1673 Database courses

This online delivered course consists of over 4 1/2 hours of presentation, case studies and acupuncture point database including needling videos. A great way to refine your clinical reasoning and treatments for patients with chronic pain. Also can be used as a good refresher, as it recaps the mechanisms behind acupuncture succinctly. See the website for more information

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

This course starts with the basics then moves seamlessly to an intermediate level. It includes a comprehensive yet balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to use the online Power BI service. It looks at authoring tools that enables you to connect to and transform data from a variety of sources, allowing you to produce dynamic reports using a library of visualisations. Once you have those reports, the course looks at the seamless process of sharing those with your colleagues by publishing to the online Power BI service. The aim of this course is to provide a strong understanding of the Power BI analysis process, by working with real-world examples that will equip you with the necessary skills to start applying your knowledge straight away. 1 Getting started The Power BI process Launching Power BI Desktop The four views of Power BI Dashboard visuals 2 Connecting to files Connect to data sources Connect to an Excel file Connect to a CSV file Connect to a database Import vs. DirectQuery Connect to a web source Create a data table 3 Transforming data The process of cleaning data Column data types Remove rows with filters Add a custom column Append data to a table Fix error issues Basic maths operations 4 Build a data model Table relationships Manage table relationships 5 Merge queries Table join kinds Merging tables 6 Create report visualisations Creating map visuals Formatting maps Creating chart visuals Formatting chart Tables, matrixes, and cards Control formatting with themes Filter reports with slicers Reports for mobile devices Custom online visuals Export report data to Excel 7 The power query editor Fill data up and down Split columns by delimiter Add conditional columns Merging columns 8 The M formula Creating M functions Create an IF function Create a query group 9 Pivot and unpivot tables Pivot tables in the query editor Pivot and append tables Pivot but don't summarise Unpivot tables Append mismatched headers 10 Data modelling revisited Data model relationships Mark a calendar as a date table 11 Introduction to calculated columns New columns vs. measures Creating a new column calculation The SWITCH function 12 Introduction to DAX measures Common measure categories The SUM measure Adding measures to visuals COUNTROWS and DISINCTCOUNT functions DAX rules 13 The CALCULATE measure The syntax of CALCULATE Things of note about CALCULATE 14 The SUMX measure The SUMX measure X iterator functions Anatomy of SUMX 15 Introduction to time intelligence Importance of a calendar table A special lookup table The TOTALYTD measure Change year end in TOTALYTD 16 Hierarchy, groups and formatting Create a hierarchy to drill data Compare data in groups Add conditional formatting 17 Share reports on the web Publish to the BI online service Get quick insights Upload reports from BI service Exporting report data What is Q&A? Sharing your reports 18 Apply your learning Post training recap lesson

Unlock the power of data with our 'Sales Analysis in Excel' course. Dive into e-commerce sales analysis and craft insightful sales analysis reports. Discover how to manipulate sales data, forecast trends, and automate workbook functionality. Elevate your career with advanced Excel skills! Learning Outcomes of Sales Analysis in Excel: Master data manipulation techniques for e-commerce sales analysis. Create comprehensive sales reports with Excel's advanced functions. Visualize data effectively using charts, PivotTables, and PivotCharts. Forecast future trends and make data-driven decisions. Automate repetitive tasks to boost efficiency and productivity. Why buy this Sales Analysis in Excel? 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 Sales Analysis in Excel 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 course for? Business analysts seeking to enhance their data analysis skills. Sales professionals aiming to leverage Excel for deeper insights. Aspiring data scientists interested in e-commerce sales data. Students and graduates looking to gain a competitive edge. Entrepreneurs striving to optimize their sales strategies. Prerequisites This Sales Analysis in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Sales Analysis in Excel 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 Data Analyst: £25,000 - £40,000 Per Annum Business Analyst: £30,000 - £50,000 Per Annum Sales Analyst: £25,000 - £45,000 Per Annum Financial Analyst: £30,000 - £55,000 Per Annum Market Research Analyst: £25,000 - £40,000 Per Annum Excel Specialist: £22,000 - £35,000 Per Annum Course Curriculum Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Welcome to the Course 00:03:00 Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00

Unleash the power of data with our Data Analysis in Excel course, where you'll journey through the realm of spreadsheet analysis and uncover the secrets hidden within your data. In today's data-driven world, the ability to navigate, interpret, and extract insights from data is a coveted skill. Whether you're a professional looking to enhance your analytical capabilities or a student aiming to excel in data-driven fields, this course empowers you to harness Excel's full potential for data analysis. From modifying worksheets to forecasting future trends, you'll master the art of data manipulation, visualization, and analysis with confidence and precision. Learning Outcomes Master the art of modifying Excel worksheets to suit your data analysis needs. Discover advanced data analysis techniques, including working with lists and lookup functions. Create compelling data visualizations using charts, PivotTables, and PivotCharts. Effortlessly manage multiple worksheets and workbooks, making data organization a breeze. Apply data forecasting techniques and automate workbook functionality, saving time and boosting productivity. Why choose this Data Analysis in Excel 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 Data Analysis in Excel course for? Professionals seeking to enhance their data analysis skills. Students preparing for careers in data-driven industries. Analysts, researchers, and data enthusiasts eager to upskill. Business professionals looking to make data-driven decisions. Anyone interested in harnessing Excel for powerful data analysis. Career path Data Analyst: £25,000 - £47,000 Business Analyst: £26,000 - £50,000 Financial Analyst: £26,000 - £56,000 Market Research Analyst: £24,000 - £40,000 Operations Analyst: £23,000 - £48,000 Business Intelligence Analyst: £27,000 - £56,000 Prerequisites This Data Analysis in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Analysis in Excel 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 Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Recommended Materials Workbook - Data Analysis in Excel 00:00:00 Assignment Assignment - Data Analysis in Excel 00:00:00

Duration 5 Days 30 CPD hours This course is intended for System installersSystem integratorsSystem administratorsNetwork administratorsSolution designers Overview After taking this course, you should be able to:Describe the Cisco IOS XR software architecture, high availability components, and scalability featuresPerform basic configurations on a Cisco IOS XR routerDescribe Cisco IOS XR software operationsDescribe the configuration file systemPerform Cisco IOS XR software installationsConfigure AAA servicesConfigure NTPConfigure Simple Network Management Protocol (SNMP), telemetry, and loggingConfigure routing protocolsMonitor processesUse error messages and core dumps he Introduction to Cisco IOS XR (IOSXR100) v2.0 course introduces you to the features and functions of the Cisco© Internetwork Operating System (Cisco IOS©) XR Software operating system. You learn the fundamental concepts on which the operating system is based and Cisco IOS XR basic operations, system administration, and troubleshooting. Cisco IOS XR Software Overview Platform Overview Cisco IOS XR Architecture Cisco IOS XR High Availability Cisco IOS XR Software Configuration Basics Cisco IOS XR Configuration Operations Cisco IOS XR Initial Configuration Reviewing the Configuration Cisco IOS XR Software Operations Examining Configuration Operations Examining Configuration Rollback and Recovery Configuration File System Overview Examining the Binary Configuration Examining the Commit Database Examining the ASCII Configuration Examining the Nonvolatile Generation (NVgen) Files Verifying Cisco Fabric Services (CFS) Integrity Cisco IOS XR Software Installation Software Package Basics Installing Software Packages AAA Security AAA Fundamentals Task-Based Security Configuring a User Security Policy Authentication with Remote Servers Configuring Router to AAA Server Communication Configuring Authentication Terminal Access Controller Access-Control System Plus (TACACS+) Command Authorization Configuring Accounting AAA Troubleshooting Network Time Synchronization Network Time Protocol SNMP, Telemetry, and Logging Examining SNMP Examining Telemetry Examining Logging Basic Routing Configuration Configuring Intermediate System to Intermediate System (IS-IS) Configuring Open Shortest Path First (OSPF) Configuring Border Gateway Protocol (BGP) Configuring Routing Protocol for LLN (RPL) Policy Packet Filtering Access Control Lists Unicast Reverse Path Forwarding Management Plane Protection Monitoring Process Examining Processes and Threads Process Crashes Commands for Debugging Processes Restartability of Processes Process Monitoring Identifying Memory Problems Memory Depletion Core Dumps Core Dump Fundamentals Using Core Dump Information Additional course details: Nexus Humans Cisco Introduction to Cisco IOS XR v2.0 (IOSXR100) 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 Cisco Introduction to Cisco IOS XR v2.0 (IOSXR100) 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.

Duration 5 Days 30 CPD hours This course is intended for This course benefits individuals responsible for implementing, monitoring, and troubleshooting Layer 3 components of a service provider's network. Overview Describe the various OSPF link-state advertisement (LSA) types. Explain the flooding of LSAs in an OSPF network. Describe the shortest-path-first (SPF) algorithm. List key differences between OSPFv2 and OSPFv3. Describe OSPF area types and operations. Configure various OSPF area types. Summarize and restrict routes. Identify some scenarios in a service provider network that can be solved using routing policy or specific configuration options. Use routing policy and specific configuration options to implement solutions for various scenarios. Describe how to troubleshoot OSPF. Explain the concepts and operation of IS-IS. Describe various IS-IS link-state protocol data unit (LSP) types. List IS-IS adjacency rules and troubleshoot common adjacency issues. Configure and monitor IS-IS. Display and interpret the link-state database (LSDB). Perform advanced IS-IS configuration options. Implement IS-IS routing policy. Explain the default operation in multiarea IS-IS. Describe IS-IS address summarization methods. Configure and monitor a multiarea IS-IS network. Describe how to troubleshoot IS-IS. Describe basic BGP operation. List common BGP attributes. Explain the route selection process for BGP. Describe how to alter the route selection process. Configure some advanced options for BGP peers. Describe various BGP attributes in detail and explain the operation of those attributes. Manipulate BGP attributes using routing policy. Explain the causes for route instability. Describe the effect of damping on BGP routing. Explain the default behavior of damping on links. Control damping using routing policy. View damped routes using command-line interface (CLI) commands. Describe the operation of BGP route reflection. Configure a route reflector. Describe the operation of a BGP confederation. Configure confederations. Describe peering relationships in a confederation. Describe how to troubleshoot BGP. Describe how to troubleshoot routing policy. This five-day course is designed to provide students with detailed coverage of OSPF, IS-IS, BGP, and routing policy. Course Outline Course Introduction OSPF OSPFv2 Review Link-State Advertisements Protocol Operations OSPF Authentication OSPF Areas Review of OSPF Areas Stub Area Operation Stub Area Configuration NSSA Operation NSSA Configuration Route Summarization OSPF Case Studies and Solutions Virtual Links OSPF Multiarea Adjacencies External Reachability Troubleshooting OSPF Troubleshooting OSPF IS-IS Overview of IS-IS IS-IS PDUs Neighbors and Adjacencies Configuring and Monitoring IS-IS Advanced IS-IS Operations and Configuration Options IS-IS Operations IS-IS Configuration Options IS-IS Routing Policy Multilevel IS-IS Networks Level 1 and Level 2 Operations Multilevel Configuration Troubleshooting IS-IS Troubleshooting IS-IS BGP Review of BGP BGP Operations BGP Path Selection Options Configuration Options BGP Attributes and Policy?Part 1 BGP Policy Next Hop Origin and MED AS Path BGP Attributes and Policy?Part 2 Local Preference Communities Route Reflection and Confederations Route Reflection Operation Configuration and Routing Knowledge BGP Confederations BGP Route Damping Route Flap and Damping Overview Route Damping Parameters Configuring and Monitoring Route Damping Troubleshooting BGP Troubleshooting BGP Troubleshooting Policy Troubleshooting Policy

Duration 5 Days 30 CPD hours This course is intended for Enterprise network engineers System engineers System administrators Network administrators Overview After taking this course, you should be able to: Configure classic Enhanced Interior Gateway Routing Protocol (EIGRP) and named EIGRP for IPv4 and IPv6 Optimize classic EIGRP and named EIGRP for IPv4 and IPv6 Troubleshoot classic EIGRP and named EIGRP for IPv4 and IPv6 Configure Open Shortest Path First (OSPF)v2 and OSPFv3 in IPv4 and IPv6 environments Optimize OSPFv2 and OSPFv3 behavior Troubleshoot OSPFv2 for IPv4 and OSPFv3 for IPv4 and IPv6 Implement route redistribution using filtering mechanisms Troubleshoot redistribution Implement path control using Policy-Based Routing (PBR) and IP service level agreement (SLA) Configure Multiprotocol-Border Gateway Protocol (MP-BGP) in IPv4 and IPv6 environments Optimize MP-BGP in IPv4 and IPv6 environments Troubleshoot MP-BGP for IPv4 and IPv6 Describe the features of Multiprotocol Label Switching (MPLS) Describe the major architectural components of an MPLS VPN Identify the routing and packet forwarding functionalities for MPLS VPNs Explain how packets are forwarded in an MPLS VPN environment Implement Cisco Internetwork Operating System (IOS) Dynamic Multipoint VPNs (DMVPNs) Implement Dynamic Host Configuration Protocol (DHCP) Describe the tools available to secure the IPV6 first hop Troubleshoot Cisco router security features Troubleshoot infrastructure security and services The Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 gives you the knowledge you need to install, configure, operate, and troubleshoot an enterprise network. This course covers advanced routing and infrastructure technologies, expanding on the topics covered in the Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 course. This course may earn a Credly Badge Course Outline Implementing EIGRP Optimizing EIGRP Troubleshooting EIGRP Implementing OSPF Optimizing OSPF Troubleshooting OSPF Implementing Internal Border Gateway Protocol (IBGP) Optimizing BGP Implementing MP-BGP Troubleshooting BGP Configuring Redistribution Troubleshooting Redistribution Implementing Path Control Exploring MPLS Introducing MPLS L3 VPN Architecture Introducing MPLS L3 VPN Routing Configuring Virtual Routing and Forwarding (VRF)-Lite Implementing DMVPN Implementing DHCP Troubleshooting DHCP Introducing IPv6 First Hop Security Securing Cisco Routers Troubleshooting Infrastructure Security and Services Lab Outline Configure EIGRP Using Classic Mode and Named Mode for IPv4 and IPv6 Verify the EIGRP Topology Table Configure EIGRP Stub Routing, Summarization, and Default Routing Configure EIGRP Load Balancing and Authentication LAB: Troubleshoot EIGRP Issues Configure OSPFv3 for IPv4 and IPv6 Verify the Link-State Database Configure OSPF Stub Areas and Summarization Configure OSPF Authentication Troubleshoot OSPF Implement Routing Protocol Redistribution Manipulate Redistribution Manipulate Redistribution Using Route Maps Troubleshoot Redistribution Issues Implement PBR Configure IBGP and External Border Gateway Protocol (EBGP) Implement BGP Path Selection Configure BGP Advanced Features Configure BGP Route Reflectors Configure MP-BGP for IPv4 and IPv6 Troubleshoot BGP Issues Implement PBR Configure Routing with VRF-Lite Implement Cisco IOS DMVPN Obtain IPv6 Addresses Dynamically Troubleshoot DHCPv4 and DHCPv6 Issues Troubleshoot IPv4 and IPv6 Access Control List (ACL) Issues Configure and Verify Control Plane Policing Configure and Verify Unicast Reverse Path Forwarding (uRPF) Troubleshoot Network Management Protocol Issues: Lab 1 Troubleshoot Network Management Protocol Issues: Lab 2

This course is designed for project managers and planners who need to plan and manage projects without resources in Oracle Primavera P6 PPM. You will learn how to navigate the user interface, create project plans, define activities, and manage project timelines without relying on resource constraints.

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