear equations in one variable 00:13:00 Algebraic Identities Lecture 26 Standard Identities (a + b )² and (a - b )² identities 00:11:00 Lecture 27 Standard Identity ( a - b ) ( a + b) = a ² - b ² 00:08:00 Lecture 28 Standard Identities ( a + b + c ) ² = a ² + b ² + c ² + 2 a b + 2 a c +2 b c 00:07:00 Lecture 29 Standard Identities ( a + b ) ³ and ( a - b ) ³ 00:09:00 Lecture 30 Standard Identities a ³ + b ³ and a ³ - b ³ 00:06:00 Lecture 31 Standard Identities a ³ + b ³ + c ³ - 3 a b c 00:10:00 Formula : Change of subject of formula Lecture 32 -Changing the subject of formula 00:08:00 Linear Inequalities Lecture 33 Linear Inequalities 00:12:00 Resolve into factors Lecture 34 Factorization by taking out common factor 00:10:00 Lecture 35 Factorization by grouping the terms 00:09:00 Lecture 36 Factorize using identity a ² - b ² 00:07:00 Lecture 37 Factorize using identity (a + b )² and (a - b )² 00:08:00 Lecture 38 Factorize using identity ( a + b + c ) ² 00:05:00 Lecture 39 Factorization by middle term split 00:12:00 Algebraic Fractions Lecture 40 Simplification of algebraic fractions 00:06:00 Coordinate axis - points and Line graph Lecture 41 All that you need to know about co ordinate axis 00:04:00 Lecture 42 Some important facts needed to draw line graph 00:03:00 Lecture 43 How to draw a line graph on coordinate plane 00:03:00 Lecture 44 Drawing line graphs 00:06:00 System of simultaneous linear equations in two variables Lecture 45 Simultaneous Linear Equations in two variables- intro 00:03:00 Lecture 46 Graphical method of solving linear equations 00:06:00 Lecture 47 Graphical method - more sums 00:10:00 Lecture 48 Method of Elimination by substitution 00:09:00 Lecture 49 Method of Elimination by Equating coefficients 00:11:00 Lecture 50 Method of Elimination by cross multiplication 00:07:00 Lecture 51 Equations reducible to simultaneous linear equations 00:12:00 Lecture 52 Word Problems on Linear equations 00:18:00 Polynomials Lecture 53 Polynomials and Zeros of polynomials 00:10:00 Lecture 54 Remainder Theorem 00:04:00 Lecture 55 Factor Theorem 00:08:00 Lecture 56 Practice problems on Remainder and Factor Theorem 00:09:00 Lecture 57 Factorization using factor Theorem 00:10:00 Quadratic Polynomials Lecture 58 Zeros of polynomials α, β & γ 00:10:00 Lecture 59 Relation between zeros and coefficients of a polynomials 00:13:00 Lecture 60 Writing polynomials if zeros are given 00:06:00 Lecture 61 Practice problems on zeros of polynomials 00:10:00 Lecture 62 Problems solving with α and β (part 1) 00:11:00 Lecture 63 Problems solving with α and β (part 2) 00:10:00 Quadratic Equations Lecture 64 what are Quadratic equations 00:03:00 Lecture 65 Solutions by factorization method 00:12:00 Lecture 66 Solutions by completing square formula 00:06:00 Lecture 67 Deriving Quadratic formula 00:05:00 Lecture 68 Practice problems by Quadratic formula 00:07:00 Lecture 69 Solving complex quadratic equations by Quadratic Formula 00:11:00 Lecture 70 Solutions of reducible to Quadratic Formula 00:09:00 Lecture 71 Skilled problems on Quadratic Equations 00:07:00 Lecture 72 Exponential problems reducible to Quadratic Equations 00:06:00 Lecture 73 Nature of Roots of Quadratic Equations 00:09:00 Lecture 74 Word problems on quadratic Equations Part 1 00:13:00 Lecture 75 Word problems on quadratic Equations Part 2 00:11:00 lecture 76 word problems on Quadratic 00:12:00 Mock Exam Mock Exam - Algebra for Beginners 00:20:00 Final Exam Final Exam - Algebra for Beginners 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00