81 Analyst courses in Bradford

The Real Estate Investor course primarily focuses on financial modelling and commercial considerations in the real estate industry across various sectors, geographies, and project types.

PYTHON BOOTCAMP: This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts . You will be fully fluent and confident as a Python data analyst, with full understanding of Python Programming. From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards The course is a practical, instructor-lead program.

Data Visualization Courses London. In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational visualizations This course is ideal for managers and data analysts who need to make business decisions based on data.

This course is intended to the most ambitious modellers in the property industry who would like to be fully proficient in building complex real estate models.

The Real Estate Analyst course has been taught non-stop to global real estate firms over the last 25 years, and is without doubt the core financial modelling training in your career portfolio. Whether you have an upcoming financial modelling test for a new job or an APC exam, the Real Estate Analyst course is the choice for you.

Are you looking to enter the dynamic world of real estate? Our course is designed to equip you with the knowledge and tools you need to communicate effectively with real estate professionals and develop key skills in real estate investment strategy and analytics. At the end of the course, you'll be able to read and interpret real estate market reports, and have a firm grasp of how iconic buildings, cities, and companies fit into the overall picture of the real estate sector. On this course, you will… Become familiar with the players, structure, general terminology and overall needs of Real Estate. Learn what is Real Estate and why it is different from other asset classes Get to grips with the overall size and structure of the UK Real Estate Market Learn and analyse the links between the different parts of the property market Understand who works in the Real Estate Market, their qualifications and their job descriptions Recognise how and when to use basic real estate concepts: Rent, Value, Yield, Risk and Return, etc… Learn how to read a real estate market report Understand how current affairs, politics and economics affects Real Estate Investment Use household names and iconic companies, cities and buildings to help consolidate your appreciation of this exciting sector Who will benefit from this course: Graduates or undergraduates studying economics, finance. Professionals working in Marketing or Accounting teams within Real Estate firms. APC students. Anyone interested in Real Estate. School leavers/A-Level Students looking to gain an understanding of Real Estate. Non cognate students who wish to transfer into Real Estate/Finance careers. Course Outline Module 1: What is and why buy Real Estate? The property Market The Size and Structure of the UK property market The impact of Real Estate in the Economy Module 2: The Real Estate Market System The Space Market The Asset Market The Development Market Module 3: How to value Real Estate An Introduction to Financial Mathematics The difference between Price, Value and Worth Property Yield Conventional Valuation Methods Module 4: How to read a Real Estate Market Report Property Market Indicators: Stock Indicators Property Market Indicators: Investment Indicators Module 5: Who works in Real Estate? The build Environment by Cobalt Recruitment Rea; Estate Agents Examples of Real Estate Market Agents CVs Real Estate Network

Duration 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. Introduction to end-to-end analytics using Microsoft Fabric Explore end-to-end analytics with Microsoft Fabric Data teams and Microsoft Fabric Enable and use Microsoft Fabric Knowledge Check Get started with lakehouses in Microsoft Fabric Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Exercise - Create and ingest data with a Microsoft Fabric Lakehouse Use Apache Spark in Microsoft Fabric Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook Exercise - Analyze data with Apache Spark Work with Delta Lake Tables in Microsoft Fabric Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data Exercise - Use delta tables in Apache Spark Ingest Data with DataFlows Gen2 in Microsoft Fabric Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

Duration 5 Days 30 CPD hours This course is intended for This course is designed primarily for cybersecurity practitioners who perform job functions related to protecting information systems by ensuring their availability, integrity, authentication, confidentiality, and non-repudiation. This course focuses on the knowledge, ability, and skills necessary to provide for the defense of those information systems in a cybersecurity context, including protection, detection, analysis, investigation, and response processes. In addition, the course ensures that all members of an IT team?everyone from help desk staff to the Chief Information Officer?understand their role in these security processes. Overview In this course, you will assess and respond to security threats and operate a systems and network security analysis platform. You will: - Assess information security risk in computing and network environments. - Analyze reconnaissance threats to computing and network environments. - Analyze attacks on computing and network environments. - Analyze post-attack techniques on computing and network environments. - Implement a vulnerability management program. - Collect cybersecurity intelligence. - Analyze data collected from security and event logs. - Perform active analysis on assets and networks. - Respond to cybersecurity incidents. - Investigate cybersecurity incidents. - Address security issues with the organization's technology architecture. The course introduces tools and tactics to manage cybersecurity risks, identify various types of common threats, evaluate the organization's security, collect and analyze cybersecurity intelligence, and handle incidents as they occur. 1 - ASSESSING INFORMATION SECURITY RISK Identify the Importance of Risk Management Assess Risk Mitigate Risk Integrate Documentation into Risk Management 2 - ANALYZING RECONNAISSANCE THREATS TO COMPUTING AND NETWORK ENVIRONMENTS Assess the Impact of Reconnaissance Incidents Assess the Impact of Social Engineering 3 - ANALYZING ATTACKS ON COMPUTING AND NETWORK ENVIRONMENTS Assess the Impact of System Hacking Attacks Assess the Impact of Web-Based Attacks Assess the Impact of Malware Assess the Impact of Hijacking and Impersonation Attacks Assess the Impact of DoS Incidents Assess the Impact of Threats to Mobile Security Assess the Impact of Threats to Cloud Security 4 - ANALYZING POST-ATTACK TECHNIQUES Assess Command and Control Techniques Assess Persistence Techniques Assess Lateral Movement and Pivoting Techniques Assess Data Exfiltration Techniques Assess Anti-Forensics Techniques 5 - MANAGING VULNERABILITIES IN THE ORGANIZATION Implement a Vulnerability Management Plan Assess Common Vulnerabilities Conduct Vulnerability Scans Conduct Penetration Tests on Network Assets 6 - COLLECTING CYBERSECURITY INTELLIGENCE Deploy a Security Intelligence Collection and Analysis Platform Collect Data from Network-Based Intelligence Sources Collect Data from Host-Based Intelligence Sources 7 - ANALYZING LOG DATA Use Common Tools to Analyze Logs Use SIEM Tools for Analysis 8 - PERFORMING ACTIVE ASSET AND NETWORK ANALYSIS Analyze Incidents with Windows-Based Tools Analyze Incidents with Linux-Based Tools Analyze Malware Analyze Indicators of Compromise 9 - RESPONDING TO CYBERSECURITY INCIDENTS Deploy an Incident Handling and Response Architecture Mitigate Incidents Prepare for Forensic Investigation as a CSIRT 10 - INVESTIGATING CYBERSECURITY INCIDENTS Apply a Forensic Investigation Plan Securely Collect and Analyze Electronic Evidence Follow Up on the Results of an Investigation 11 - ADDRESSING SECURITY ARCHITECTURE ISSUES Remediate Identity and Access Management Issues Implement Security During the SDLC Additional course details: Nexus Humans CompTIA Cybersecurity Analyst Certification (CySA Plus) (Exam CS0-003) 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 CompTIA Cybersecurity Analyst Certification (CySA Plus) (Exam CS0-003) 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 3 Days 18 CPD hours This course is intended for The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Prerequisites Understanding core data concepts. Knowledge of working with relational data in the cloud. Knowledge of working with non-relational data in the cloud. Knowledge of data analysis and visualization concepts. DP-900T00 Microsoft Azure Data Fundamentals is recommended 1 - Discover data analysis Overview of data analysis Roles in data Tasks of a data analyst 2 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 3 - Get data in Power BI Get data from files Get data from relational data sources Create dynamic reports with parameters Get data from a NoSQL database Get data from online services Select a storage mode Get data from Azure Analysis Services Fix performance issues Resolve data import errors 4 - Clean, transform, and load data in Power BI Shape the initial data Simplify the data structure Evaluate and change column data types Combine multiple tables into a single table Profile data in Power BI Use Advanced Editor to modify M code 5 - Design a semantic model in Power BI Work with tables Create a date table Work with dimensions Define data granularity Work with relationships and cardinality Resolve modeling challenges 6 - Add measures to Power BI Desktop models Create simple measures Create compound measures Create quick measures Compare calculated columns with measures 7 - Add calculated tables and columns to Power BI Desktop models Create calculated columns Learn about row context Choose a technique to add a column 8 - Use DAX time intelligence functions in Power BI Desktop models Use DAX time intelligence functions Additional time intelligence calculations 9 - Optimize a model for performance in Power BI Review performance of measures, relationships, and visuals Use variables to improve performance and troubleshooting Reduce cardinality Optimize DirectQuery models with table level storage Create and manage aggregations 10 - Design Power BI reports Design the analytical report layout Design visually appealing reports Report objects Select report visuals Select report visuals to suit the report layout Format and configure visualizations Work with key performance indicators 11 - Configure Power BI report filters Apply filters to the report structure Apply filters with slicers Design reports with advanced filtering techniques Consumption-time filtering Select report filter techniques Case study - Configure report filters based on feedback 12 - Enhance Power BI report designs for the user experience Design reports to show details Design reports to highlight values Design reports that behave like apps Work with bookmarks Design reports for navigation Work with visual headers Design reports with built-in assistance Tune report performance Optimize reports for mobile use 13 - Perform analytics in Power BI Explore statistical summary Identify outliers with Power BI visuals Group and bin data for analysis Apply clustering techniques Conduct time series analysis Use the Analyze feature Create what-if parameters Use specialized visuals 14 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 15 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method Additional course details: Nexus Humans PL-300T00: Microsoft Power BI Data Analyst 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 PL-300T00: Microsoft Power BI Data Analyst 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 3 Days 18 CPD hours This course is intended for CxO?s IT Managers/ Directors Senior Project Officers Project & Program Coordinator/Managers Operations Managers Quality Managers Business Analysts Engineering Managers IT Infrastructure Managers Internal Consultants Professional Consultants Overview Change and the individual Change and the organization Communication and stakeholder engagement Change practice Dealing with change and more importantly, the impact of change is a high priority for all organisations. The Change Management Certification has been developed by APMG in partnership with the Change Management Institute (CMI), an independent, global professional association of change managers. Together they have developed a professional ?body of knowledge? for the discipline of change management. This body of knowledge now provides an independent benchmark for the professional knowledge expected of an effective change manager. APMG?s refreshed Change Management certification is fully aligned with the change management body of knowledge. Prerequisites There is no prerequisite to attending this foundation course, although it is recommended that candidates should have a good understanding of business practices. 1 - Change and the Organization Drivers for change Developing a vision Culture and climate Emergent change and lifecycle Organizational metaphors Models of change Roles required for change 2 - Stakeholders Principles Identification Analysis Influencing and listening Emotion and demonstration Communications Cognitive biases Remaining people focused Improving Communications Communications channels Collaboration Communications Planning Larger workshops 2 - Change Impact Assessing impact McKinsey 7 S Stakeholder impact assessment Assessing change readiness Large change ? how to staff Building a change team Preparing for resistance Building team effectiveness 4 - Individual Change Learning theory Motivation Change Curve Personality differences