Courses in Bristol

Description This course introduces students to project management fundamentals. Topics covered include project management basics, types of projects, building the team and schedule, creating the budget, execution, and more. COURSE CONTENT: Module 1 - Getting Started - 3m Getting Started Instructor Introduction Course Objectives Agenda Agenda Module 2 - Project Management Basics - 27m Project Management Basics PMI's PMBOK What is a Project? Attributes of a Project Examples of Projects What is Project Management Project Constraints “The Iron Triangle” Scope Cost Time How do we make this happen? How do we make this happen? The Fundamental Project Life Cycle The Project Life Cycle Fundamental Project Management Process Outputs Examples Unforeseen Circumstances Recommendations Words of Wisdom The Tools Fundamental Project Management Tools Fundamental Project Management Processes and Tools The People Objectives Stakeholder Customer Sponsor Team Members Management Project Manager's Role Project Manager's Responsibilities Time Management Matrix Time Management Matrix Time IS Money The Benefits of Project Management Summary Agenda Module 3 - Where Do Projects Come From - 56m Where Do Projects Come From Types of Organizations Enterprise Portfolio Management The Agenda BM101 Mission Vision Goals Business Strategy Management By Objectives Balanced Scorecard Approach Balanced Goals Objectives SMART Objectives from Balanced Goals SMART Objectives from Balanced Goals cont. Key Performance Indicators Action Plans BM101 Summary Project Management 101 PM Quotes Phases and Knowledge Areas 10 Knowledge Areas Aligned The Project Triangle PM101 PM101 Programs Portfolio PM101 Summary Enterprise Portfolio Management The Connection The Enterprise V Plans The Enterprise V Objectives The Enterprise V Programs The Enterprise V Portfolio Another View Enterprise Portfolio Management Versus Program & Project Management Summary Why Great ROI? But why is it necessary? Matrix Organization Structure Review Cadence How Projects Are Selected Objectives Needs Identification Business Case Enterprise Portfolio Management Proposing Projects Project Selection “The Funnel Flowchart” Project Prioritization Exercise Thirst Beverage Corporation Project Challenge Agenda Module 4 - Types of Projects - 32m Types of Projects Predictive Versus Agile Predictive Versus Agile Project Management Traditional Versus Agile Project Management Predictive Versus Agile The Predictive Project Life Cycle An Agile Project Life Cycle The Scrum Framework - Modified An Agile Project Life Cycle The Big Picture The Divide Agenda Module 5 - Initiation - 28m Initiation Our Project Our Project Setup 6 Essential Features for a PMIS PMIS Examples Leveraging Microsoft Teams Leveraging Microsoft Teams PMI's Project Life Cycle Fundamental Project Management Processes and Tools Project Charter Leveraging Microsoft Teams Creating a Project Charter Creating a Project Charter Fundamental Project Management Processes and Tools Stakeholder Register Leveraging Microsoft Teams Stakeholder Register Stakeholder Register Creating a Project Charter “The Iron Triangle” Agenda Module 6 - Building the Team - 24m Building the Team The Fundamental Project Life Cycle Build a High Performing Team Benefits of a High Performing Team Stages of Team Development Team Charter Working Agreement Working Agreement Leveraging Microsoft Teams Being a Good Leader Being a Servant Leader Servant Leader Kickoff Meeting Conducting Effective Meetings Agenda Module 7 - Building the Schedule - 52m Building the Schedule The Fundamental Project Life Cycle Fundamental Project Management Processes and Tools What a Schedule looks like….according to Google Benefits of a Project Schedule Aligning To PMI Steps to Build a Schedule 1 Plan Schedule Management Our project 1 Plan Schedule Management Steps to Build a Schedule Project Schedule….according to PMI How to Define Activities What Does It Look Like? Option 2 - WBS* by Work Package Option 3 - WBS By Phase Steps to Build a Schedule Leveraging Microsoft Teams “The Iron Triangle” Microsoft Scheduling Tool Capability Model Microsoft Scheduling Tool Capability Model Project Schedule in Excel Project Schedule in Microsoft Project Project Schedule in Project Online Agenda Module 8 - Creating the Budget - 24m Creating the Budget The Fundamental Project Life Cycle Project Cost Management General Notes Types of Costs What is a budget? Aligning To PMI Steps to Create a Budget 1. Plan Cost Management The Budget Tool Microsoft Scheduling Tool Capability Model Estimated Costs and Budget in Microsoft Project “The Iron Triangle” Agenda Module 9 - Planning Wrap Up - 6m Planning Wrap Up “The Iron Triangle” The Fundamental Project Life Cycle Perform Analysis Obtain Approval Save a Baseline Aligning to PMI Progressive Elaboration Agenda Module 10 - Execution - 41m Execution The Fundamental Project Life Cycle Fundamental Project Management Processes and Tools Managing Your Project Update Schedule and Actual Costs Managing Your Project Fundamental Project Management Processes and Tools Risks Aligning To PMI Risk Management Risk Management Processes Risk Register Risk Management Risk Probability Impact Assessment Risk Management Risk Register Risk Management Risk Management Risk Management Risk Register Risk Management Managing Your Project Issues Fundamental Project Management Processes and Tools Issue Log Fundamental Project Management Processes and Tools Status Report Status Report Status Report Project Status Report Agenda Module 11A - Monitor and Control - 11m Monitor and Control What is Monitor and Control? What is Monitor and Control? What should you monitor? What should you monitor? Project Control Project Control Principles Control Scope What should you monitor? Control Schedule What should you monitor? Control Costs What should you monitor? Module 11B - Earned Value Management - 41m Progress Monitoring Earned Value Management Earned Value Analysis Our Project Pipeline Project The Process to Set Up Pipeline Schedule Baseline Cost over Time Performance Measures Baselined Cost - Timephased PV - Planned Value PV - Planned Value PV - Planned Value PV - Planned Value The Process to Maintain Performing Analysis Performance Measures EV - Earned Value EV - Earned Value EV - Earned Value Performance Measures AC - Actual Cost AC - Actual Cost AC - Actual Cost Variances Cost Variance Schedule Variance Total Variance Graphical Representation Graphical Representation Graphical Representation Graphical Representation Microsoft Project - Math Check! Visual Reports in MS Project Report Exported from MS Project to Excel Aligning with Reality Revised Plan Reschedule Uncomplete Work in MS Project Revised Plan Revised Plan The Moral of the Story Performance Indexes Cost Performance Index Schedule Performance Index Completion Metrics Completion Metrics Completion Metrics Completion Metrics Completion Metrics Project Status as of 4/30 The Process to Maintain Project Status as of 4/30 Microsoft Project Math Check! Why Measure? Why Measure? What should you monitor? Module 11C - Other Items to Monitor - 19m What should you monitor? Risk Monitor and Control Risk Monitor and Control What should you monitor? Control Issues What should you monitor? Manage Stakeholder Engagement What should you monitor? Control Documents What should you monitor? Control The Product, Service or Result Control The Product, Service or Result Quality Terms and Definitions 7 Basic Quality Tools Controlling Quality What should you monitor? Module 11D - Controlling Changes - 3m Controlling Changes Controlling Changes Example Change Request Process Agenda Module 12 - Closure - 9m Closure Fundamental Project Management Processes and Tools Customer Feedback Customer Feedback Survey Lessons Learned Lessons Learned Fundamental Project Management Processes and Tools Project Summary Report Performance Evaluations Documentation Close-out Celebration Agenda Module 13 - Course Wrap Up - 14m Course Wrap Up Project Procurement Management Project Procurement Management Project Procurement Management Typical Steps Procurement Statement of Work Typical Steps Bid Document Typical Steps Contract Types of Contracts Typical Steps Control Procurements Typical Steps Close Procurements Typical Steps Congratulations! Objectives Review Agenda Total Duration: 6h 32m

Artificial intelligence & Javascript 2D Game Development - MinMax algorithm - "Computer vs You" Tic Tac Toe AI game

Course overview Gain the skills to summaries large amounts of data into meaningful information with the Learn Excel With Pivot Tables, Pivot Charts, Slicers, and Timelines course. In this course, you will develop a comprehensive understanding of the PivotTable and PivotChart and explore how they work. In this Learn Excel With Pivot Tables, Pivot Charts, Slicers, and Timelines course, you will learn the steps to create your Pivot table and Pivot chart. We'll show you how to use Pivot tables to summarize large amounts of data. You'll also learn how to use PivotChart to provide visual representation to your summarized data. We will then take you through adding sorts, filters, timelines and slicers to create dynamic dashboards. You will also learn how to use the slicer to slice and dice your data the way you want. Learning outcomes Learn how to summaries data with Pivot Table Be able to add graphical representation to your summarized data with PivotChart Learn how to update the Pivot Table with new data Deepen your understanding of sorting and filtering Be able to import data from various sources with Power Query Gain an excellent understanding of Power Pivot Who is this course for? Professionals who want to learn how to summaries large sums of data into meaningful information using Excel Pivot and Charts can take this course. The program will provide learners with in-demand knowledge and skills, allowing them to take advantage of outstanding employment opportunities. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The Learn Excel With Pivot Tables, Pivot Charts, Slicers, and Timelines course provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as: Data Analyst Accountants Financial Analyst Learn Excel With Pivot Tables, Pivot Charts, Slicers, and Timelines Getting started with your Pivot Table 00:04:00 Drill Down 00:01:00 Managing the Field List 00:02:00 Changing the Calculation type with Value Field Settings 00:06:00 Growing your Pivot Table with Multiple Fields 00:04:00 Formatting the Pivot Table 00:05:00 Sorting and Filtering the Pivot Table 00:03:00 Creating a Dashboard with Slicers, Timelines and Pivot Charts 00:09:00 Reporting by day, month, qtr, or year within the Pivot Table 00:04:00 Refreshing the Pivot Data with new data 00:03:00 Adding your own calculations into the Pivot Table 00:03:00 The power of the Filter Section in the Pivot Table 00:04:00 PowerQuery 00:12:00 PowerPivot 00:21:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Embark on a journey to uncover the labyrinthine world of digital financial security with the 'Hacked Credit and Debit Card Recovery Course'. Navigate through the depths of the web, from understanding the diverse range of websites to delving deep into the dark corridors of the internet, equipping yourself with invaluable cyber intelligence. Through this course, you'll decode various threat perceptions, familiarise yourself with card fraud intricacies, and master the art of information recovery - all tailored to ensure your digital financial transactions remain impervious to threats. Learning Outcomes Understand the fundamentals of cyber threats and their impact on digital financial transactions. Differentiate between various website types and their susceptibility to cyber-attacks. Analyse threat actors and their modus operandi in the cyber realm. Gain insights into the deep and dark web and the tools necessary for information recovery. Acquire proficiency in information handling procedures to maintain digital financial security. Why buy this Hacked Credit and Debit Card Recovery Course? 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 Hacked Credit and Debit Card Recovery Course 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 Hacked Credit and Debit Card Recovery Course for? Individuals keen on enhancing their understanding of digital financial security. Banking and finance professionals looking to fortify their defence mechanisms. Cybersecurity enthusiasts aiming to delve into card fraud detection and prevention. Internet users wanting to safeguard their online financial transactions. Tech-savvy individuals eager to explore deep and dark web intelligence. Prerequisites This Hacked Credit and Debit Card Recovery Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Hacked Credit and Debit Card Recovery Course 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 Cyber Security Analyst: £35,000 - £55,000 Fraud Detection Analyst: £30,000 - £50,000 Dark Web Researcher: £40,000 - £65,000 Information Security Officer: £45,000 - £70,000 Threat Intelligence Specialist: £50,000 - £75,000 Financial Security Consultant: £55,000 - £80,000 Course Curriculum Unit 01: Introduction Introduction & Objective 00:01:00 Unit 02: Types of Website Types of Website 00:01:00 Surface Web 00:01:00 Deep Web 00:01:00 Dark Web 00:03:00 2016 - 2017 Profit Comparison from 5000 00:01:00 Intelligence Agency Web 00:01:00 Quantum Computers 00:01:00 Polymeric Falcighol Derivation 00:01:00 Graphical representation 00:01:00 Unit 03: Threat Perception Threat Perception 00:01:00 Threat Actor 00:01:00 Threat Actor-Compared to a Hacker Or Attacker 00:01:00 Is the Dark Net Market gone? 00:03:00 Unit 04: Card Fraud Card Fraud 00:04:00 Card-Not-Present Fraud (CNP) 00:02:00 Unit 05: Threat Ninja Threat Ninja 00:01:00 Threat Ninja Architecture 00:03:00 Adaptive Assessment 00:01:00 Secure Coat Approach 00:01:00 Secure Coat's Value Proposition 00:02:00 Challenge 00:01:00 Unit 06: Threat Actor Analysis Threat Actor Analysis 00:00:00 Kuchinoni - ATM Theft 00:01:00 Insider Threats 00:01:00 Unit 07: Cyber Security Monitoring Cyber Security Monitoring 00:01:00 Protect Your Company via DDWM 00:01:00 Unit 08: Threat Life Cycle Threat Life Cycle 00:06:00 Unit 09: Information Leakage Points Information Leakage Points 00:04:00 Unit 10: Valuable Information Valuable Information 00:09:00 Unit 11: Area of Search Area of Search 00:01:00 Sell Cards at Social Media, Messenger, etc. Groups 00:01:00 Unit 12: Deep & Dark Web Intelligence and Information Recovery Deep & Dark Web Intelligence and Information Recovery 00:01:00 Unit 13: Banking Fraud Types Banking Fraud Types 00:01:00 Card Fraud- Nilson Report 00:01:00 U.S. Card Fraud Losses 00:01:00 Card Fraud Statistics 00:05:00 Unit 14: Threat Ninja Tool Secure Coat Threat Ninja Portal 00:01:00 Threat Ninja Demo 00:05:00 Unit 15: Information Handing Procedures Information Handling Procedures 00:01:00 Card Discard Life Cycle 00:02:00 Unit 16: Course Wrap up Congratulations and Course Summary 00:03:00 Thank you! 00:01:00 Unit 17: Bonus Rise in the price of the Crypto Coin 00:06:00 Assignment Assignment - Hacked Credit and Debit Card Recovery Course 00:00:00

Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

The significance of mathematics has never been more paramount in our world. Our expertly curated GCSE Mathematics course, a key requisite qualification, opens doors to college and university, vocational training, apprenticeships, and a plethora of employment opportunities. Math, an age-old discipline, not only supports many other subjects but is also an independent intellectual field, serving as the lingo of science and engineering. Our specially crafted course is engineered to ensure your success in achieving the qualification you seek. You have the flexibility to choose between Foundation or Higher level study. You're also allowed to switch levels in the initial phases of the course, after receiving feedback from your assignments and tutor. This ensures that by the time you register for exams, you've opted for the level that best suits your capability. Make no mistake, GCSEs are qualifications that truly matter. Advantages you stand to gain: A freshly conceived course, drafted to the most recent specification with dynamic, captivating content Fast-track option available for the 2022 exams Guaranteed exam venue within our network of partnered exam centres Unlimited tutor support – we assist you in drafting a study plan and provide continuous support Exam pass guarantee - should you not succeed the first time, we’ll support you up to the next exam Mathematics, akin to its core counterpart English, forms a fundamental building block for a multitude of educational pursuits and daily life. Excelling in maths fosters understanding in subjects like sciences, and even humanities such as Geography. It’s more than just number-crunching; it encompasses statistics, geometry, and an array of other critical skills. So, plunge into our comprehensive GCSE Mathematics course and chart your path towards the future. About the awarding body Awarding body: AQA Our course code: X801 Qualification code: 8300 AQA qualifications are globally recognized, taught in 30 countries worldwide, highly esteemed by employers and universities, and pave the way for learners to advance to their next life stage. AQA qualifications cater to various abilities and encompass GCSEs, IGCSEs and A-levels. ⏱ Study Hours: Allocate between 120 and 150 hours for study time, along with additional time for assignment completion. 👩‍🏫 Study Method: Our course is presented via our online learning platform for a dynamic and engaging learning experience. If you prefer, you can print the learning materials. The resources are in various media, including videos, quizzes, and interactive activities. 📆 Course Duration: After enrolment, you have a span of two years to complete your study and exams. Your unlimited tutor support will continue throughout this duration. 📋 Assessment: Enrol now for exams from Summer 2022. Our Maths GCSE is a tiered exam, meaning you choose the level of your exam study: Foundation tier: Grades 1 to 5, with grade 5 as the highest attainable and equivalent to grade C. Higher tier: Grades 4 to 9, with grade 9 as the highest attainable and equivalent to grade A*. Official exams comprise three GCSE standard written exams, each of 1 hour 30 minutes and each accounting for 33.3% of marks. You also have a guaranteed exam space in one of our exam centres across the country. Assignments: You will complete one introductory assignment and 10 other assignments throughout your course. While these do not contribute to your final grade, they provide a chance to submit work to your tutor for marking and feedback, helping you assess your progress. There is no coursework to complete. All exams must be taken in the same session. 👩‍🎓 Course Outcomes: Upon successful course completion, you will receive a GCSE in Mathematics, issued by AQA. We've chosen this syllabus specifically for its suitability to distance learning. ℹ️ Additional Information: Difficulty - Level 2 Entry Requirements - There are no formal prerequisites for this course, however, we recommend an intermediate ability to read and write in English. Course Content: Numbers: This module covers all aspects of integer-based maths, from basic operations to the use of standard units of mass, length, time, and more, laying a solid foundation for subsequent units. Algebra: This unit demystifies everything from basic algebraic notation to solving complex quadratic equations, by the end of which you'll master topics like quadratics and exponential functions. Ratios and Proportions: This segment sharpens your skills in comparing numerical data, a key skill in several sciences and engineering disciplines. Topics covered include value considerations and comparative skills. Geometry and Measures: This module extends beyond studying shapes, covering properties of angles, rotations, concepts of area and volume, and more. By the end of this unit, you'll find angles a cinch. Probability: This unit lets you delve into the intricacies of probability, covering various graphical representations like tree diagrams. Statistics: A crucial element in numerous subjects like Science and Geography, this unit involves skills like inferring information about populations based on statistical analysis and understanding primary or secondary data sets.

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics