125 Courses delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Duration 4 Days 24 CPD hours This course is intended for The audience for this course is data professionals managing data and databases who want to learn about administering the data platform technologies that are available on Microsoft Azure. This course is also valuable for data architects and application developers who need to understand what technologies are available for the data platform with Azure and how to work with those technologies through applications. This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases. Prerequisites In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses: AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Prepare to maintain SQL databases on Azure Describe Microsoft Intelligent Data Platform roles Understand SQL Server in an Azure virtual machine Design Azure SQL Database for cloud-native applications Explore Azure SQL Database Managed Instance 2 - Deploy IaaS solutions with Azure SQL Explain IaaS options to deploy SQL Server in Azure Understand hybrid scenarios Explore performance and security Explain high availability and disaster recovery options 3 - Deploy PaaS solutions with Azure SQL Explain PaaS options for deploying SQL Server in Azure Explore single SQL database Deploy SQL database elastic pool Understand SQL database hyperscale Examine SQL managed instance Describe SQL Edge 4 - Evaluate strategies for migrating to Azure SQL Understand compatibility level Understand Azure preview features Describe Azure database migration options 5 - Migrate SQL workloads to Azure SQL databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL Database offline Migrate SQL Server to Azure SQL Database online Load and move data to Azure SQL Database 6 - Migrate SQL workloads to Azure Managed Instances Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed Instance Load and Move data to SQL Database Managed Instance 7 - Configure database authentication and authorization Describe Active Directory and Azure Active Directory Describe authentication and identities Describe Security Principals Describe database and object permissions Identify authentication and authorization failures 8 - Protect data in-transit and at rest Explore Transparent Data Encryption Configure server and database firewall rules Explain object encryption and secure enclaves Enable encrypted connections Describe SQL injection Understand Azure Key Vault 9 - Implement compliance controls for sensitive data Explore data classification Explore server and database audit Implement Dynamic Data Masking Implement Row Level security Understand Microsoft Defender for SQL Explore Azure SQL Database Ledger Implement Azure Purview 10 - Describe performance monitoring Describe performance monitoring tools Describe critical performance metrics Establish baseline metrics Explore extended events Describe Azure SQL Insights Explore Query Performance Insight 11 - Configure SQL Server resources for optimal performance Explain how to optimize Azure storage for SQL Server virtual machines Describe virtual machine resizing Optimize database storage Control SQL Server resources 12 - Configure databases for optimal performance Explore database maintenance checks Describe database scoped configuration options Describe automatic tuning Describe intelligent query processing 13 - Explore query performance optimization Understand query plans Explain estimated and actual query plans Describe dynamic management views and functions Explore Query Store Identify problematic query plans Describe blocking and locking 14 - Evaluate performance improvements Describe wait statistics Tune and maintain indexes Understand query hints 15 - Explore performance-based design Describe normalization Choose appropriate data types Design indexes 16 - Automate deployment of database resources Describe deployment models in Azure Automate deployment by using Azure Resource Manager templates and Bicep Automate deployment by using PowerShell Automate deployment by using Azure CLI 17 - Create and manage SQL Agent jobs Create a SQL Server maintenance plan Describe task status notifications 18 - Manage Azure PaaS tasks using automation Explore Elastic jobs Understand Azure Automation Build an automation runbook Automate database workflows by using Logic Apps Monitor automated tasks 19 - Describe high availability and disaster recovery strategies Describe recovery time objective and recovery point objective Explore high availability and disaster recovery options Describe Azure high availability and disaster recovery features for Azure Virtual Machines Describe high availability and disaster recovery options for PaaS deployments Explore an IaaS high availability and disaster recovery solution Describe hybrid solutions 20 - Explore IaaS and PaaS solutions for high availability and disaster recovery Describe failover clusters in Windows Server Configure Always-on availability groups Describe temporal tables in Azure SQL Database Describe active geo-replication for Azure SQL Database Explore auto-failover groups for Azure SQL Database and Azure SQL Managed Instance 21 - Back up and restore databases Back up and restore SQL Server running on Azure virtual machines Back up a SQL Server virtual machine Back up and restore a database using Azure SQL Database Additional course details: Nexus Humans DP-300T00: Administering Microsoft Azure SQL Solutions 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 DP-300T00: Administering Microsoft Azure SQL Solutions 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 4 Days 24 CPD hours This course is intended for The information protection administrator translates an organization?s risk and compliance requirements into technical implementation. They are responsible for implementing and managing solutions for content classification, data loss prevention (DLP), information protection, data lifecycle management, records management, privacy, risk, and compliance. They also work with other roles that are responsible for governance, data, and security to evaluate and develop policies to address an organization's risk reduction and compliance goals. This role assists workload administrators, business application owners, human resources departments, and legal stakeholders to implement technology solutions that support the necessary policies and controls. Learn how to protect information in your Microsoft 365 deployment. This course focuses on data lifecycle management and information protection and compliance within your organization. The course covers implementation of data loss prevention policies, sensitive information types, sensitivity labels, data retention policies, Microsoft Purview Message Encryption, audit, eDiscovery, and insider risk among other related topics. The course helps learners prepare for the Microsoft Information Protection Administrator exam (SC-400). Prerequisites Foundational knowledge of Microsoft security and compliance technologies. Basic knowledge of information protection concepts. Understanding of cloud computing concepts. Understanding of Microsoft 365 products and services. 1 - Introduction to information protection and data lifecycle management in Microsoft Purview Know your data Protect your data Prevent data loss Govern your data 2 - Classify data for protection and governance Data classification overview Classify data using sensitive information types Classify data using trainable classifiers Review sensitive information and label usage Explore labeled and sensitive content Understand activities related to your data 3 - Create and manage sensitive information types Compare built-in versus custom sensitive information types Create and manage custom sensitive information types Describe custom sensitive information types with exact data match Implement document fingerprinting Create keyword dictionary 4 - Understand Microsoft 365 encryption Learn how Microsoft 365 data is encrypted at rest Understand service encryption in Microsoft Purview Explore customer key management using Customer Key Learn how data is encrypted in-transit 5 - Deploy Microsoft Purview Message Encryption Implement Microsoft Purview Message Encryption Implement Microsoft Purview Advanced Message Encryption Use Microsoft Purview Message Encryption templates in mail flow rules 6 - Protect information in Microsoft Purview Information protection overview Configure sensitivity labels Configure sensitivity label policies Configure auto-labeling policies Manage, monitor, and remediate information protection 7 - Apply and manage sensitivity labels Apply sensitivity labels to Microsoft Teams, Microsoft 365 groups, and SharePoint sites Plan on-premises labeling Configure on-premises labeling for the Unified Labeling Scanner Apply protections and restrictions to email and files Monitor label performance using label analytics 8 - Prevent data loss in Microsoft Purview Data loss prevention overview Identify content to protect Define policy settings for your DLP policy Test and create your DLP policy Prepare Endpoint DLP Manage DLP alerts in the Microsoft Purview compliance portal View data loss prevention reports Implement the Microsoft Purview Extension 9 - Configure DLP policies for Microsoft Defender for Cloud Apps and Power Platform Configure data loss prevention policies for Power Platform Integrate data loss prevention in Microsoft Defender for Cloud Apps Configure policies in Microsoft Defender for Cloud Apps Manage data loss prevention violations in Microsoft Defender for Cloud Apps 10 - Manage data loss prevention policies and reports in Microsoft 365 Configure data loss prevention for policy precedence Implement data loss prevention policies in test mode Explain data loss prevention reporting capabilities Manage permissions for data loss prevention reports Manage and respond to data loss prevention policy violations 11 - Manage the data lifecycle in Microsoft Purview Data Lifecycle Management overview Configure retention policies Configure retention labels Configure manual retention label policies Configure auto-apply retention label policies Import data for Data Lifecycle Management Manage, monitor, and remediate Data Lifecycle Management 12 - Manage data retention in Microsoft 365 workloads Explain retention in Exchange Online Explain retention in SharePoint Online and OneDrive Explain retention in Microsoft Yammer Activate archive mailboxes in Microsoft Exchange Apply mailbox holds in Microsoft Exchange Recover content in Microsoft Exchange 13 - Manage records in Microsoft Purview Records management overview Import a file plan Configure retention labels Configure event driven retention Manage, monitor, and remediate records 14 - Explore compliance in Microsoft 365 Plan for security and compliance in Microsoft 365 Plan your beginning compliance tasks in Microsoft Purview Manage your compliance requirements with Compliance Manager Examine the Compliance Manager dashboard Analyze the Microsoft Compliance score 15 - Search for content in the Microsoft Purview compliance portal Explore Microsoft Purview eDiscovery solutions Create a content search View the search results and statistics Export the search results and search report Configure search permissions filtering Search for and delete email messages 16 - Manage Microsoft Purview eDiscovery (Standard) Explore Microsoft Purview eDiscovery solutions Implement Microsoft Purview eDiscovery (Standard) Create eDiscovery holds Search for content in a case Export content from a case Close, reopen, and delete a case 17 - Manage Microsoft Purview eDiscovery (Premium) Explore Microsoft Purview eDiscovery (Premium) Implement Microsoft Purview eDiscovery (Premium) Create and manage an eDiscovery (Premium) case Manage custodians and non-custodial data sources Analyze case content 18 - Manage Microsoft Purview Audit (Standard) Explore Microsoft Purview Audit solutions Implement Microsoft Purview Audit (Standard) Search the audit log Export, configure, and view audit log records Use audit log searching to investigate common support issues 19 - Prepare Microsoft Purview Communication Compliance Plan for communication compliance Identify and resolve communication compliance workflow Case study--Configure an offensive language policy Investigate and remediate communication compliance alerts 20 - Manage insider risk in Microsoft Purview Insider risk management overview Create and manage insider risk policies Investigate insider risk alerts Take action on insider risk alerts through cases Manage insider risk management forensic evidence Create insider risk management notice templates 21 - Implement Microsoft Purview Information Barriers Explore Microsoft Purview Information Barriers Configure information barriers in Microsoft Purview Examine information barriers in Microsoft Teams Examine information barriers in OneDrive Examine information barriers in SharePoint 22 - Manage regulatory and privacy requirements with Microsoft Priva Create and manage risk management policies Investigate and remediate risk management alerts Create rights requests Manage data estimate and retrieval for rights requests Review data from rights requests Get reports from rights requests 23 - Implement privileged access management Case study--Implementing privileged access management 24 - Manage Customer Lockbox Manage Customer Lockbox requests

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Become a Mental Health First Aid Champion Mental Health First Aid (MHFA) is an internationally recognised training course, which teaches people how to spot the signs and symptoms of mental ill health and to provide help on a first aid basis. This course is designed for people who want to promote and positively affect attitudes on mental health in the workplace.

This masterclass will enable you to gain comprehensive awareness and be a supportive guide for Key Staff through fully understanding recent changes and developments in one of the fastest growing categories of safeguarding concerns.

Some 60% of injuries at work are caused by lifting heavy objects. This powerful, practical programme is designed to help stop any of your staff from becoming the next statistic. 1 Introduction and objectives 2 Overview of Health and Safety Legislation and HSE Injury Statistics Health and Safety at Work Act 1974 Management of Health and Safety at Work Regulations (MHSWR) 1992 MHSWR 1999 specific duties to risk assess Manual Handling Operations Regulations (MHOR) 1992 Breakdown of injury statistics and costs of poor manual handling 3 The musculoskeletal system explained Prevention and ill-health Ergonomics RSI The spine in detail 4 Risk assessment General principles The TILE method Employees' duties Workplace scenarios

This course raises awareness of mental health. It covers:  What mental health is and how to challenge stigma A basic knowledge of some common mental health issues An introduction to looking after your own mental health and maintaining wellbeing Confidence to support someone in distress or who may be experiencing a mental health issue Format This is a half day course deliver via Zoom Learning takes place through a mix of presentations, group discussions and workshop activities We limit numbers to 25 people per course so that the instructor can keep people safe and supported while they learn Takeaways Everyone who completes the course gets: A certificate of attendance to say you are Mental Health Aware A manual to refer to whenever you need it A workbook including a helpful toolkit to support your own mental health Course Structure What is mental health? Mental Health Continuum Factors which affect mental health Stigma Stress and stress management Spotting signs of distress Mental health conditions:DepressionAnxiety disordersPsychosisEating disordersSuicideSelf-harm Recovery Take 10 Together - starting a supportive conversation Supporting mental health in the workplace Useful statistics Helpful resources

About this Virtual Instructor Led Training (VILT) This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system. The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way. With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed. Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery. Training Objectives Upon completion of this VILT course, participants will be able to: Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues. Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices. Understand and analyze energy performance from main renewable energy systems. Get equipped on the insights into forecasting models for solar energy. Predict solar generation from weather forecasts using machine learning. Explore operational aspects of a complex power system with variability from both the supply & demand sides. Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation. Target Audience Engineers, planners and operations professionals from the following organizations: Energy aggregators who would like to understand the system operations of renewable energy power plants Renewable energy power system operator Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Course Objectives The goal of this course is to provide you with the knowledge required to use more advanced functions and formulas and work with various tools to analyse and present data in spreadsheets, such as sorting, filtering, applying conditional formatting and charting the data. ' Customer Feedback Really useful and engaging course. Learnt a lot that will be very beneficial in my job. Trainer was great. Kelly Moreley - TACT Very happy with the course. Worked as a good refresher from what I knew already and enhanced my knowledge further in formulas + vlookup and shortcut keys. Jenny Price - Acer 1 year email support service Take a look at the consistent excellent feedback from our corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering classroom, one to one, tailored and bespoke courses. Tailored In company training: You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in. Recap on Excel formulas and calculations Overview of formulas in Excel Relative, Absolute and Mixed cell references Group editing worksheets Autofill and Flash Fill Changing Excel’s environment Options Changing the default number of sheets Creating an Autofill Custom List Adding tools to the Quick Access Toolbar Mastering Excel Tables Introducing Excel Tables Formatting a Table Creating Calculated Columns Using Slicers to filter your data Using Totals to get statistics out of your data Removing duplicates Converting Tables back to normal Ranges Using names Ranges In Excel formulas As a way of navigating through the workbook Advanced Formulas Simple IF examples Using IF to check if a cell is blank Nested IFs VLOOKUP HLOOKUP Text Functions Date Functions Conditional formatting Apply Conditional Formatting Customising Conditional Formatting Using Icons in Conditional Formatting Using Formulas to conditionally format cells Linking spreadsheets and workbooks Making a reference to another worksheet Making a reference to another workbook Editing links Troubleshooting links Analysing databases Quick analysis Sorting a database Apply filters to a database Advance filter Sorting and Filtering by Conditional Formats Charts Analyse trends in data using Sparklines Creating charts from start to finish Exploring the different Chart Types Apply Chart Styles Formatting Chart Elements Filtering Charts by Series or Categories Adding a Trendline to a Chart Create a Chart Template Attaching security to a spreadsheet and workbook Protect Cells Protect Structure of worksheets Protect a Workbook by adding passwords Introduction to Pivot Tables What are Pivot Tables? Using recommended pivot tables to analyse your data Who is this course for? Who is this course for? For those who want to explore in more detail formulas and functions, data analysis and data presentation. Requirements Requirements Preferably, delegates would have attended the Excel Introduction course. Career path Career path Excel know-how can instantly increase your job prospects as well as your salary. 80 percent of job openings require spreadsheet and word-processing software skills