306 Computer Science (CS) courses delivered Online

Getting Started Pursuing a Diploma in E-Commerce is a highly valuable choice in the current landscape, given its prominent role in the IT industry. The increasing impact of websites on consumer perception and engagement has prompted leading organizations to actively seek out top-tier Merchandisers. Grasp and apply IT principles in diverse business settings. Apply IT principles within a specialized context. Enhance learners' employability by connecting management theories with real-world IT applications. Analyse problem-solving methods tailored to business and industry needs. Gather, review, and analyse information from a broad array of sources. Proficiently utilize verbal and communication skills. Demonstrate both independent and collaborative work abilities. Take charge of personal development and growth. Key Benefits Key Benefits: Pursuing a Diploma in E-Commerce is a highly valuable choice in the current landscape, given its prominent role in the IT industry. The increasing impact of websites on consumer perception and engagement has prompted leading organizations to actively seek out top-tier Merchandisers. Grasp and apply IT principles in diverse business settings. Apply IT principles within a specialized context. Enhance learners' employability by connecting management theories with real-world IT applications. Analyse problem-solving methods tailored to business and industry needs. Gather, review, and analyse information from a broad array of sources. Proficiently utilize verbal and communication skills. Demonstrate both independent and collaborative work abilities. Take charge of personal development and growth. Key Highlights Are you a practicing IT Professional seeking greater knowledge and understanding of the industry, and to support your development into senior positions? Then, the Qualifi Level 4 Diploma in Information Technology - E-Commerce is the ideal starting point for your career journey. • The course will help you forge a career and prepare individuals to become professional staff and managers of the future in the health and social care sector. • Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exams. • With the School of Business and Technology London, you can complete the qualification at your own pace by choosing online or blended learning from the comfort of your home. • Learning and pathway materials and study guides developed by our Qualifi-approved 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 you with comprehensive tutor support through our dedicated support desk. • If you choose the blended learning course, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completion of the Level 4 Diploma in Information Technology - E-Commerce, graduates may pursue various career paths in education and training, such as: • E-commerce Manager; with an estimated average salary of £44,925 per annum • Digital Marketing Specialist; with an estimated average salary of £33,000 per annum • E-commerce Developer; with an estimated average salary of between £50,000 per annum • Online Merchandiser; with an estimated average salary of £31,984 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 Assignment based Assessment No exam Entry Requirements The qualification has been intentionally designed to ensure accessibility without unnecessary obstacles hindering entry and advancement. To enrol in the qualification, individuals should meet the following criteria: • Should have a certain level of proficiency and hold a Qualification at Level 3, such as an 'A' LEVEL or any vocational certificate. • They should be actively pursuing additional professional development to acquire job-related skills and practical knowledge. • International students whose first language is not English will need to have a score of 6 or above in IELTS (International English Language Testing System). Progression Learners who successfully complete any of the corresponding QUALIFI Level 4 Diplomas in IT - E Commerce have various advancement options, including:   • Transitioning to the QUALIFI Level 5 Diplomas in IT-E Commerce. • Moving on to the second year of undergraduate programs in fields like Computer Science, Information Technology, or related disciplines. • Entering the workforce directly in a relevant professional capacity. 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- Information Technology and IT Ethics. Reference No : L/617/6692 Credit : 20 || TQT : 200 The objective of this unit is to enhance learners' understanding and utilization of information technology, encompassing the utilization of standard office applications for the creation of documents and presentations. UNIT2- Mathematics and Statistics for IT Reference No : R/617/6693 Credit : 20 || TQT : 200 The primary goal of this unit is to offer learners the chance to acquire proficiency in mathematics and statistics, equipping them with the mathematical capabilities necessary to analyze and resolve problems, thereby preparing them for roles within the IT field. UNIT3- PC Maintenance and Operating Systems. Reference No : Y/617/6694 Credit : 20 || TQT : 200 The objective of this unit is to impart knowledge regarding personal computer hardware. Successfully completing this unit will empower learners to perform tasks such as installing a computer system unit and operating system, as well as conducting troubleshooting procedures. UNIT4- Computer Graphics Editing and Database Concepts Reference No : D/617/6695 Credit : 20 || TQT : 200 The purpose of this unit is to elucidate the concepts of photo editing. This knowledge will empower learners to seamlessly integrate photos into documents, such as user manuals and the IT infrastructure documentation of an 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 Pursuing a Diploma in Web Designing is a highly valuable choice in the current landscape, given its prominent role in the IT industry. The increasing impact of websites on consumer perception and engagement has prompted leading organizations to actively seek out top-tier web designers. Web design has gained immense popularity due to its direct impact on how individuals perceive a business, influencing their decision to explore the company further. The web design industry has thrived, with a remarkable growth rate of 27%, even when other sectors have experienced stagnation. Achieving an organization's online success objectives as a web designer can be personally fulfilling, offering a sense of independence and pride. The field of web design offers abundant opportunities to unleash one's creative talents, and it is financially rewarding. Moreover, web designers enjoy the flexibility of collaborating with diverse industries and clients, regardless of geographical constraints. Key Benefits • Comprehend the ethical considerations within the realm of information technology. • Gain a fundamental understanding of the statistical principles underpinning information technology. • Develop a comprehensive understanding of both Windows and Linux operating systems. • Create a database system. • Design an effective website. Key Highlights Are you a practicing IT professional seeking greater knowledge and understanding of the industry, as well as support for your career development into senior positions? Then, the Qualifi Level 4 Diploma in Information Technology- Web Design is the ideal starting point for your career journey. • The course will pave the way for a career and help individuals prepare for professional roles and future managers in the health and social care sector. • Remember! The assessment for the qualification is based on assignments only, so you do not need to worry about taking any exams. • With the School of Business and Technology London, you can complete the qualification at your own pace, choosing between online or blended learning from the comfort of your home. • Learning materials, pathway materials, and study guides, all developed by our Qualifi-approved 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 you with comprehensive tutor support through our dedicated support desk. • If you choose the blended learning option, you will also have the opportunity to enjoy live sessions with an assigned tutor, which you can schedule at your convenience. Career Pathways Upon completion of the Level 4 Diploma in Information Technology- Web Design, graduates may pursue various career paths in education and training, such as: • Web Developer, with an estimated average salary of £45,641 per annum • Front-End Developer, with an estimated average salary of £51,006 per annum • Back-End Developer, with an estimated average salary of between £79,886 per annum • UI/UX Designer, with an estimated average salary of £41,101 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 Assignment based Assessment No exam   Entry Requirements The qualification has been intentionally designed to ensure accessibility without unnecessary obstacles hindering entry and advancement. To enrol in the qualification, applicants should meet the following criteria: • Should have a certain level of proficiency and hold a Qualification at Level 3, such as 'A' LEVEL or any vocational certificate. • They are actively pursuing additional professional development to acquire job-related skills and practical knowledge. • International students whose first language is not English will need to have a score of 6 or above in IELTS (International English Language Testing System).   Progression Learners who successfully complete any of the corresponding QUALIFI Level 4 Diplomas in IT - Web Design have various advancement options, including: • Transitioning to the QUALIFI Level 5 Diplomas in IT - Web Design. • Moving on to the second year of undergraduate programs in fields like Computer Science, Information Technology, or related disciplines. • Entering the workforce directly in a relevant professional capacity. 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- Information Technology and IT Ethics Reference No : L/617/6692 Credit : 20 || TQT : 200 The objective of this unit is to enhance learners' understanding and utilization of information technology, encompassing the utilization of standard office applications for the creation of documents and presentations. UNIT2- Mathematics and Statistics for IT Reference No : R/617/6693 Credit : 20 || TQT : 200 The primary goal of this unit is to offer learners the chance to acquire proficiency in mathematics and statistics, equipping them with the mathematical capabilities necessary to analyze and resolve problems, thereby preparing them for roles within the IT field. UNIT3- PC Maintenance and Operating Systems. Reference No : Y/617/6694 Credit : 20 || TQT : 200 The objective of this unit is to impart knowledge regarding personal computer hardware. Successfully completing this unit will empower learners to perform tasks such as installing a computer system unit and operating system, as well as conducting troubleshooting procedures. UNIT4- Computer Graphics Editing and Database Concepts Reference No : D/617/6695 Credit : 20 || TQT : 200 The purpose of this unit is to elucidate the concepts of photo editing. This knowledge will empower learners to seamlessly integrate photos into documents, such as user manuals and the IT infrastructure documentation of an 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.

About the course “Quantum Computing for Finance” is an emerging multidisciplinary field of quantum physics, finance, mathematics, and computer science, in which quantum computations are applied to solve complex problems. “Quantum Algorithms for Computational Finance” is an advanced course in the emerging field of quantum computing for finance. This technical course will develop an understanding in quantum algorithms for its implementation on quantum computers. Through this course, you will learn the basics of various quantum algorithms including: Grover’s and Rudolf’s algorithm, Quantum amplitude Estimation (QAE) algorithm envisioned as a quadratic speed-up over Classical Monte-Carlo simulations, Combinatorial optimization algorithms namely Quantum Approximate Optimization Algorithm (QAOA), and Variational Quantum Eigensolver (VQE), and Quantum-inspired optimization algorithms – Simulated Coherent Ising Machine (Sim-CIM), and Simulated Bifurcation Algorithm (SBA). This course is meant for all those learners who want to explore the long-term employability of quantum computing in finance, assuming that you are familiar with the concepts of quantitative and computational finance. In addition, the course contains several Python based programming exercises for learners to practice the algorithms explained throughout the course. This course is the second part of the specialised educational series: “Quantum Computing for Finance”. What Skills you will learn Ability to perform quantum arithmetic operations and simulations. An understanding of the Quantum Amplitude Estimation algorithm and its variants. The computational and modelling techniques for option pricing and portfolio optimization on a quantum computer. The skills for a career in quantum finance including Quantum Algorithmic Research, Quantitative Asset Management and Trading, financial engineering, and risk management, using quantum computing technology. Course Prerequisites All potential learners must have prior knowledge or familiarity with basic quantum algorithms/basic quantum programming. Before enrolling this course, we recommend all learners to complete the first course “Introduction to Quantitative and Computational Finance” of the series “Quantum Computing for Finance”, if they have no previous experience with the concepts of quantitative and computational finance. Duration The estimated duration to complete this course is approximately 6 weeks (~4hrs/week). Course assessment To complete the course and earn the certification, you must pass all the quizzes at the end of each lesson by scoring 80% or more on each of them. Instructors QuantFiQuantFi is a French start-up research firm formed in 2019 with the objective of using the science of quantum computing to provide solutions to the financial services industry. With its staff of PhD's and PhD students, QuantFi engages in fundamental and applied research in in the field of quantum finance, collaborating with industrial partners and universities in seeking breakthroughs in such areas as portfolio optimisation, asset pricing, and trend detection.

Unity 3d face to face training customised and bespoke.

Flash Sale(was 2499) Job Ready Program, Personalised Job Searching Support, CV & Portfolio Building, Expert Consultation

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

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.

The Computer Science and Programming Diploma course covers the fundamental theories of Algorithm Analysis. If you want to explore the concepts and methods that make a good programmer, then the course is designed for you. Programming is all about how to solve a problem. Programming theory is not confined to a single language; rather it applies to all programming languages. By understanding the right programming theory, you will be able to analyse a problem and also able to find out the probable solution. The course teaches you these Programming theories covering Algorithm analysis, Binary Number System, Arrays and their Advantages, the process of analysing a problem, Nodes and their Importance, various sorting algorithms and their comparisons, and more. Upon completion, you will be able to understand the core theories of computer science. What Will I Learn? Understand the Fundamental Theories of Algorithm Analysis Be able to Compare Various Algorithms Understand When to use Different Data Structures and Algorithms Understand the Fundamentals of Computer Science theory Requirements A Willingness to Learn New Topics! No Prior Experience or Knowledge is Needed! Module: 01 Kurt Anderson - 1 Introduction FREE 00:01:00 Kurt Anderson - 2 Binary System FREE 00:11:00 Kurt Anderson - 3 Complexity Introduction 00:02:00 Kurt Anderson - 4 Math Refresher Logarithmic Functions 00:11:00 Kurt Anderson - 5 Math Refresher Factorial Functions.TS 007 00:03:00 Kurt Anderson - 6 Math Refresher Algebraic Expressions.TS 00:03:00 Kurt Anderson - 7 n-notation 00:19:00 Kurt Anderson - 8 Big O 00:13:00 Kurt Anderson - 9 Big O Real World Example 00:10:00 Module: 02 Kurt Anderson - 10 How is Data Stored 00:09:00 Kurt Anderson - 11 Fixed Arrays 00:20:00 Kurt Anderson - 12 Circular Arrays 00:08:00 Kurt Anderson - 13 Dynamic Arrays 00:16:00 Kurt Anderson - 14 Array Review 00:08:00 Kurt Anderson - 15 Array Real World Examples 00:06:00 Kurt Anderson - 16 Linked List 00:12:00 Kurt Anderson - 16 Nodes 00:04:00 Kurt Anderson - 17 Linked List Run Times 00:15:00 Kurt Anderson - 18 Doubly Linked Lists 00:08:00 Kurt Anderson - 19 Tail Pointer 00:05:00 Module: 03 Kurt Anderson - 20 Linked List Real World Examples 00:03:00 Kurt Anderson - 20 Stack Example 00:11:00 Kurt Anderson - 21 Linked List Review 00:04:00 Kurt Anderson - 22 Stacks 00:10:00 Kurt Anderson - 23 Queues 00:09:00 Kurt Anderson - 24 Queue Examples 00:10:00 Kurt Anderson - 25 Queue and Stack Run Times 00:06:00 Kurt Anderson - 26 Stack and Queues Real World Examples 00:07:00 Kurt Anderson - 27 Sorting Algorithm Introdcution 00:02:00 Kurt Anderson - 28 Bubble Sort 00:10:00 Kurt Anderson - 29 Selection Sort 00:10:00 Module: 04 Kurt Anderson - 30 Insertion Sort 00:09:00 Kurt Anderson - 31 Quick Sort 00:15:00 Kurt Anderson - 32 Quick Sort Run Times 00:10:00 Kurt Anderson - 33 Merge Sort 00:12:00 Kurt Anderson - 34 Merge Sort Run Times 00:08:00 Kurt Anderson - 35 Stable vs Nonstable 00:07:00 Kurt Anderson - 36 Sorting Algorithm Real World Examples 00:04:00 Kurt Anderson - 37 Basics of Trees 00:08:00 Kurt Anderson - 38 Binary Search Tree 00:09:00 Kurt Anderson - 39 BST Run Times 00:08:00 Module: 05 Kurt Anderson - 40 Tree Traversals 00:13:00 Kurt Anderson - 41 Tree Real World Examples 00:05:00 Kurt Anderson - 42 Heap Introduction 00:04:00 Kurt Anderson - 43 Heap Step by Step 00:12:00 Kurt Anderson - 44 Heap Real World Examples 00:07:00 Kurt Anderson - 45 Thank You 00:01:00

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