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In this practical, hands-on course, you'll learn how to use R for effective data analysis and visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Description: In developing a website, it is important to choose a subject or theme that will suit your style and preference. In this course, you will learn to decide on the function and niche of your site. You will learn the importance of visualization and how to make your site content-rich. You will also be able to know how to do back links. Then you will see the significance of SEO, multimedia, and social sites to improve the traffic of your website. Who is the course for? Employees of the business industry and other businessmen who want to learn how to become profitable through website designing. People who have an interest in Website Design and Marketing and how to effectively communicate with their potential clients through the web. 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 you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: The Web Development Basics course will be very beneficial and helpful, especially to the following careers: Businessman Marketing and Promotions Specialists Marketing Managers Product Creators Programmers Sales Managers Sales and Promotions Specialists Top Executives Website Developer. Updated Version - Web Development Basics Section 01: Getting Started Introduction 00:03:00 How to Get Course requirements 00:02:00 Getting Started on Windows, Linux or Mac 00:02:00 How to ask a Great Questions 00:01:00 FAQ's 00:01:00 Section 02: HTML Introduction HTML 00:05:00 Choosing Code Editor 00:06:00 Installing Code Editor (Sublime Text) 00:04:00 Overview of a Webpage 00:05:00 Structure of a Full HTML Webpage 00:07:00 First Hello World! Webpage 00:09:00 Section 03: HTML Basic Heading tags 00:09:00 Paragraph 00:08:00 Formatting Text 00:12:00 List Items Unordered 00:05:00 List Items Ordered 00:04:00 Classes 00:09:00 IDs 00:06:00 Comments 00:04:00 Section 04: HTML Intermediate Images 00:12:00 Forms 00:05:00 Marquee 00:06:00 Text area 00:06:00 Tables 00:06:00 Links 00:07:00 Navbar - Menu 00:04:00 HTML Entities 00:05:00 Div tag 00:06:00 Google Maps 00:07:00 Section 05: HTML Advanced HTML Audio 00:07:00 HTML Video 00:05:00 Canvas 00:06:00 Iframes 00:05:00 Input Types 00:04:00 Input Attributes 00:06:00 Registration Form 00:04:00 Contact Us Form 00:10:00 Coding Exercise 00:01:00 Solution for Coding Exercise 00:02:00 Section 06: JavaScript Introduction What is JavaScript 00:09:00 Hello World Program 00:14:00 Getting Output 00:11:00 Internal JavaScript 00:13:00 External JavaScript 00:09:00 Inline JavaScript 00:04:00 Async and defer 00:06:00 Section 07: JavaScript Basics Variables 00:13:00 Data Types 00:11:00 Numbers 00:06:00 Strings 00:06:00 String Formatting 00:05:00 Section 08: JavaScript Operators Arithmetic operators 00:07:00 Assignment operators 00:03:00 Comparison operators 00:06:00 Logical operators 00:08:00 Section 09: JavaScript Conditional Statements If-else statement 00:05:00 If-else-if statement 00:04:00 Section 10: JavaScript Control Flow Statements While loop 00:09:00 Do-while loop 00:03:00 For loop 00:08:00 Coding Exercise 00:02:00 Solution for Coding Exercise 00:02:00 Section 11: JavaScript Functions Creating a Function 00:07:00 Function Call() 00:07:00 Function with parameters 00:05:00 Section 12: JavaScript Error Handling Try-catch 00:05:00 Try-catch-finally 00:17:00 Section 13: JavaScript Client-Side Validations On Submit Validation 00:09:00 Input Numeric Validation 00:12:00 Section 14: Python Introduction Introduction to Python 00:02:00 Python vs Other Languages 00:04:00 Why It's Popular 00:04:00 Command Line Basics 00:07:00 Python Installation (Step By Step) 00:06:00 PyCharm IDE Installation 00:08:00 Getting Start PyCharm IDE 00:05:00 First Python Hello World Program 00:07:00 Section 15: Python Basic Variables 00:16:00 Data Types 00:13:00 Type Casting 00:07:00 User Inputs 00:08:00 Comments 00:04:00 Section 16: Python Strings Strings 00:05:00 String Indexing 00:05:00 String Slicing 00:04:00 String Built-in Functions 00:09:00 Formatting String (Dynamic Data) 00:05:00 Section 17: Python Operators Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Comparison Operators 00:05:00 Logical Operators 00:02:00 AND Operator 00:04:00 OR Operator 00:02:00 NOT Operator 00:03:00 Booleans 00:02:00 Section 18: Python Data Structures Arrays in Earler 00:02:00 Lists 00:06:00 Add List Items 00:07:00 Remove List Items 00:01:00 Sort Lists 00:03:00 Join Lists 00:08:00 Tuples 00:08:00 Update tuples 00:07:00 Join tuples 00:02:00 Dictionaries 00:06:00 Add Dictionary Items 00:04:00 Remove Dictionary Items 00:03:00 Nested Disctionaries 00:04:00 Sets 00:04:00 Add Set Items 00:03:00 Remove Set Items 00:01:00 Join Set Items 00:04:00 Section 19: Python Conditional Statements If Statement 00:03:00 If-else Statement 00:04:00 If-elif-else Statement 00:04:00 If Statement Coding Excercise 00:05:00 Section 20: Python Control Flow Statements Flow Charts 00:06:00 While Loops Statement 00:10:00 For Loops Statement 00:06:00 The range() Function 00:04:00 Nested Loops 00:04:00 2D List using Nested Loop 00:04:00 Section 21: Python Core Games Guessing Game 00:07:00 Car Game 00:10:00 Section 22: Python Functions Creating a Function 00:03:00 Calling a Function 00:06:00 Function with Arguments 00:05:00 Section 23: Python args, KW args for Data Science args, Arbitary Arguments 00:04:00 kwargs, Arbitary Keyword Arguments 00:06:00 Section 24: Python Project Project Overview 00:04:00 ATM RealTime Project 00:13:00 Old Version - Web Development Basics Web Development Basics What Are Niche Website? 01:00:00 The Role Of Visualization In Education 00:15:00 Identify Your Best Platform Or Software 01:00:00 Select A Web Host 01:00:00 Collect Your Site 00:15:00 Building A Content Rich Website 00:15:00 Build Backlinks 00:30:00 Use SEO, Multimedia And Social Sites 01:30:00 Use Analytics 01:00:00 Wrapping Up 00:15:00 Mock Exam Mock Exam-Web Development Basics 00:20:00 Final Exam Final Exam-Web Development Basics 00:20:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

About Course Master the fundamental building block of the web and learn to create beautiful and functional websites with HTML5. In this comprehensive course, you will learn: The basics of HTML syntax, including elements, attributes, and tags. How to structure your web pages using HTML5 semantic elements. How to add images, videos, and other multimedia content to your websites. How to create interactive web pages using forms and buttons. How to style your websites using CSS. This course is perfect for beginners with no prior experience in HTML. However, if you have some programming experience, you will be able to learn the material more quickly. You will learn from an experienced web developer who will teach you the concepts and skills you need to succeed. By the end of this course, you will be able to: Create and structure web pages using HTML5. Add multimedia content and interactive elements to your websites. Style your websites using CSS. Build a portfolio of real-world websites Throughout the course, you will work on a variety of hands-on projects to build your skills and create a portfolio of real-world websites. Join a supportive community of learners You will have access to a dedicated student forum where you can ask questions and get help from the instructor and other students. Enroll today and start your journey to becoming a web developer! Bonus: Get access to the instructor's personal collection of HTML5 resources. Why learn HTML5? HTML5 is the latest version of HTML, and it is the most widely used markup language in the world. It is used to create the structure and content of web pages. HTML5 is a powerful tool that can be used to create a variety of websites, from simple static pages to complex dynamic applications. Here are some of the benefits of learning HTML5: HTML5 is easy to learn, even for beginners. HTML5 is a versatile language that can be used to create a variety of websites. HTML5 is in high demand, and there are many job opportunities for HTML5 developers. HTML5 is a valuable skill to have, even if you are not planning to become a web developer. So what are you waiting for? Enroll in this course today and start your journey to becoming a web developer! What Will You Learn? Become a modern and confident HTML developer, no prior knowledge needed! Learn to quickly apply CHatGPT AI skills for your website development Design and build a stunning real-world project for your portfolio from scratch A web design framework with easy-to-use rules and guidelines to design eye-catching websites How to make websites work on every possible mobile device (responsive design) You will learn quickly prompt engineering skills to make real-world websites Learn to Publish your website on production servers using FTP app Course Content Getting Started Introduction to Getting Started Course Curriculum How to Get Pre - Requisites Getting Started on Windows, Linux or Mac How to Ask Great Questions FAQ's HTML Setting Up Local Environment Introduction to HTML Choosing Code Editor Installing Code Editor (Sublime Text) Overview of a Webpage Structure of a Full HTML Webpage First Hello World Webpage Summary HTML Basic Introduction Heading Tags Paragraph Formatting Text List Items Unordered List Items Ordered Classes IDs Comments Summary HTML Intermediate Introduction Images Forms Form Actions Br Tag Marquee Text Area Tables Links Navbar - Menu HTML Entities Div Tag Google Maps Summary HTML Advanced Introduction HTML5 Audio HTML5 Video Progress Bar Drag and Drop Canvas Iframes Input Types Input Attributes YouTube Video Linking Creating Responsive Page Summary HTML Expert Introduction Registration Form Login Form About Us Form Contact Us Form Footer Form Integrate All Together Coding Exercise Solution for Coding Exercise Summary Publish Your Website Live Introduction Installing Free FTP Solution (FileZilla) Setting Up FTP (File Transfer Protocol) Publish Website to Hosting Server Summary HTML Website Project Introduction Challenge - HTML 5 Clock Face with Numbers Project Overview Conclusion on Project Summary A course by Sekhar Metla IT Industry Expert RequirementsNo coding or design experience necessary for this courseAny computer works - Windows, Linux or macOSYou don't need to buy any software - we will use the best free code editor in the world

Learn Object-oriented Programming in Python-beginner-level! (Exercises + cheat sheets + better Coding)!

Learning Smartsheet doesn't need any prior coding experience. This complete hands-on course helps you get familiar with the concepts of working on a Smartsheet from scratch. You will be able to manage projects and track progress in an organized manner. This course is specifically designed for beginners.

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.

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Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the

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