39946 Courses

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 5 Days 30 CPD hours This course is intended for System architects and system administrators Overview By the end of the course, you should be able to meet the following objectives: Introduce troubleshooting principles and procedures Use command-line interfaces, log files, and the vSphere Client to diagnose and resolve problems in the vSphere environment Explain the purpose of common vSphere log files Identify networking issues based on reported symptoms Validate and troubleshoot the reported networking issue Identify the root cause of networking issue Implement the appropriate resolution to recover from networking problems Analyze storage failure scenarios using a logical troubleshooting methodology identify the root cause of storage failure Apply the appropriate resolution to resolve storage failure problems Troubleshoot vSphere cluster failure scenarios Analyze possible vSphere cluster failure causes Diagnose common VMware vSphere High Availability problems and provide solutions Identify and validate VMware ESXiTM host and VMware vCenter problems Analyze failure scenarios of ESXi host and vCenter problems Select the correct resolution for the failure of ESXi host and vCenter problems Troubleshoot virtual machine problems, including migration problems, snapshot problems, and connection problems Troubleshoot performance problems with vSphere components This five-day training course provides you with the knowledge, skills, and abilities to achieve competence in troubleshooting the VMware vSphere© 8 environment. This course increases your skill level and competence in using the command-line interface, VMware vSphere© Client?, log files, and other tools to analyze and solve problems. Course Introduction Introductions and course logistics Course objectives Introduction to Troubleshooting Define the scope of troubleshooting Use a structured approach to solve configuration and operational problems Apply troubleshooting methodology to logically diagnose faults and improve troubleshooting efficiency Troubleshooting Tools Discuss the various methods to run commands Discuss the various ways to access ESXi Shell Use commands to view, configure, and manage your vSphere components Use the vSphere CLI Use ESXCLI commands from the vSphere CLI Use Data Center CLI commands Identify the best tool for command-line interface troubleshooting Identify important log files for troubleshooting vCenter Server and ESXi Describe the benefits and capabilities of VMware SkylineTM Explain how VMware Skyline works Describe VMware SkylineTM Health Describe VMware Skyline AdvisorTM Troubleshooting Virtual Networking Analyze and troubleshoot standard switch problems Analyze and troubleshoot virtual machine connectivity problems Analyze and troubleshoot management network problems Analyze and troubleshoot distributed switch problems Troubleshooting Storage Discuss the vSphere storage architecture Identify the possible causes of problems in the various types of datastores Analyze the common storage connectivity and configuration problems Discuss the possible storage problems causes Solve the storage connectivity problems, correct misconfigurations, and restore LUN visibility Review vSphere storage architecture and functionality necessary to troubleshoot storage problems Use ESXi and Linux commands to troubleshoot storage problems Analyze log file entries to identify the root cause of storage problems Investigate ESXi storage issues Troubleshoot VM snapshots Troubleshoot storage performance problems Review multipathing Identify the common causes of missing paths, including PDL and APD conditions Solve the missing path problems between hosts and storage devices Troubleshooting vSphere Clusters Identify and troubleshoot vSphere HA problems Analyze and solve vSphere vMotion problems Diagnose and troubleshoot common vSphere DRS problems Troubleshooting Virtual Machines Discuss virtual machine files and disk content IDs Identify, analyze, and solve virtual machine snapshot problems Troubleshoot virtual machine power-on problems Identify possible causes and troubleshoot virtual machine connection state problems Diagnose and recover from VMware Tools installation failures Troubleshooting vCenter Server and ESXi Analyze and solve vCenter Server service problems Diagnose and troubleshoot vCenter Server database problems Use vCenter Server Appliance shell and the Bash shell to identify and solve problems Identify and troubleshoot ESXi host problems

Duration 5 Days 30 CPD hours This course is intended for Change Managers: Responsible for documentation, approval and change processes System Landscape Architects: Responsible for the design of the transport landscape topology System Administrators: Responsible for executing transports Development Managers: Responsible for performing development changes Application Manager: Responsible for approving and performing changes in an application Support Manager and members of the customer's SAP competence center: Responsible for Reporting and Diagnostics capabilities Partners and System Integrators Overview This course will prepare you to: Describe the concept and methods of E2E Change Control Management. Leverage the SAP Solution Manager 7.2 as application platform for E2E Change Control Management. In this course you will learn how change control management coordinates changes that are introduced into a software landscape so that the changes do not conflict with each other and how to make sure the changes are executed without disrupting ongoing business. This results in improved quality of the software landscape, higher availability of IT solutions, and lower total cost of ownership. Also important, change control management ensures that the changes introduced remain transparent, traceable and are made available for reporting and change analysis. Becoming adept at change control management requires skill in the efficient use of standardized methods and procedures. In this ?how to use? training, SAP imparts best-in-class knowledge of solution operations. The End-to-End Change Control Management course introduces participants to what change control management is and the standard tools used to accomplish it, tools provided by SAP Solution Manager. Introduction to E2E Change Control Management Explain the scope of End-to-End Change Control Management Explain the role of SAP Solution Manager to manage changes in your solution landscape Enhanced Change and Transport System Explain how the Enhanced Change and Transport System (CTS+) works Understand the basic concepts of Enterprise Portal and how it is supported by CTS+ Describe the best practices for the setup and usage of CTS+ in different scenarios Configuration Validation Understand the concepts and architecture of E2E Change Diagnostics Find current configuration information with the Change Reporting tool Find recent changes in the solution landscape with the E2E Change Analysis tool Compare multiple systems with the Configuration Validation tool Create targets, use operators and run validation reports Know how to use predefined reports in the report directory Transport and Execution Analysis Service and Transport and Execution Analysis Service for Projects Know how to run and use this self-check services within SAP Solution Manager Understand how to interpret the software change management KPIïs that are collected for your landscape Software Change Strategy Understand the limitations of a three-system landscape Understand the benefits of bundling changes in cycles and synchronized releases Transport Management with SAP Solution Manager Understand the change control landscape concept for transport management in SAP Solution Manager 7.2 Understand the usage of critical objects, cross system object locking and downgrade protection Know how to use retrofit in a dual landscape Understand the features of cCTS, which can be used for Quality Gate Management and Change Request Management parallel to CTS. Quality Gate Management Explain the concept of Solution Transports and Track Synchronization Setup and use Quality Gate Scenario as a central Transport Management Tool Create and release transport requests centrally in SAP Solution Manager for ABAP and Non-ABAP environments Know how to work within the Quality Gate Scenario Change Request Management Understand the different use cases for Change Request Management Describe the various elements of Change Request Management as part of SAP Solution Manager Understand SAP?s best practices for transport management which are implemented in Change Request Management Know how to work with Change Request Management Release Management Learn how to manage Release Management with SAP Solution Manager Understand how to manage the successful deployment of all related changes into the productive environment.

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Want a new direction for your career? Think Accountancy, according to statistics, the average salary for Accountants is £50,000, it is the sector where the employability rate is higher than any other sector. Whether you're a school leaver, already employed or simply looking for a career change a career in accountancy could be a real option for you. What is AAT? The AAT is an internationally recognised accounting qualification and over 100,000 people are currently benefiting from gaining an AAT qualification and full AAT membership. Gaining the qualification will help you support yourself throughout your accountancy career. AAT Accounting Courses Overview: First of all, the AAT qualification consists of four progressive qualification levels (1, 2, 3 & 4) which will cover the key areas of Financial Accounting, Management Accounting, Taxation, Audit and Report Writing. Although you can start from Level 1, you may start from Level 2 if you have basic math and numeracy skills. In order to complete the full AAT Accounting qualification and gain full membership of the AAT, you will need to complete Level 3 and Level 4. Level 2 is recommended as an entry-level if you have no experience or knowledge of accounting and bookkeeping. The AAT qualification for accounting is broken down into three levels: AAT Level 2 Foundation Certificate in Accounting (5 Papers/Subjects) AAT Level 3 Advanced Diploma in Accounting (6 Papers/Subjects) Finally AAT Level 4 Professional Diploma in Accounting (6 Papers/Subjects) Hence, the AAT Accounting Qualification gives you practical, internationally recognised finance and accountancy skills that can open doors for you in many industries across the world. Finally, AAT offers a range of benefits for student members (including study support, career advice to help find the perfect job and exclusive discounts), as well as a route to progress into chartered accountancy. Moreover, if you choose to further your studies with any of the leading chartered accountancy professional bodies like ACCA, CIMA, CIPFA etc. your AAT qualification could make you eligible for generous exemptions. A Certificate of Attendance. A newly qualified AAT member can expect to earn an average of £21,600. Moreover, the AAT member will have been earning throughout their training and will have avoided student debt. Accounting technicians work at all levels of finance and accounting, depending on the level of their career. Some accounting technicians work as accounts clerks, others go on to become managing directors or finance directors of well-known companies. Some go to work as a self-employed accountant as AAT allows the student to become Accredited.

Duration 5 Days 30 CPD hours This course is intended for Experienced Programmers and Systems Administrators. Overview Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices. Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to: ? Create working Python scripts following best practices ? Use python data types appropriately ? Read and write files with both text and binary data ? Search and replace text with regular expressions ? Get familiar with the standard library and its work-saving modules ? Use lesser-known but powerful Python data types ? Create 'real-world', professional Python applications ? Work with dates, times, and calendars ? Know when to use collections such as lists, dictionaries, and sets ? Understand Pythonic features such as comprehensions and iterators ? Write robust code using exception handling An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features. An Overview of Python What is python? 1 -- An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Built-in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings The standard library The sys module Launching external programs Math functions Random numbers The string module Reading CSV data Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the file system Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations 17 ? Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network services Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Parsing command-line options Detecting the current platform Trapping signals Implementing logging Python Timeline Advantages/Disadvantages of Python Getting help with pydoc

Duration 2 Days 12 CPD hours This course is intended for It is appropriate for Managers, Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, managers; supervisors, team leaders, and process operators. Overview Describe business process improvement (BPI) business drivers.Plan, manage and close requirements for a Business Process Improvement project Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Apply a methodology to business process improvement projects. This 2-day course aims at introducing its attendees to the core values, principles, and practices of Business Process Improvement. Introduction - A Business Process Improvement (BPI) Overview Why are we here today? What is BPI? Benefits of BPI Specific challenges/obstacles and successes Process improvement examples: Industry specific examples Famous debacles to avoid and successes to emulate Your role in helping to identify problems Overview of the Joiner 7-Step Method What is the Joiner 7-Step Method? Walkthrough of the Joiner 7-Step Method Template: Introduce and review Process Improvement Template Case Study Exercise: Read and discuss introduction to the Case Study Step #1: Initiate the Project Types of business problems typically encountered at insurance companies and banks How to recognize a business-related problem Identifying the gaps (delta between current and future states) Ownership of the project and the business problem Defining measurable success criteria Case Study Exercise: Complete the Problem Statement section (Step #1) of the template Step #2: Define Current Situation What are symptoms of a problem? Looking for symptoms of the problem Performing Stakeholder Analysis Technique: View a RACI Matrix Defining the impacts caused by the problem Technique: Business Process Modeling (As-Is) Understand how to draw an As-Is Business Process Model Case Study Exercise: Complete the Define Current Situation section (Step #2) of the template Step #3: Identify Root Causes What are root causes? Performing Root Cause Analysis Technique: Fishbone Diagram using the cafeteria example Case Study Exercise: Discuss a Fishbone Diagram Technique: Pareto Chart (discuss and show example) Case Study Exercise: Complete the Identify Root Causes section (Step #3) of the template Step #4: Develop Solutions Identifying options for problem resolution Avoid jumping to conclusions Technique: Brainstorming Case Study Exercise: Conduct a Brainstorming Session Recognizing pros and cons for each option Technique: Kempner-Tregoe (?Must-Have? vs. ?Nice-to-Have?) Case Study Exercise: Determine best solution using a ?simple? Kempner-Tregoe model Case Study Exercise: Complete the Develop Solutions section (Step #4) of the template Step #5: Define Measurable Results Prototyping the solution Technique: Business Process Modeling (To-Be) Measuring results against the success criteria (Step #1) Case Study Exercise: Review changes to an As-Is Business Process Model Case Study Exercise: Complete the Define Measurable Results section (Step #5) of the template Step #6: Standardize Process Defining how the process will be documented Plan and understand organizational readiness Discuss how employees are empowered to identify and act upon their ideas Identifying follow-up needs (i.e., training) for the staff that will be impacted Technique: Communication Plan Case Study Exercise: Complete the Standardize Process section (Step #6) of the template Step #7: Determine Future Plans Monitoring the process for Continuous Process Improvement (The ?Plan-Do-Check-Act? Cycle) Understand how to sustain the improvements made by the Joiner 7-Step Method Technique: PDCA form Case Study Exercise: Complete the Determine Future Plans section (Step #7) of the template Going Forward with a Plan of Action Identifying process problems in your organization Individual Exercise: Name three (3) possible areas for improvement Prioritize and define the next steps Individual Exercise: Using a new template complete Step 2 & Step 3 for one possible area for improvement you have identified

Duration 2 Days 12 CPD hours This course is intended for Data Protection Officers Data Protection Managers Auditors Legal Compliance Officers Security Manager Information Managers Anyone involved with data protection processes and programs Overview It will show the world that students know privacy laws and regulations and how to apply them, and that students know how to secure your place in the information economy. When students earn a CIPP credential, it means they've gained a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. The Certified Information Privacy Professional/United States (CIPP/US) program, developed by the International Association of Privacy Professionals (IAPP) - the world?s largest comprehensive global information privacy community and resource, was the first professional certification ever to be offered in information privacy. The CIPP/US credential demonstrates a strong foundation in U.S. privacy laws and regulations and understanding of the legal requirements for the responsible transfer of sensitive personal data to/from the U.S., the EU and other jurisdictions.This course will provide you with a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. Introduction to privacy Modern history of privacy Introduction to personal information Overview of data protection roles Summary of modern privacy frameworks Structure of U.S. law Structure and sources of U.S. law and relevant terms Governmental bodies having privacy and information security authority General Data Protection Regulation overview (GDPR) High-level overview of the GDPR Significance of the GDPR to U.S. organizations Roles and responsibilities outlined in the law California Consumer Privacy Act of 2018 (CCPA) High-level overview of the newly passed California Consumer Privacy Act of 2018 Scope Consumer rights Business obligations Enforcement Enforcement of U.S. privacy and security laws Distinguishing between criminal and civil liability Comparing federal and state authority Theories of legal liability Enforcement powers and responsibilities of government bodies, such as the FTC and state attorneys general Information management from a U.S. perspective Developing a privacy program Role of privacy professionals and accountability Employee training User preferences Managing vendors Data classification Federal versus state authority Differences between federal and state authority Preemption Healthcare Privacy laws in healthcare Major components of HIPAA Development of HITECH Privacy protections mandated by other significant healthcare laws Financial privacy Goals of financial privacy laws Key concepts of FCRA, FACTA and GLBA Red Flags Rule, Dodd-Frank and consumer protection laws Education Privacy rights and protections under FERPA Recent amendments provided by PPRA and NCLBA Telecommunications and marketing Rules and regulations of telecommunications entities Laws that govern marketing Addressing privacy in the digital advertising Law enforcement and privacy Privacy laws on intercepting communication Telecommunications industry and law enforcement Laws ensuring rights to financial privacy National security and privacy Rules and regulations on intercepting communication Evolution of the law Collaboration of government agencies and private companies to improve cybersecurity Civil litigation and privacy Privacy issues related to litigation Electronic discovery, redaction and protective orders U.S. discovery rules versus foreign laws Legal overview of workplace privacy Federal and state laws regulating and protecting employee privacy Federal laws prohibiting discrimination Privacy before, during and after employment Lifecycle of employee privacy Background screening Employee monitoring Investigating misconduct and termination Antidiscrimination laws ?Bring your own device? policies State data security laws State laws impacting data security Social Security number use regulation Laws governing data destruction Data breach notification laws Scope of state data breach notification law Nine elements of state data breach notification laws Major differences in state laws

Duration 2 Days 12 CPD hours This course is intended for A prior understanding of EU Data Protection legislation is recommended. Candidates are typically management professionals and decision-makers who already have responsibility for data protection compliance within their organisation.Co-Requisite Subjects Candidates should have a good understanding of their own organisation?s data management activities through the life cycle from initial acquisition, through the various areas of processing and usage, to eventual removal or destruction. Overview To equip the learner with a foundational understanding of the principles of the General Data Protection Regulation (GDPR) and to provide constructive suggestions on implementing compliant processes. The social, historical and legal background leading to the General Data Protection Regulation (GDPR) The scope and global context of the GDPR The key concepts within the GDPR The definition of all key words and phrases relating to this Data Protection regulation Principle One: The criteria governing fair, open and transparent processing of personal data Principle Two: Purpose Limitation, the challenge of limiting the processing within the context of specified and lawful purposes Principle Three: Minimisation of processing, and ensuring that only that data is processed which is necessary to achieve the purpose. Principle Two: Purpose Limitation, the challenge of limiting the processing within the context of specified and lawful purposes Principle Three: Minimisation of processing, and ensuring that only that data is processed which is necessary to achieve the purpose. Principle Four: Ensuring that any personal data held by the organisation is kept accurate and current, and that any processing of such data is appropriate Principle Five: Management and storage of personal data in a manner that meets regulatory obligations, while minimising the time that the individual remains identifiable Principle Six: The criteria governing safe, secure and confidential processing of personal data in order to protect its integrity Principle Seven: The key roles, responsibilities and accountabilities of those involved in Data Management within an organisation Establishment within a single Member State Joint Controllers Privacy by Design and by Default Nominated Representatives Third-party Contracts and shared liability Logging of data management processes Data Breach Notification obligations Privacy Impact Assessments Overseas transfer of personal data L2.8 The Data Subject Rights, and their implications for the Data Controller and the Data Processor L2.8.1 The ?right to be forgotten? L2.8.2 The right to restriction of processing L2.8.3 The right to object to certain processing L2.8.4 The right to have inaccurate data amended or erased L2.8.5 The right to data portability L2.8.6 The right of access to one?s personal data L2.8.7 Rights in relation to automated decision-making and profiling The role of the Data Protection Officer (DPO) The role of the Data Protection Officer (DPO) Criteria for designating a DPO Tasks of the DPO Position of the DPO within the organisation The role of the Supervisory Authority within the Member State The Lead Supervisory Authority and independence Investigative, corrective and advisory powers Independence of the Supervisory Authority Collaboration with other Supervisory Authorities Codes of Conduct and Certification The role, powers and tasks of the European Data Protection Board (EDPB) The remedies, liabilities and penalties available under the GDPR Right to raise a complaint Right to representation Right to effective judicial remedy Right to compensation and liability Administrative fines of up to ?10m or 2% of GAT Administrative fines of up to ?20m or 4% of GAT Provisions for specific processing situations Freedom of Expression Processing of official documents Processing of National Identification Numbers Processing regarding employment Processing for archiving purposes Processing under obligations of official secrecy Processing of data by religious organisations Preparing for implementation of the GDPR Review of data management policies and procedures Review of data assets and security structures Training and Awareness-raising Data management governance structures Embedding Privacy By Design and Default Codes of Conduct and Certification against standards Breach detection and notification procedures Review of third-party agreements, contracts