366 Analytics courses in Bulford Camp delivered Live Online

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.

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.

Email Marketing remains a cornerstone of digital communication, which when used effectively can elevate your brand, foster customer loyalty, and drive remarkable results.

Learn how to create and manage a successful YouTube channel for your business. This workshop will cover everything you need to know when setting up and using YouTube in your business. You will also learn how to use YouTube analytics to track your channel's performance to help you make improvements.

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

Duration 1 Days 6 CPD hours This course is intended for This course is designed for users who wish to analyze Website or mobile application traffic or online advertising campaigns using Google Analytics and Standard Google Analytics reports for a variety of reasons including increasing customer reach, and increasing conversions. Overview Upon successful completion of this course, students will be able to will perform more in-depth analysis of website data by using Google Analytics reports. In this course, you will create a Google Analytics account, create multiple web properties to monitor, and tag website pages with Google Analytics tracking code. You will then create multiple views for collecting and analyzing data, and create filters, goals, and funnels for your views. You will then use Google Analytics real-time reports and dashboards to perform quick analysis of your monitored websites. Implementing Google Analytics Overview of Google Analytics Create a Google Analytics Account Tag Your Pages Configuring Google Analytics Configure Google Analytics Settings Configure Accounts, Properties, and Views Configuring Goals, Funnels, and Filters Configure Goals Configure Funnels Configure Filters Configuring Monitoring and Alerting Monitor Real-Time Reports Manage Dashboards Manage Custom Alerts Analyzing Website Traffic Analyze Web Traffic with Audience Reports Analyze Web Traffic with Acquisition Reports Analyzing Behavior and Conversions Analyze Data with Behavior Reports Analyze Data with Conversion Reports Create Reports with Google Data Studio

Duration 3 Days 18 CPD hours This course is intended for Before taking this course delegates should already be familiar with basic analytics techniques, comfortable with basic data manipulation tools such as spreadsheets and databases and already familiar with at least one programming language Overview This course teaches delegates who are already familiar with analytics techniques and at least one programming language how to effectively use the programming language for three tasks: data manipulation and preparation, statistical analysis and advanced analytics (including predictive modelling and segmentation). Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. Outcomes: After completing the course, delegates will be capable of writing production-ready R code to perform advanced analytics tasks enabling their organisations make better, data-driven decisions. Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. Topic 1 Intro to our chosen language Topic 2 Basic programming conventions Topic 3 Data structures Topic 4 Accessing data Topic 5 Descriptive statistics Topic 6 Data visualisation Topic 7 Statistical analysis Topic 8 Advanced data manipulation Topic 9 Advanced analytics ? predictive modelling Topic 10 Advanced analytics ? segmentation

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization. Overview After completing this course delegates will be capable of writing effective R code to manipulate, analyse and visualise data to enable their organisations make better, data-driven decisions. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Course Outline Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R programming language is one of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. The course will explore the following topics through a series of interactive workshop sessions: What is R? Basic R programming conventions Data structures in R Accessing data in R Descriptive statistics in R Statistical analysis in R Data manipulation in R Data visualisation in R Additional course details: Nexus Humans Beginning Data Analytics With R 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 Beginning Data Analytics With R 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 1 Days 6 CPD hours This course is intended for Multi-role (consumers, business authors, professional authors, developers, administrators, modelers, project managers) This course provides students with an overview of the IBM Cognos Analytics suite of products and their underlying architecture. Students will examine each component as it relates to an Analytics solution & will be shown a range of resources. IBM Cognos Analytics Describe IBM Cognos Analytics Describe IBM Cognos Analytics components Describe IBM Cognos architecture at a high level Describe IBM Cognos security at a high level Consume Content in IBM Cognos Analytics Where do consumers access BI content? Use published reports Drill through to related data Specify run report options Specify properties of an entry Alerts and Watch Items Create Reports in IBM Cognos Analytics Overview of reporting and report authoring Identify package types, uploaded files, and data modules available for reporting Examine IBM Cognos Analytics - Reporting Examine the interface Explore different report types Create a simple, sorted, and formatted report Create a report view Create a subscription Create an Active Report Import and report on personal data Create Dashboards in IBM Cognos Analytics Describe IBM Cognos Dashboarding Identify the IBM Cognos Dashboarding user interface Add report content and tools to create dashboards Widget-to-widget communication Filter data in the dashboard Sort, group and ungroup, and calculate data Create Metadata Models in IBM Cognos Analytics Define IBM Cognos Framework Manager and its purpose Describe the IBM Cognos Framework Manager environment Describe IBM Cognos Cube Designer Get high-level content from Dynamic Cubes course and/or FM course Web-based Modeling Create Data Modules Extend IBM Cognos Analytics Introduction to IBM Cognos Mobile Key features Examine Cognos Mobile architecture Identify supported products Introduction to IBM Cognos BI for Microsoft Office Describe Cognos Analysis for Excel (CAF) Compare IBM Cognos Analytics & IBM Cognos BI New features in IBM Cognos Analytics Changes from IBM Cognos BI to IBM Cognos Analytics Legacy option Examine Event Studio Examine the role of Event Studio in Performance Management List the benefits of Event Studio Examine Metric Studio Identify scorecards, metrics, and metric types Organize metrics with strategies Track initiatives with projects