8 Marketing Analytics courses in Potters Bar delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. Overview By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions. The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.As you make your way through the course, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding sections, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. Data Preparation and Cleaning Data Models and Structured Data pandas Data Manipulation Data Exploration and Visualization Identifying the Right Attributes Generating Targeted Insights Visualizing Data Unsupervised Learning: Customer Segmentation Customer Segmentation Methods Similarity and Data Standardization k-means Clustering Choosing the Best Segmentation Approach Choosing the Number of Clusters Different Methods of Clustering Evaluating Clustering Predicting Customer Revenue Using Linear Regression Understanding Regression Feature Engineering for Regression Performing and Interpreting Linear Regression Other Regression Techniques and Tools for Evaluation Evaluating the Accuracy of a Regression Model Using Regularization for Feature Selection Tree-Based Regression Models Supervised Learning: Predicting Customer Churn Classification Problems Understanding Logistic Regression Creating a Data Science Pipeline Fine-Tuning Classification Algorithms Support Vector Machine Decision Trees Random Forest Preprocessing Data for Machine Learning Models Model Evaluation Performance Metrics Modeling Customer Choice Understanding Multiclass Classification Class Imbalanced Data Additional course details: Nexus Humans Data Science for Marketing Analytics 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 Data Science for Marketing Analytics 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.

What You'll Learn An introduction to reactive expressions - how they differ from base R functionality and why they are needed within Shiny. Simple reactive expressions - creating dynamic data expressions Reacting to user-initiated actions - how to get your dashboard to adapt dynamically to user inputs Nested reactions - more complex relationships where multiple actions need to bee accounted for About The Trainer Jeremy has been using R since the very first day of his career in 2005, when it was better known as a mere letter of the alphabet! As an early adopter of the language, he’s seen it evolve – from its ugly initial versions to more elegant analytics solutions underpinned by the tidyverse, on which this course is focused. He is a regular speaker on UK R circuit and co-organises a number of R-community groups, including LondonR, ManchesterR & BrightonR, and the infamous EARL conference! About Us Datacove are a data and analytics consultancy specialising in customer analytics, marketing analytics and process automation. With over 20 years of combined experience in the industry we answer the questions that sit at the heart of every business, from who your customers are, to where and how you find more of them and how much you need to spend to do so. We also automate your most painful business processes, removing the 20+ hours you spend on them per week, forever! Extra Information Our courses are delivered during core office hours, ensuring they fit seamlessly into your work schedule. Once your booking is confirmed, we will send you a Microsoft Teams link, allowing you to join the session with ease.

What You'll Learn Static vs dynamic displays - why interactive plots and tables are useful in shiny and how they can contribute towards the overall usability of the application Introduction to highcharter - how to create rendered, interactive plots using a similar syntax to the tidyverse (ggplot2) Developing dynamic charts within high charts - creating visualisations that respond to user-initiated actions within the application Introduction to DT - a package for creating data tables that users can interact with, e.g. by searching for specific pieces of data Developing dynamic tables within DT - developing sortable and searchable interactive tables for use in the application About The Trainer Jeremy has been using R since the very first day of his career in 2005, when it was better known as a mere letter of the alphabet! As an early adopter of the language, he’s seen it evolve – from its ugly initial versions to more elegant analytics solutions underpinned by the tidyverse, on which this course is focused. He is a regular speaker on UK R circuit and co-organises a number of R-community groups, including LondonR, ManchesterR & BrightonR, and the infamous EARL conference! About Us Datacove are a data and analytics consultancy specialising in customer analytics, marketing analytics and process automation. With over 20 years of combined experience in the industry we answer the questions that sit at the heart of every business, from who your customers are, to where and how you find more of them and how much you need to spend to do so. We also automate your most painful business processes, removing the 20+ hours you spend on them per week, forever! Extra Information Our courses are delivered during core office hours, ensuring they fit seamlessly into your work schedule. Once your booking is confirmed, we will send you a Microsoft Teams link, allowing you to join the session with ease.

What You'll Learn Overview of the Shiny interface - the difference between a UI and a server and how they interlink Shiny folder structures - hows to store and use static datasets, imagery and other assets for your application. Introduction to Shiny servers - how to create and deploy your first application and how to manage deployments within Shiny apps Basic Shiny UI inputs - include filters/drop downs, date sliders, text and buttons About The Trainer Jeremy has been using R since the very first day of his career in 2005, when it was better known as a mere letter of the alphabet! As an early adopter of the language, he’s seen it evolve – from its ugly initial versions to more elegant analytics solutions underpinned by the tidyverse, on which this course is focused. He is a regular speaker on UK R circuit and co-organises a number of R-community groups, including LondonR, ManchesterR & BrightonR, and the infamous EARL conference! About Us Datacove are a data and analytics consultancy specialising in customer analytics, marketing analytics and process automation. With over 20 years of combined experience in the industry we answer the questions that sit at the heart of every business, from who your customers are, to where and how you find more of them and how much you need to spend to do so. We also automate your most painful business processes, removing the 20+ hours you spend on them per week, forever! Extra Information Our courses are delivered during core office hours, ensuring they fit seamlessly into your work schedule. Once your booking is confirmed, we will send you a Microsoft Teams link, allowing you to join the session with ease.

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 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators or operators responsible for the installation, setup, configuration, and administration of the BIG-IQ system or management of BIG-IP devices and F5 products running on those devices. This course uses lectures and hands-on exercises to give participants real-time experience in configuring and using the BIG-IQ© product. Students are introduced to BIG-IQ, its interface, and its various functionality. We first look at administering and operating the BIG-IQ system itself, then detail how it is used to remotely manage BIG-IP devices running BIG-IP Local Traffic Manager (LTM). We then look configuring a BIG-IQ Data Collection Device (DCD) system and see how it is used for the remote storage and examination of BIG-IP log events and statistics. Module 1: BIG-IQ Overview BIG-IQ Centralized Management BIG-IQ Components BIG-IQ Core Functionality REST API BIG-IQ Data Collection Device (DCD) BIG-IP Cloud Edition (CE) Setting up the BIG-IQ System Module 2: Administering the BIG-IQ System Controlling Access to the BIG-IQ Creating, Authenticating, Configuring Users Backups Local Host Settings Configuring DNS, NTP, and SMTP Monitoring BIG-IQ, DCD, and BIG-IP Events with Alerts Monitoring BIG-IQ with iHealth Post Installation Issues; Licensing, Changing Management IP, Master Key, Restoring Backups Module 3: Managing BIG-IP LTM Devices BIG-IP LTM Device Discovery BIG-IP Device Backup Deploying to BIG-IP Devices Deployment and Deployment Logs Configuration Snapshots Managing BIG-IP Certificates Managing BIG-IP Licenses Monitoring BIG-IP Devices with iHealth Management of QKView Reports from Managed BIG-IP Devices Module 4: Setting Up the BIG-IQ Data Collection Device Custom Roles Types and Groups Setting up User Accounts with custom roles and privileges Managing BIG-IP DSC Discovery and management of BIG-IP Device Clusters (DSC) with BIG-IQ Administering BIG-IQ High Availability Configuration and management of BIG-IQ systems in a High Availability pair

Course Overview This comprehensive course on "Data Analysis and Forecasting in Excel" provides learners with essential skills to manage, analyse, and visualise data effectively using Excel. Whether you are analysing historical data or forecasting future trends, this course covers key tools such as PivotTables, charts, and lookup functions to make your data work for you. Learners will also gain proficiency in automating tasks and creating dynamic reports, which are invaluable for decision-making processes in various professional settings. By the end of the course, you will have the capability to work with complex data sets, produce insightful reports, and apply forecasting techniques to guide future strategies. Course Description In this course, learners will delve into the full spectrum of data analysis capabilities offered by Excel. Topics include modifying worksheets, working with lists, and using advanced tools such as PivotTables, PivotCharts, and lookup functions. Learners will explore the process of visualising data through charts and sparklines, allowing them to convey complex information in an accessible manner. The course also covers automating workbook functionality and creating mapping data for better analysis. Additionally, learners will gain expertise in forecasting data trends to support strategic planning. By the end of the course, participants will have developed a comprehensive understanding of Excel’s analytical tools, enabling them to manage data with efficiency and precision in various business contexts. Course Modules Module 01: Modifying a Worksheet Module 02: Working with Lists Module 03: Analyzing Data Module 04: Visualizing Data with Charts Module 05: Using PivotTables and PivotCharts Module 06: Working with Multiple Worksheets and Workbooks Module 07: Using Lookup Functions and Formula Auditing Module 08: Automating Workbook Functionality Module 09: Creating Sparklines and Mapping Data Module 10: Forecasting Data (See full curriculum) Who is this course for? Individuals seeking to enhance their Excel data analysis skills. Professionals aiming to improve their forecasting and reporting capabilities. Beginners with an interest in data management and analysis. Those seeking to enhance their proficiency in Excel for career advancement. Career Path Data Analyst Business Analyst Financial Analyst Marketing Analyst Operations Manager Project Manager Excel Specialist in various industries such as finance, marketing, and logistics

Excel Data Analysis Course Overview The Excel Data Analysis course is designed to equip learners with the essential skills needed to analyse and interpret data using Microsoft Excel. This course covers a range of tools and techniques that are vital for processing, summarising, and visualising data. Learners will explore functions, pivot tables, charts, and data manipulation strategies that will enable them to work efficiently with data sets. By the end of the course, learners will be able to transform raw data into meaningful insights, making it an invaluable skill for professionals across various industries. Whether you're looking to improve your data skills or progress in your career, this course offers the foundational knowledge required for data analysis in Excel. Course Description This course delves into the core aspects of Excel Data Analysis, starting with basic functions and advancing to complex data manipulation techniques. Learners will explore how to create and manage pivot tables, perform data filtering, and apply functions such as VLOOKUP and INDEX MATCH. Visualisation tools like charts and graphs will be covered, enabling learners to present their findings in a clear and impactful way. Additionally, learners will be introduced to data modelling, conditional formatting, and advanced formula techniques that will enhance their data analysis capabilities. The course is structured to provide a comprehensive understanding of Excel’s data analysis features, building competency for a wide range of practical applications in both personal and professional settings. Excel Data Analysis Curriculum Module 01: Introduction to Excel for Data Analysis Module 02: Using Excel Functions for Data Manipulation Module 03: Working with Pivot Tables and Pivot Charts Module 04: Data Visualisation: Creating Charts and Graphs Module 05: Advanced Excel Functions for Complex Data Analysis Module 06: Data Filtering and Sorting Techniques Module 07: Conditional Formatting for Data Insights Module 08: Introduction to Data Modelling and Forecasting Module 09: Data Analysis Best Practices and Case Studies (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance in data-centric roles. Beginners with an interest in data analysis and Excel. Anyone looking to improve their Excel knowledge for career development. Career Path Data Analyst Business Analyst Financial Analyst Marketing Analyst Operations Manager Administrative Assistant Project Manager Research and Development Analyst