20214 Courses

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.

This Early Years qualification is ideal for current early year practitioners who want to expand their knowledge of the Early-Years in order to provide quality care for children and young people. By studying this course, you will have proven that you possess in-depth knowledge of managing and leading a team of early years practitioners to provide care that meets the highest standards outlined in the EYFS. Our course is suitable for existing Early Years Practitioners who want to advance their childcare knowledge. The course goes into greater detail to provide management and senior-level staff members with a solid understanding of key aspects within a childcare environment such as safeguarding, managing a team, professional partnerships, and how to work to the highest standards within the early years. The course includes specialized modules that break down each topic and ensure that our students receive an exceptional and comprehensive education. So, enrol in this Early Years course today and start learning instantly! Learning Outcomes By the end of this Early Years course, the learner will be able to: Understand the emotional and physical well-being of children. Understand equality, diversity and professional partnerships. Understand health and safety legislation. Describe observations, assessments and planning. Explain safeguarding children. Understand the Early Years Foundation Stage. Manage in a nursery environment. Engage in professional development. Why Choose Level 4 Early Years Course from Us Self-paced course, access available from anywhere. Easy to understand, high-quality study materials. Course developed by industry experts. MCQ quiz after each module to assess your learning. Automated and instant assessment results. 24/7 support via live chat, phone call or email. Free PDF certificate as soon as completing the course. ***Courses are included in this Bundle Course Course 01: Early Years Course 02: Child Protection and Risk Assessment Course 03: Childcare and Nutrition Course 04: Care and support for Vulnerable Children Course 05: Child and Adolescent Mental Health Course Course 06: Diploma in Special Education Needs (SEN) Exploitation (CSE & CCE) Awareness Training Course 07: Level 5 Childcare Training Course 08: Introduction to Psychology Course 09: EYFS Teaching Diploma Course 10: Equality and Diversity Course 11: Level 3 Dyslexia Awareness ***Other Other Benefits of Early Years Bundle Course Free 11 PDF Certificate Lifetime Access Free Retake Exam Tutor Support [ Note: Free PDF certificate as soon as completing the Early Years course ] Detailed course curriculum of Level 4 Early Years Course Module 01: Supporting the Emotional and Physical Well-being of Children Module 02: Equality, Diversity and Professional Partnerships Module 03: Health and Safety Legislation Module 04: Observations, Assessments and Planning Module 05: Safeguarding Children Module 06: The Early Years Foundation Stage Module 07: Managing in a Nursery Environment Module 08: Engaging in Professional Development >>---------------<< Assessment Method After completing each module of the Early Years Course, you will find automated MCQ quizzes. To unlock the next module, you need to complete the quiz task and get at least 60% marks. Certification After completing the MCQ/Assignment assessment for this Early Years Course, you will be entitled to a Certificate of Completion from Training Tale. The certificate is in PDF format, which is completely free to download. A printed version is also available upon request. It will also be sent to you through a courier for £13.99. Who is this course for? This Early Years course is designed for anyone interested in working as a nursery nurse in a childcare setting. Suitable for both new and existing nursery nurses, the course develops an understanding of childcare and how to work with young people. Requirements There are no specific requirements for this Early Years course course because it does not require any advanced knowledge or skills. Career path The Early Years Course is designed to give you the skills and knowledge you need to land your dream job, advance at work, go self-employed, or start your own business. Certificates Certificate of completion Digital certificate - Included

Feeling Stuck in Your Career? The Entrepreneurship: Business Development & Business Management with Investment Bundle is Your Skill-Building Solution. This exceptional collection of 30 premium courses is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the Entrepreneurship: Business Development & Business Management bundle provides an engaging learning experience, helping you learn skills across various disciplines. With Entrepreneurship: Business Development & Business Management with Investment Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The Entrepreneurship: Business Development & Business Management bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set. By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Entrepreneurship: Business Development & Business Management with Investment bundle on your job life and career growth! This Entrepreneurship: Business Development & Business Management with Investment Bundle Comprises the Following CPD Accredited Courses: Course 01: Administrative Management Course 02: Office Administration Course 03: Business Management Course 04: Strategic Business Management - Online Diploma Course Course 05: Business Performance Management Course 06: Business Law Course 07: Strategic Management - Industry Change And Value Curves Course 08: Applied Business Strategy for Managers Course 09: Leadership and Management Course Course 10: Business Studies Course 11: Diploma in Business Analysis Course 12: Business Plan Course 13: Entrepreneurship Training Course 14: Investment Course 15: Business Accounting Training Course 16: Finance and Budgeting Course Course 17: Finance: Financial Risk Management Course 18: Financial Statement Analysis Masterclass Course 19: Introduction to Corporate Finance Course 20: UK Tax Accounting Course 21: Managerial Accounting Masterclass Course 22: Xero Accounting and Bookkeeping Online Course 23: Corporate Risk And Crisis Management - Online Course Course 24: Resourcing and Managing Talent Course Course 25: Customer Relationship Management Course 26: Career Development Plan Fundamentals Course 27: CV Writing and Job Searching Course 28: Learn to Level Up Your Leadership Course 29: Networking Skills for Personal Success Course 30: Ace Your Presentations: Public Speaking Masterclass What will make you stand out? Upon completion of this online Entrepreneurship: Business Development & Business Management with Investment Bundle, you will gain the following: CPD QS Accredited Proficiency with this Entrepreneurship: Business Development & Business Management Bundle After successfully completing the Entrepreneurship: Business Development & Business Management bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials of this Entrepreneurship: Business Development & Business Management Bundle The online test with immediate results You can study and complete the Entrepreneurship: Business Development & Business Management bundle at your own pace. Study for the Entrepreneurship: Business Development & Business Management bundle using any internet-connected device, such as a computer, tablet, or mobile device. The Entrepreneurship: Business Development & Business Management with Investment bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development. Advance the future of learning with the Entrepreneurship: Business Development & Business Management bundle, a comprehensive, complete collection of 30 courses. Each course in the Entrepreneurship: Business Development & Business Management bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience. Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the Entrepreneurship: Business Development & Business Management bundle offers the flexibility and convenience to learn at your own pace. Make the Entrepreneurship: Business Development & Business Management package your trusted partner in your lifelong learning journey. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Entrepreneurship: Business Development & Business Management with Investment is perfect for: Expand your knowledge and skillset for a fulfilling career with the Entrepreneurship: Business Development & Business Management bundle. Become a more valuable professional by earning CPD certification and mastering in-demand skills with the Entrepreneurship: Business Development & Business Management bundle. Discover your passion or explore new career options with the diverse learning opportunities in the Entrepreneurship: Business Development & Business Management bundle. Learn on your schedule, in the comfort of your home - the Entrepreneurship: Business Development & Business Management bundle offers ultimate flexibility for busy individuals. Requirements You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the Entrepreneurship: Business Development & Business Management bundle. Certificates CPD Certificates Digital certificate - Included

10 QLS Endorsed Courses for Estate Agents | 10 QLS Endorsed Certificates Included | Lifetime Access | Tutor Support

10 QLS Endorsed Courses for Hospitality Manager | 10 Endorsed Certificates Included | Life Time Access

Augmented Reality is one of the promising and ever-growing sectors of IT! Enter the world of Augmented Reality

This course will help anyone supporting or moving into the sector with the knowledge and tools to communicate effectively with real estate professionals.

Prepare for a rewarding career shaping young minds with our Pre-School Teacher Certificate Course. Gain essential skills in early childhood education, curriculum development, and classroom management. Start your journey to becoming a nurturing and effective pre-school teacher today.

How purposeful, high quality feedback can be used effectively to drive progress.

Level 7 QLS Endorsed Course | Endorsed Certificate Included | Plus 5 Career Guided Courses | CPD Accredited