4554 Operations courses in Oldham delivered Online

The Statistics Analyst - CPD Accredited Course provides a dynamic and in-depth understanding of statistical analysis, designed for those seeking to develop their analytical abilities in various industries. Through this course, participants will gain a solid grounding in statistical methods, techniques, and tools that are essential for making data-driven decisions. The curriculum has been crafted to enhance learners’ understanding of key statistical concepts, empowering them to interpret and analyse data effectively. By completing this course, learners will be equipped with the knowledge to apply statistical analysis to real-world scenarios, boosting their analytical thinking and decision-making capabilities. With a focus on developing core analytical expertise, the course is ideal for individuals looking to advance their careers in data analysis, research, or any field where data plays a critical role. Whether you are pursuing a career in business, healthcare, or marketing, this CPD-accredited course offers a professional route to becoming a proficient statistics analyst. Learning Outcomes: It's your chance to start with ourITcourse and give your resume the stamp of approval that employers are looking for. So, pick up your card now and fill up your virtual basket with this highly-rated Statistics Analyst - CPD Accredited online training program from Training Express Still not convinced? Take a glimpse of the key benefits you'll get with - Lessons prepared in collaboration with Professionals User-friendly Learner Management System (LMS) Syllabus designed in line with the standards of the UK Education System Updated Study Materials focusing both on Knowledge and Skill based training Guidance to expand in 'a' territory and move forward with Data Analyst profession Free Assessment to test learners' knowledge and skills · Accredited learning and widely recognised certificate from reputed CPD Accreditation Bodies Course Curriculum: Module 01: Introduction to Statistics Module 02: Measuring Central Tendency Module 03: Measures of Dispersion Module 04: Correlation and Regression Analysis Module 05: Probability Module 06: Sampling Module 07: Charts and Graphs Module 08: Hypothesis Testing Module 09: Business Processes Module 10: Business Analysis Planning and Monitoring Module 11: Strategic Analysis and Product Scope Module 12: Ratio Analysis Module 13: Planning & Forecasting Operations Module 14: Ten Common Statistical Mistakes Course Assessment You will immediately be given access to a specifically crafted MCQ test upon completing the Statistics Analyst - CPD Accredited course. For each test, the pass mark will be set to 60%. Accredited Certificate After successfully completing this Statistics Analyst - CPD Accredited course, you will qualify for the CPD Quality Standards (CPD QS) certified certificate from Training Express. CPD 10 CPD hours / points Accredited by The CPD Quality Standards (CPD QS) Who is this course for? The Statistics Analyst - CPD Accredited training is ideal for highly motivated individuals or teams who want to enhance their skills and efficiently skilled employees. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Learn the essential skills and knowledge you need to excel in your professional life with the help & guidance from our Statistics Analyst - CPD Accredited training.

Set your course for a thriving career in travel and tourism management. Our Travel & Tourism Management Career Track Diploma equips you with essential skills to excel in this exciting industry, creating memorable experiences for travellers worldwide. **16 Free CPD Certificates** Dive into the exciting world of Travel & Tourism with our complete Career Track Diploma. This pack includes 16 courses covering everything from tourism basics, looking after hotel guests, and getting better at talking and growing yourself. Whether you're new to the industry or aiming to upgrade your expertise, this diploma will equip you with the tools to excel in the competitive travel and tourism market. From mastering the intricacies of event management to understanding the logistics behind travel arrangements, the curriculum strikes a harmonious balance between theoretical knowledge and practical insights. With a focus on developing key leadership and organisational skills, you'll emerge as a well-rounded professional, ready to shape the future of travel and tourism. Learning Outcomes Understand the fundamentals of tourism and travel management. Develop insights into hospitality and event management. Cultivate essential communication and reporting skills. Enhance personal and time management capabilities. Acquire knowledge in Six Sigma for project management. Discover the art of travel blogging. Key Features Accredited by CPD Instant e-certificate Fully online, interactive Tourism Management courses with audio voiceover Self-paced learning and laptop, tablet, smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases How you will benefit from this Travel & Tourism Management Career Track Diploma All through this self-paced training, you will get engaging learning materials and acquire the necessary knowledge to work with various concepts to gain a competitive advantage in the employment market. Each course within this Travel & Tourism Management Career Track Diploma is thoughtfully crafted to deepen your understanding of different Travel and Tourism concepts and arm you with theoretical knowledge and skills vital to the Travel and Tourism sector. Course 1: Tourism Management Delve deep into the intricacies of the tourism sector, exploring core concepts and industry practices. Course 2: Travel and Tourism Discover the broad world of travel, from trip planning to understanding traveller behaviour. Course 3: Hospitality Unveil the art of impeccable service, learning the essentials of guest satisfaction and hotel operations. Course 4: Hospitality Assessor Evaluate and assess hospitality standards to ensure exceptional service quality and consistency. Course 5: Event and Hospitality Management Master the dynamics of event planning whilst integrating key hospitality components for memorable experiences. Course 6: Hospitality and Tourism Management Integrate key knowledge areas, merging the worlds of hospitality and tourism for a holistic approach. Course 7: Travel Agent Navigate the role of travel agents, from itinerary planning to client consultations. Course 8: Transport And Logistic Understand the backbone of travel - transport logistics, ensuring smooth and efficient movement. Course 9: Communication and Organisational Skills Enhance your communication prowess and learn to organise tasks and teams efficiently. Course 10: Personal Development Skills Invest in personal growth, focusing on self-awareness, resilience, and continuous learning. Course 11: Leadership & Management: Interpersonal Skills Hone leadership qualities and manage teams with effective interpersonal interactions. Course 12: Effective Organisational Reporting Master the art of producing clear, concise, and effective organisational reports. Course 13: Time Management Skills Maximise productivity by mastering the skill of managing time effectively and setting priorities. Course 14: Effective Communication Training Level-3 Elevate your communication skills, ensuring clarity, empathy, and assertiveness in interactions. Course 15: Project Management: Six Sigma Introduce yourself to Six Sigma methodology, optimising processes for improved project outcomes. Course 16: Travel Blogger Dive into the digital realm of travel, crafting engaging content and captivating travel stories. Accreditation: All of our courses included in thisTravel & Tourism Management Career Track Diploma are fully CPDQS accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certification: Once you've successfully completed the courses in this bundle, you will immediately be sent digital certificates for each course. CPD 65 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Travel & Tourism Management Career Track Diploma will benefit the following professionals in the Travel and Tourism field, whether you are an aspiring professional or holding an experienced role in the sector. Aspiring travel consultants or agents. Individuals keen on hospitality management roles. Those considering a career in event management. Enthusiasts looking to delve into travel blogging. Individuals aiming to strengthen leadership abilities. Professionals seeking improved organisational skills. Graduates exploring diverse sectors within tourism. Career switchers intrigued by travel & tourism industry. Requirements There are no formal requirements for this Travel & Tourism Management Career Track Diploma to be enrolled. Career path This Travel & Tourism Management Career Track Diploma will help you understand the fundamental knowledge required in the following career paths - Travel Consultant Hospitality Manager Event Coordinator Travel Blogger Tourism Promotion Officer Transport & Logistics Coordinator. Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included You will get the hard copy certificates for Free! The delivery charge of the hard copy certificate inside the UK is £3.99 each.

Dive into the dynamic world of retail banking and discover its intricate workings with the course, 'Retail Banking Fundamentals: Navigating the Financial World'. This comprehensive guide unravels the complexities of the financial realm, presenting them in an easy-to-grasp manner for those eager to embark on a journey into the banking sector. From the foundational aspects of banking to the nuanced skills of cash sorting and fraud handling, every module has been designed to provide a holistic understanding of the industry and empower you to navigate the financial world with confidence. Learning Outcomes Understand the foundational concepts of retail banking and its various services. Differentiate between the categories of banking institutions and their functions. Develop proficiency in bank account operations, from opening to management. Acquire essential skills in bookkeeping, payment processing, and handling fraudulent activities. Grasp the principles of customer service, risk management, and ethics within the banking domain. Why buy this Retail Banking Fundamentals: Navigating the Financial World? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Retail Banking Fundamentals: Navigating the Financial World there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Retail Banking Fundamentals: Navigating the Financial World for? Individuals aspiring to pursue a career in the retail banking sector. Current banking employees seeking to deepen their knowledge and understanding. Finance and commerce students aiming to expand their educational horizon. Entrepreneurs and business owners who interact regularly with banks. Anyone interested in understanding the mechanics of the financial world. Prerequisites This Retail Banking Fundamentals: Navigating the Financial World does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Retail Banking Fundamentals: Navigating the Financial World was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Bank Teller - Average UK salary: £18,000 - £22,000. Customer Service Representative (Bank) - Average UK salary: £19,000 - £23,500. Risk Management Analyst - Average UK salary: £32,000 - £47,000. Bank Branch Manager - Average UK salary: £30,000 - £55,000. Fraud Investigator - Average UK salary: £28,000 - £43,000. Bookkeeper - Average UK salary: £20,000 - £27,000 Course Curriculum Module 01: Introduction to Banking Introduction to Banking 00:13:00 Module 02: Banking Services Banking Services 00:11:00 Module 03: Categories of Banking Institutions Categories of Banking Institutions 00:13:00 Module 04: Bank Teller Bank Teller 00:08:00 Module 05: Bank Accounts and Opening Them Bank Accounts and Opening Them 00:14:00 Module 06: Mathematics for Bank Tellers Mathematics for Bank Tellers 00:15:00 Module 07: Bookkeeping and Payment Bookkeeping and Payment 00:14:00 Module 08: Cash Sorting & Counterfeit Identification Cash Sorting & Counterfeit Identification 00:12:00 Module 09: Fraud Handling Fraud Handling 00:12:00 Module 10: Customer Services Customer Services 00:12:00 Module 11: Banking Risk Management Banking Risk Management 00:13:00 Module 12: Ethics Ethics 00:06:00

Description: In this current world, it is imperative to have computer skills for personal and professional field. If you are someone who is new to this idea and looking to brush up your skills, then this Computer Operating and Maintenance Foundation Training is perfect stepping stone for you. With the course guidance, you will know about the basic hardware and software stuff in a very minimum time. You will learn how to interact with the applications interface, protect and safeguard your data, customizing your computer, etc. You will also learn about basic input, output and storage devices. Learning Outcomes: Realise the common computing concepts Figure out the difference between hardware and software, as well as how they work Realise the operations of information networks Be conscious of security measures as well as learn working safely Obtain knowledge of the primary steps of operating a computer, involving using the keyboard,mouse, and Windows desktop Become competent to manage and use files and folders with proficiency Get knowledge of how to implement the fundamental Windows Applications,at the same time, learn Wordpad, Notepad, Task Manager, Calculator, Paint and Internet Explorer. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Computer Operating and Maintenance Foundation Training is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Computer Operating and Maintenance Foundation Training is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. General Concepts Basic Terms 00:15:00 Types of Computers 00:15:00 Anatomy of a PC 00:30:00 How a PC Works 00:15:00 Hardware Devices CPU and Memory 00:30:00 Input Devices 00:15:00 Output Devices 00:15:00 Secondary Storage Devices 00:30:00 Software The Basics 00:15:00 Operating Systems and Applications 00:30:00 How is Software Built 00:15:00 Types of Software 00:15:00 Legal Issues 00:15:00 Troubleshooting Software 00:14:00 Hardware, Devices, and Peripherals 00:06:00 Backup and Restore 00:03:00 Mock Exam Mock Exam- Computer Operating and Maintenance Foundation Training 00:20:00 Final Exam Final Exam- Computer Operating and Maintenance Foundation Training 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Build your communication skills to boost the productivity of office administration. Learn Business Etiquette, Organisational Skills, Effective Planning and Scheduling.

Learn advanced joins, folder and workbook integration, and data transformation in our 120-minute course on Microsoft Excel Power Query.

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Duration 5 Days 30 CPD hours This course is intended for Security Professionals Incident Handling Professionals Anyone in a Security Operations Center Forensics Experts Cybersecurity Analysts Overview Our Certified Cyber Security Analyst course helps you prepare an organization to create a complete end to end solution for proactively monitoring, preventing, detecting, and mitigating threats as they arise in real time. Do not fool yourself, this course is far more advanced than you may expect. It is fast paced and thorough, so you can enjoy a well-rounded experience. Be ready to dig deep into the details of security analysis for today's needs. When we are done you will be able to setup and deploy state of the art open source and for purchase analysis tools, intrusion detection tools, syslog servers, SIEMs, along with integrating them for the entire company to find and an many cases prevent today's exploits. This course maps to the mile2 Certified Cyber Security Analyst Exam as well as the CompTIA CySA+CS0-001 certification exam. Our Certified Cyber Security Analyst course helps you prepare an organization to create a complete end to end solution for proactively monitoring, preventing, detecting, and mitigating threats as they arise in real time.Do not fool yourself, this course is far more advanced than you may expect. It is fast paced and thorough, so you can enjoy a well-rounded experience. Be ready to dig deep into the details of security analysis for today?s needs.When we are done you will be able to setup and deploy state of the art open source and for purchase analysis tools, intrusion detection tools, syslog servers, SIEMs, along with integrating them for the entire company to find and an many cases prevent today?s exploits.This course maps to the mile2 Certified Cyber Security Analyst Exam as well as the CompTIA CySA+CS0-001 certification exam. Blue Team?Principles Network Architecture?and how it lays the groundwork Defensive Network Security Data Locations?and how they tie together Security?Operations?Center The People, Processes, and Technology Triage and Analysis Digital Forensics Incident Handling Vulnerability Management Automation, Improvement, and Tuning Digital?Forensics Investigative Theory and?Processes Digital Acquisition Evidence Protocols Evidence Presentation Computer Forensics?Laboratory Protocols Processing Techniques Specialized?Artifacts Advanced Forensics for Today?s?Exploitations Malware Analysis Creating the Safe Environment Static Analysis Dynamic Analysis Behavior Based Analysis What is different about?Ransomware? Manual Code Reversing Traffic Analysis Manual Analysis Principles Automated?Analysis Principles Signatures?compared to?Behaviors Application Protocols Analysis Principles Networking Forensics Assessing the Current State of Defense with the?Organization Network Architecture and Monitoring Endpoint Architecture and Monitoring Automation, Improvement, and continuous?monitoring Leveraging SIEM for Advanced Analytics Architectural Benefits Profiling and?Baselining Advanced Analytics Defeating the Red Team with Purple Team tactics Penetration Testing?with full knowledge Reconnaissance Scanning Enumeration Exploitation Lateral Movement Additional course details: Nexus Humans C)CSA: Cybersecurity Analyst Mile 2 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 C)CSA: Cybersecurity Analyst Mile 2 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.

Embark on a journey to establish a successful cleaning business in the UK with our comprehensive course. Learn start-up costs, business models, legal aspects, and client satisfaction strategies. Ideal for entrepreneurs eager to thrive in the cleaning industry.

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.