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Flash Sale! 17-in-1 Premium Bundle | CPD Certified | 17 Free PDF Certificates Certificates | Lifetime Access

Flash Sale! 17-in-1 Premium Bundle | CPD Certified | 17 Free PDF Certificates Certificates | Lifetime Access

Ignite your dynamic career and strengthen your deep insight knowledge by signing up for Sustainable Horticulture Training. This course is the ideal approach for you to obtain a thorough understanding and knowledge of the subject. We are concerned about the progression of your career. Therefore, after conducting extensive studies and consulting with experienced personnel, we formulated this outstanding Sustainable Horticulture Training course to improve your pertinent skills. In this easy-to-digest course, you will get exclusive training, which will enable you to stand out in this competitive market. However, the course covers all of the recent materials in order to keep you up to date with the job market and make you a good fit for your career. This top-notch Sustainable Horticulture Training course curriculum comprises basic to advanced levels of modules that will increase your skill sets. After completing this programme, you will attain the productivity to succeed in your organisation. So, if you are eager to see yourself in a gratifying career, then enrol in the course today! What will Make You Stand Out? On completion of this Sustainable Horticulture Training online course, you will gain: CPD QS Accredited course After successfully completing the Course, you will receive a FREE PDF Certificate as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials. Enroling in the Course has no additional cost. 24x7 Tutor Support You can study and complete the course at your own pace. Course Curriculum Sustainable Horticulture Training Module 01: Introduction to Horticulture Module 02: Structure and Function of Horticulture Plants Module 03: Growth of Horticulture Plants Module 04: Impact of Temperature Module 05: Impact of Light Module 06: Impact of Soil and Water Module 07: Plant Propagation Module 08: Plant Nutrition Module 09: Harvesting, Training and Pruning Module 10: Growing Plant Indoors Module 11: Ornamental Horticulture and Garden Design Module 12: Cut Floral Design and Landscaping Module 13: Plant Pathology, Entomology and Weed Control Module 14: Permaculture and Arboriculture Module 15: Professional Opportunities in Horticulture Module 16: Biotechnology Applications in Horticulture Show off your new skills with a certificate of completion. After successfully completing the course, you can order your CPD Accredited Certificates as proof of your achievement absolutely free. Please Note: The delivery charge inside the U.K. is £4.99, and international students have to pay £8.99. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Course the Right Option for You? This Sustainable Horticulture Training course is open to everybody. You can access the course materials from any location in the world and there are no requirements for enrolment. Requirements Without any formal requirements, you can delightfully enrol in this Sustainable Horticulture Training course. Just get a device with internet connectivity and you are ready to start your learning journey. Thus, complete this course at your own pace. Career path The aim of this exclusive Sustainable Horticulture Training course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas.

Level 4 QLS Endorsed Diploma | 120 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Get ready for an exceptional online learning experience with the Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle! This carefully curated collection of 20 premium courses is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations. The Mechanical Engineering & Car Maintenance package is dynamic, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Mechanical Engineering & Car Maintenance package has something for everyone. As part of the Mechanical Engineering & Car Maintenance, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth! This Bundle Comprises the Following Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic CPD-accredited courses: Course 01: Mechanical Engineering Course 02: Electric Vehicle Battery Management System Course 03: Automotive Engineering: Onboard Diagnostics Course 04: Hybrid Vehicle Expert Training Course 05: Large Goods Vehicle (LGV) Course 06: Car Mechanic Interactive Online Training Course 07: Bicycle Maintenance Course Course 08: Motorbike Maintenance Course Course 09: Automotive Engineering: Onboard Diagnostics Course 10: Diploma in Supercharger Automobile Engineering Course 11: Crack Your Mechanical Engineer Interview Course 12: Engine Lubrication Systems Online Course Course 13: MET Technician Course 14: Workshop Technology: Machine Shop Theory Course 15: Workplace First Aid Online Training Course Course 16: Career Development Plan Fundamentals Course 17: CV Writing and Job Searching Course 18: Learn to Level Up Your Leadership Course 19: Networking Skills for Personal Success Course 20: Ace Your Presentations: Public Speaking Masterclass What will make you stand out? Upon completion of this online Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle, you will gain the following: CPD QS Accredited Proficiency with this Mechanical Engineering & Car Maintenance bundle After successfully completing the Mechanical Engineering & Car Maintenance 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 in this Mechanical Engineering & Car Maintenance bundle The online test with immediate results You can study and complete the Mechanical Engineering & Car Maintenance bundle at your own pace. Study for the Mechanical Engineering & Car Maintenance bundle using any internet-connected device, such as a computer, tablet, or mobile device. Each course in this Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Mechanical Engineering & Car Maintenance bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Embrace the future of learning with Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic , a rich anthology of 30 diverse courses. Our experts handpick each course in the Mechanical Engineering & Car Maintenance bundle to ensure a wide spectrum of learning opportunities. This Mechanical Engineering & Car Maintenance bundle will take you on a unique and enriching educational journey. The Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Mechanical Engineering & Car Maintenance bundle offers you the flexibility and convenience to learn at your own pace. Make the Mechanical Engineering & Car Maintenance package your trusted companion in your lifelong learning journey. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic bundle is perfect for: Aspiring automotive engineers: Ideal for those interested in a career focused on car design, development, and manufacturing. Car enthusiasts: Suitable for individuals passionate about car mechanics and who wish to understand how to maintain and repair vehicles professionally. Motorcycle aficionados: Designed for those who want to specialise in motorcycle mechanics, including repair and custom modifications. Career changers: Perfect for individuals looking to shift their career path towards automotive and mechanical engineering sectors. Technical school leavers: A great fit for recent graduates from technical schools who aim to expand their practical knowledge and skills in specific areas of mechanical engineering. Requirements You are warmly invited to register for this Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic 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 Upon Mechanical Engineering: Automotive Engineering, Car Maintenance, Motorcycle & Met Mechanic course completion, you can expect to: Automotive Engineer Car Maintenance Technician Motorcycle Mechanic Met Technician (Metallurgical Technician) Performance Specialist Automotive Designer Quality Control Inspector Service Manager Automotive Research and Development Entrepreneur in Automotive Sector Certificates CPD Certificates Digital certificate - Included

Duration 3 Days 18 CPD hours This course is intended for This introductory-level course is for experienced DBAs who will be working with MongoDB. In order to gain the most from this course you should have: Prior practical experience in Database Administration Experience working with Linux and be comfortable working with command line Overview This skills-focused course is approximately 50% hands-on. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will explore: The MongoDB Basic Architecture and Installation MongoDB administration User Management MongoDB security Indexes Backup & Recovery High Availability / Replication Diagnostics & Troubleshooting MongoDB is fast becoming the database of choice for big data applications, being one of the most popular and widely implemented NoSQL databases. Its scalability, robustness, and flexibility have made it extremely popular among business enterprises who use it to implement a variety of activities including social communications, analytics, content management, archiving and other activities. This has led to an increased demand for MongoDB administrators who have the skills to handle cross functional duties. Geared for experienced DBAs, MongoDB for DBAs is a three-day hands-on course that explores the concepts, architecture and pitfalls of managing a MongoDB installation. This course is targeted to the DBA who is familiar with the concepts and tasks of working with a Relational database and is not responsible for a NoSQL MongoDB database. You will learn the critical aspects of MongoDB and use it to solve data management challenges. You will learn to manage MongoDB effectively by gaining expertise in MongoDB administration tools, syntax, MongoDB installations, configurations, security, troubleshooting, backup, scaling and many other features. The focus of this course is on practical skills and applying the DBA existing database knowledge to a MongoDB installation. Introduction to MongoDB Basic Architecture and Installation Differentiate database categories Learn MongoDB design goals List MongoDB tools Describe JSON and BSON Understanding the basic concepts of a Database Database categories: What is NoSQL? Why NoSQL? Benefit over RDBMS Types of NoSQL Database, and NoSQL vs. SQL Comparison, ACID & Base Property CAP Theorem, implementing NoSQL and what is MongoDB? Graph Database Overview of MongoDB, Design Goals for MongoDB Server and Database, MongoDB tools Understanding the following: Collection, Documents and Key/Values, etc., Introduction to JSON and BSON documents Environment setup (live Handson) and using various MongoDB tools available in the MongoDB Package MongoDB Administration Take database backup and restore MongoDB© Export and import data from/ to a MongoDB© instance Check server status and DB status Monitor various resource utilization of a mongod instance Understand various optimization strategies Administration concepts in MongoDB Monitoring issues related to Database Monitoring at Server, Database, Collection level, and various Monitoring tools related to MongoDB Database Profiling, Locks, Memory Usage, No of connections, page fault etc., Backup and Recovery Methods for MongoDB Export and Import of Data to and from MongoDB Run time configuration of MongoDB Production notes/ best practices Data Managements in MongoDB (Capped Collections/ Expired data from TTL), TTL Collection Features GridFS Memory-Mapped Files Journaling Mechanics Storage Engines Power of 2-Sized Allocations No Padding Allocation Strategy Diagnosing Performance Issues Optimization Strategies for MongoDB Configure Tag Sets for Replica Set. Optimize Query Performance Monitoring Strategies for MongoDB . MongoDB Utilities MongoDB Commands MongoDB Management Service (MMS) Data Backup Strategies in MongoDB Copying Underlying Data Files Backup with MongoDump Fsync and Lock MongoDB Ops Manager Backup Software Security Strategies in MongoDB Authentication Implementation in MongoDB . Authentication in a Replica set Authentication on Sharded Clusters Authorization End-to-End Auditing for Compliance User Management Create a User Administrator. Add a User to a Database. Create/Assign User a Role. Verify/Modify a User Access/Privileges. Change a User?s Password MongoDB Security Knowing security concepts in MongoDB Understand how Authentication and Authorisation works Security Introduction Security Concepts Indexes Index Introduction, Index Concepts, Index Types Index Properties Index Creation and Indexing Reference Introduction to Aggregation Aggregation Approach to Aggregation sort Order Pipeline Operators and Indexes Text Indexes Aggregate Pipeline Stages Text Search MapReduce Index Creation Aggregation Operations Index Creation on Replica Set Remove, Modify, and Rebuild Indexes Listing Indexes Measure Index Use Control Index Use Index Use Reporting Geospatial Indexes MongoDB?s Geospatial Query Operators GeoWith Operator Backup & Recovery Import and Export MongoDB Data Restore and recovery of MongoDB(Including point in time Recovery) Restore a Replica Set from MongoDB Backups Recover Data after an Unexpected Shutdown Backup and Restore with Filesystem Snapshots Back Up and Restore with MongoDB Tools Backup and Restore Sharded Clusters High Availability (Replication ) Understand the concept of Replication in MongoDB© ? Create a production like Replica Set Introduction to Replication (High Availability), Concepts around Replication What is Replica Set and Master Slave Replication? Type of Replication in MongoDB How to setup a replicated cluster & managing replica sets etc., Master-Slave Replication Replica Set in MongoDB Automatic Failover Replica Set Members Write Concern Write Concern Levels Write Concern for a Replica Set Modify Default Write Concern Read Preference Read Preference Modes Blocking for Replication Tag Set Configure Tag Sets for Replica set. Replica Set Deployment Strategies . Replica Set Deployment Patterns Oplog File Replication State and Local Database, Replication Administration Diagnostics & Troubleshooting Troubleshoot slow queries Diagnose connectivity problems Understand diagnostic tools Learn common production issues Learn fixes and solutions. Additional course details: Nexus Humans Introduction to MongoDB for DBAs (TTDB4680) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to MongoDB for DBAs (TTDB4680) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

"This course aims to explore the intricate link between buyer behavior and effective promotional strategies, emphasizing e-consumer behavior within the digital landscape. Participants will delve into the pivotal role of digital technologies in elevating customer experience, leveraging algorithms, artificial intelligence, mastering online complaint resolution, and post-purchase management. Moreover, it covers integrated marketing communications and relationship marketing, equipping learners with the expertise to assess marketing metrics for proficient customer relationship management upon completion." "After completing this course successfully, learners will gain proficiency in the following key areas: Understanding buyer behavior and effective promotional strategies. Analyzing e-consumer behavior in the digital realm. Implementing digital technologies to enhance customer experience. Harnessing algorithms and Artificial Intelligence for effective utilization. Excelling in online complaint handling and post-purchase management. Implementing integrated marketing communications and relationship marketing strategies. Evaluating marketing metrics for proficient customer relationship management." This course aims to explore the relationship between buyer behavior and promotional strategies, with a specific focus on e-consumer behavior in a digital context. It will examine the impact of digital technologies on customer experience, including the use of algorithms and artificial intelligence. The course will also cover topics such as online complaint handling and post-purchase management, integrated marketing communications, and relationship marketing. Additionally, students will learn how to evaluate marketing metrics to manage customer relationships effectively. This course aims to explore the relationship between buyer behavior and promotional strategies, with a specific focus on e-consumer behavior in a digital context. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Managing Customer Experience Communication Self-paced pre-recorded learning content on this topic. Managing Customer Experience Communication Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. Customer Experience Communication Manager Customer Journey Communication Specialist Experience Design and Communications Lead Customer Relations Communications Coordinator Brand Experience Manager Customer Engagement Strategist Digital Customer Experience Manager Customer Experience Communications Analyst User Experience Communication Consultant Customer Insight and Engagement Officer   Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

XSLT training course description This course has been designed as a follow on course for the XML primer course. The course looks at the use of XSLT in the transforming and styling XML documents. What will you learn Transform and style XML documents using XSLT. XSLT training course details Who will benefit: Anyone working with XSLT. Prerequisites: XML primer Duration 2 days XSLT training course contents Introduction Extensible Stylesheet Language (XSL), transforming and formatting XML. XML refresher The basic rules for building an XML document. An introduction to XSLT The basic concepts of XSLT, xsl:output, xsl:template, xsl:value-of. XML documents as trees How the original XML is transformed into a set of nodes, the general terms for manipulating node trees. Paths (XPath) Use of path matching to select required nodes for transformation. Using templates xsl:apply-templates, xsl:template match, nested templates, xsl:copy , <comment> and <element> , default templates, parameters. Control xsl:if, xsl:choose, xsl:for-each, xsl:sort. Constructing the result tree xsl:output, xsl:attribute, xsl:attribute-set, xsl:comment, xsl:processing-instruction, xsl:text, xsl:value-of, xsl:variable. Combining templates xsl:include, xsl:import, xsl:apply-imports. Transforming to text

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.

4G training course description This course is designed to give the delegate an understanding of the technologies used within a 3G UMTS mobile network. During the course we will investigate the UMTS air interface and the use of Wideband-Code Division Multiple Access (WCDMA) to facilitate high speed data access, together with HSPA to offer mobile broadband services. We will describe the use of soft handover rather than hard handover procedures and soft capacity sharing. The course includes a brief exploration of the UMTS protocol stack and the use of PDP Context and QoS support features. What will you learn Explain the 3G UMTS architecture. Describe the role of a Drifting & Serving RNC. Explain the use of ARQ & HARQ for mobile broadband. Describe how IMS integrates into the architecture. Describe the use of Media Gateway Controllers. Identify the temporary identities used within 3G UMTS. 4G training course details Who will benefit: Anyone working within the telecommunications area, especially within the mobile environment. Prerequisites: Mobile communications demystified Telecommunications Introduction Duration 2 days 4G training course contents LTE Introduction The path to LTE, 3GPP. LTE to LTE advanced. LTE Architecture The core, Access, roaming. Protocols: User plane, Control plane. Example information flows. Bearer management. Spectrum allocation. LTE technologies Transmission, reception, OFDMA, multiple antenna, MIMO. LTE Air interface Air interface protocol stack. Channels, Resource Grid, cell acquisition. Up and downlink controls. Layer 2 protocols. Cell acquisition Power on, selecting networks and cells. RRC connection. Attach procedure. Mobility management Roaming, RRC_IDLE, RRC_CONNECTED, cell reselection, handover, interoperation with UMTS and GSM networks. Voice and text IMS, QoS, policy and charging.