30152 Courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for This in an introductory-level course geared for QA, Test team members and others who want to use the Python testing framework PyTest to implement code testing strategies. Attendees should have prior basic Python scripting experience. Students should have some familiarity with tools to be used in this course: PyCharm, Jupyter Notebook and basic GIT. Overview Working within in a hands-on learning environment students will learn to: Become proficient with pytest from day one by solving real-world testing problems Use pytest to write tests more efficiently Scale from simple to complex and functional testing Write and run simple and complex tests Organize tests in fles and directories Find out how to be more productive on the command line Markers and how to skip, xfail and parametrize tests Explore fxtures and techniques to use them effectively, such as tmpdir, pytestconfg, and monkeypatch Convert unittest suites to pytest using little-known techniques The pytest framework is simple to use but powerful enough to cover complex testing integration scenarios. PyTest is considered by many to be the true Pythonic approach to testing in Python. Geared for QA, Test team members and others who want to use the Python testing framework PyTest to implement code testing strategies, Test Automation with Python is a hands-on, two day Python testing course that provides students with the skills required to get started with PyTest right away. Participnats will learn how to get the most out of it in their daily workflow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. Students will also learn how to use pytest in existing unittestbased test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily. Python Refresher Python Overview Python Basics Python Lab Introducing PyTest Why Spend time writing test UnitTest Module Why PyTest? Introductory Lab Writing and Running Test Installing PyTest Writing and Running Tests Organizing files and packages Command Line options Configure pytest.ini Install and Config Lab Markers and Parameters Mark Basics Built-in marks Parameterization Markers and Parameters Lab Fixtures Introduction to Fixtures Sharing fixtures with conftest.py files Scopes Autouse Parameterizing fixtures Using marks from fixtures Built-in fixtures Best Practices Fixtures Lab Fixtures Lab 2 Plugins Finding and installing plugins Overview of plugins Plugin Lab From UnitTest to PyTest Use PyTest as a Test Runner Convert asserts with unitest2pytest Handling setup/teardown Managing test hierarchies Refactoring test utilities Migration strategies Additional course details: Nexus Humans Test Automation with Python (TTPS4832) 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 Test Automation with Python (TTPS4832) 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 2 Days 12 CPD hours This course is intended for Data Modelers Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Dynamic Cubes Define and differentiate Dynamic Cubes Dynamic Cubes characteristics Examine Dynamic Cube requirements Examine Dynamic Cube components Examine high level architecture IBM Cognos Dynamic Query Review Dimensional Data Structures Dynamic Cubes caching Create & Design a Dynamic Cube Explore the IBM Cognos Cube Designer Review the cube development process Examine the Automatic Cube Generation Manual development overview Create dimensions Model the cube Best practice for effective modeling Deploy & Configure a Dynamic Cube Deploy a cube Explore the Estimate Hardware Requirements Identify cube management tasks Examine Query Service administration Explore Dynamic Cube properties Schedule cube actions Use the DCAdmin comment line tool Advanced Dynamic Cube Modelling Examine advanced modeling concepts Explore modeling caveats Calculated measures and members Model Relative Time Explore the Current Period property Define period aggregation rules for measures Advanced Features of Cube Designer Examine multilingual support Examine ragged hierarchies and padding members Define Parent-Child Dimensions Refresh Metadata Import Framework Manager packages Filter measures and dimensions Optimize Performance with Aggregates Identify aggregates and aggregate tables In-memory aggregates Use Aggregate Advisor to identify aggregates User defined in-memory aggregates Optimize In-Memory Aggregates automatically Aggregate Advisor recommendations Monitor Dynamic Cube performance Model aggregates (automatically vs manually) Use Slicers to define aggregation partitions Define Security Overview of Dynamic Cube security Identify security filters The Security process - Three steps Examine security scope Identify scope rules Identify roles Capabilities and access permissions Cube security deep dive Model a Virtual Cube Explore virtual cubes Create the virtual cube Explore virtual cube objects Examine virtual measures and calculated members Currency conversion using virtual cubes Security on virtual cubes Introduction to IBM Cognos Analytics Define IBM Cognos Analytics Redefined Business Intelligence Self-service Navigate to content in IBM Cognos Analytics Interact with the user interface Model data with IBM Cognos Analytics IBM Cognos Analytics components Create reports Perform self-service with analysis and Dashboards IBM Cognos Analytics architecture (high level) IBM Cognos Analytics security Package / data source relationship Create Data modules Upload files Additional course details: Nexus Humans B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 2 Days 12 CPD hours This course is intended for Security architects System designers Network administrators Operations engineers Network managers, network or security technicians, and security engineers and managers responsible for web security Cisco integrators and partners Overview After taking this course, you should be able to: Describe Cisco WSA Deploy proxy services Utilize authentication Describe decryption policies to control HTTPS traffic Understand differentiated traffic access policies and identification profiles Enforce acceptable use control settings Defend against malware Describe data security and data loss prevention Perform administration and troubleshooting This course shows you how to implement, use, and maintain Cisco© Web Security Appliance (WSA), powered by Cisco Talos, to provide advanced protection for business email and control against web security threats. Through a combination of expert instruction and hands-on practice, you?ll learn how to deploy proxy services, use authentication, implement policies to control HTTPS traffic and access, implement use control settings and policies, use the solution?s anti-malware features, implement data security and data loss prevention, perform administration of Cisco WSA solution, and more.This course helps you prepare to take the exam, Securing the Web with Cisco Web Security Appliance (300-725 SWSA). Describing Cisco WSA Technology Use Case Cisco WSA Solution Cisco WSA Features Cisco WSA Architecture Proxy Service Integrated Layer 4 Traffic Monitor Data Loss Prevention Cisco Cognitive Intelligence Management Tools Cisco Advanced Web Security Reporting (AWSR) and Third-Party Integration Cisco Content Security Management Appliance (SMA) Deploying Proxy Services Explicit Forward Mode vs. Transparent Mode Transparent Mode Traffic Redirection Web Cache Control Protocol Web Cache Communication Protocol (WCCP) Upstream and Downstream Flow Proxy Bypass Proxy Caching Proxy Auto-Config (PAC) Files FTP Proxy Socket Secure (SOCKS) Proxy Proxy Access Log and HTTP Headers Customizing Error Notifications with End User Notification (EUN) Pages Utilizing Authentication Authentication Protocols Authentication Realms Tracking User Credentials Explicit (Forward) and Transparent Proxy Mode Bypassing Authentication with Problematic Agents Reporting and Authentication Re-Authentication FTP Proxy Authentication Troubleshooting Joining Domains and Test Authentication Integration with Cisco Identity Services Engine (ISE) Creating Decryption Policies to Control HTTPS Traffic Transport Layer Security (TLS)/Secure Sockets Layer (SSL) Inspection Overview Certificate Overview Overview of HTTPS Decryption Policies Activating HTTPS Proxy Function Access Control List (ACL) Tags for HTTPS Inspection Access Log Examples Understanding Differentiated Traffic Access Policies and Identification Profiles Overview of Access Policies Access Policy Groups Overview of Identification Profiles Identification Profiles and Authentication Access Policy and Identification Profiles Processing Order Other Policy Types Access Log Examples ACL Decision Tags and Policy Groups Enforcing Time-Based and Traffic Volume Acceptable Use Policies, and End User Notifications Defending Against Malware Web Reputation Filters Anti-Malware Scanning Scanning Outbound Traffic Anti-Malware and Reputation in Policies File Reputation Filtering and File Analysis Cisco Advanced Malware Protection File Reputation and Analysis Features Integration with Cisco Cognitive Intelligence Enforcing Acceptable Use Control Settings Controlling Web Usage URL Filtering URL Category Solutions Dynamic Content Analysis Engine Web Application Visibility and Control Enforcing Media Bandwidth Limits Software as a Service (SaaS) Access Control Filtering Adult Content Data Security and Data Loss Prevention Data Security Cisco Data Security Solution Data Security Policy Definitions Data Security Logs Performing Administration and Troubleshooting Monitor the Cisco Web Security Appliance Cisco WSA Reports Monitoring System Activity Through Logs System Administration Tasks Troubleshooting Command Line Interface

Duration 2 Days 12 CPD hours This course is intended for There is no specific prerequisite for the CDRP© course. However, participants who have at least three years' experience in a data centre and/or IT infrastructures will be best suited. Overview After completion of the course, the participant will be able to: 1. Understand the different standards and methodologies for risk management and assessment 2. Establish the required project team for risk management 3. Perform the risk assessment, identifying current threats, vulnerabilities and the potential impact based on customised threat catalogues 4. Report on the current risk level of the data centre both quantitative and qualitative 5. Anticipate and minimise potential financial impacts 6. Understand the options for handling risk 7. Continuously monitor and review the status of risk present in the data centre 8. Reduce the frequency and magnitude of incidents 9. Detect and respond to events when they occur 10. Meet regulatory and compliance requirements 11. Support certification processes such as ISO/IEC 27001 12. Support overall corporate and IT governance Introduction to Risk Management Risk management concepts Senior management and risk Enterprise Risk Management (ERM) Benefits of risk management Data Centre Risk and Impact Risk in facility, power, cooling, fire suppression, infrastructure and IT services Impact of data centre downtime Main causes of downtime Cost factors in downtime Standards, Guidelines and Methodologies ISO/IEC 27001:2013, ISO/IEC 27005:2011, ISO/IEC 27002:2013 NIST SP 800-30 ISO/IEC 31000:2009 SS507:2008 ANSI/TIA-942 Other methodologies (CRAMM, EBIOS, OCTAVE, etc.) Risk Management Definitions Asset Availability/Confidentiality/Integrity Control Information processing facility Information security Policy Risk Risk analysis/Risk assessment/Risk evaluation/ Risk treatment Threat/Vulnerability Types of risk Risk Assessment Software The need for software Automation Considerations Risk Management Process The risk management process Establishing the context Identification Analysis Evaluation Treatment Communication and consultation Monitoring and review Project Approach Project management principles Project management methods Scope Time Cost Cost estimate methods Context Establishment General considerations Risk evaluation, impact and acceptance criteria Severity rating of impact Occurrence rating of probability Scope and boundaries Scope constraints Roles & responsibilities Training, awareness and competence Risk Assessment - Identification The risk assessment process Identification of assets Identification of threats Identification of existing controls Identification of vulnerabilities Identification of consequences Hands-on exercise: Identification of assets, threats, existing controls, vulnerabilities and consequences Risk Assessment - Analysis and Evaluation Risk estimation Risk estimation methodologies Assessment of consequences Assessment of incident likelihood Level of risk estimation Risk evaluation Hands-on exercise: Assessment of consequences, probability and estimating level of risk Risk Treatment The risk treatment process steps Risk Treatment Plan (RTP) Risk modification Risk retention Risk avoidance Risk sharing Constraints in risk modification Control categories Control examples Cost-benefit analysis Control implementation Residual risk Communication Effective communication of risk management activities Benefits and concerns of communication Risk Monitoring and Review Ongoing monitoring and review Criteria for review Risk scenarios Risk assessment approach Data centre site selection Data centre facility Cloud computing UPS scenarios Force majeure Organisational shortcomings Human failure Technical failure Deliberate acts Exam: Certified Data Centre Risk Professional Actual course outline may vary depending on offering center. Contact your sales representative for more information.

These friendly informal sessions started in lockdown 1.0 and are a chance for some informal networking with a supportive group of lawyers, at various stages of their career from student to law firm Managing Director!

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

The main topics to be covered in this course are about everyday activities, family, friends, life events, remembering and forgetting, characteristics of people, holidays and more; Students practise their speaking, writing, listening and reading skills in and out of class with their teachers and classmates using their books and applications; The course is based on Ελληνικά Α and Κλικ στα Ελληνικά. In addition, there is a wide range of language material designed by the Greek LOL Teachers. All lessons are supported by educational applications to help students enrich their vocabulary and practise their Greek with fun and interactive exercises, videos and games.

Our Fast Track Level 3 training course is tailor-made for immigration advisors and legal professionals seeking a targeted, time-efficient course focusing on essential OISC Level 3 syllabus fundamentals. This course is 1 day. Our fast track OISC Level 3 one day course is specifically designed for those interested in progressing to the next OISC level. This course focuses on 3 main areas which are introduced at Level 3: Preparation and conduct of appeals, Bail applications to the First-tier Tribunal and Pre Action-Protocol Letters. Throughout this training, you will acquire a comprehensive understanding of the intricate structures and frameworks governing UK immigration law at an advanced level. Our expert instructors will provide in-depth insights, practical knowledge, and invaluable tips to equip you with the necessary skills and confidence to handle complex immigration cases.   Course joining links, materials and instructions are sent out 24hours before the course starts. Why Study with Immigration Advice Service? Immigration Advice Service has been providing professional immigration services for over 10 years in the public, private and corporate sectors. Our OISC Level 3 (Fast Track) preparation course is thoughtfully crafted to equip participants with a comprehensive understanding of the essential knowledge needed at OISC level 3. Our fully qualified and OISC regulated trainer will guide you through the process and ensure you are competent with elements covered within the course. Course Content: This fast track course is specifically designed to covers the following key areas. Introduction: The OISC Level 3 assessment The preparation and conduct of appeals Bail applications to the First-tier Tribunal Pre Action Protocol Letters Prior to judicial review Looking for a more in-depth training session? Why not check out our standard Level 3 training course which recaps and builds on from knowledge learnt at OISC Level 2 and delivered over a 2-day period.

A free sampler for the Motorcycle Skills - Improve your Riding in Eight Weeks online e-course from Survival Skills Rider Training