722 Courses in Coventry delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

This qualification is for people who wish to raise their awareness of Mental Health problems associated with work and everyday life and how they can potentially improve their own mindfulness. Learners will be introduced to Mental Health conditions such as depression and suicide and build an understanding of stress. They will be introduced to the use of appropriate language when supporting others and the importance of self-care to potentially improve their own Mental Health. This course is delivered via online learning and assessed via an invigilated e-Assessment giving you the greatest flexibility to complete the course at a time convenient to you. Once your training is complete we will book a time which is convenient to you to undertake your invigilated e-Assessment via Teams.

This course starts with data transformation strategies, exploring capabilities in the Power Query Editor, and data-cleansing practices. It looks at the Advanced Query Editor to view the M language code. This course focuses on advanced DAX measures that include filtering conditions, with a deep dive into time intelligence measures. Like the M query language, DAX is a rich functional language that supports variables and expression references. This course also looks at the creation of dynamic dashboards and incorporates a range of visualisations available in Power BI Desktop and online in the AppSource. The course finishes with a look at setting up end user level security in tables. 1 The query editor Split by row delimiter AddDays to determine deadlines Advanced query editor 2 Fuzzy matching joins Matching inconsistencies by percentage Matching with transformation table 3 Logical column functions Logical functions IF, AND, OR Using multiple conditions Including FIND in functions 4 Editing DAX measures Make DAX easier to read Add comments to a measure Using quick measures 5 The anatomy of CALCULATE Understanding CALCULATE context filters Adding context to CALCULATE with FILTER Using CALCULATE with a threshold 6 The ALL measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentage 7 DAX iterators Anatomy of iterators A closer look at SUMX Using RELATED in SUMX Create a RANKX RANKX with ALL 8 Date and time functions Overview of functions Create a DATEDIFF function 9 Time intelligent measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 10 Visualisations in-depth Utilising report themes Create a heatmap Comparing proportions View trends with sparklines Group numbers using bins Setting up a histogram 11 Comparing variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint 12 User level security Setting up row level security Testing user security

Duration 5 Days 30 CPD hours This course is intended for This is a basic-level programming course designed for attendees with prior development experience in another language, such as COBOL, 4GL, Mainframe or other non-object oriented languages. This course is not geared for non-developers. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how it relates to OO programming and the Object Model Work with the Modular system (Project Jigsaw) Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Process large amount of data using Lambda expressions and the Stream API Abstract, static and private methods in interfaces Take advantage of the Java tooling that is available with the programming environment being used in the class Java 11 features covered: Using the Local Variable Type in Lambda expressions; Updates made to the String API This course provides hands-on Java 11 training for developers who have little or no prior working knowledge of object-oriented programming languages such as C, COBOL, and 4GL. You will learn the best practices for writing great object-oriented programs in Java 11, using sound development techniques, new improved features for better performance, and new capabilities for addressing rapid application development. Special emphasis is placed on object oriented concepts and best practices. A First Look The Java Platform Using the JDK The Eclipse Paradigm Getting Started with Java Writing a Simple Class Adding Methods to the Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Essential Java Programming Language Statements Using Strings Specializing in a Subclass Fields and Variables Using Arrays Local-Variable Type Inference Java Packages and Visibility Object Oriented Development Inheritance and Polymorphism Interfaces and Abstract Classes Introduction to Exception Handling Exceptions Java Developer's Toolboxÿ Utility Classes Java Date/Time Advanced Java Programming Introduction to Generics Lambda Expressions and Functional Interface Working with Collections Collections Using Collections Stream APIÿ Streams Collectors The Java Module System Introduction to the Module System Time Permitting Formatting Strings Introduction to Annotations Java 12 and beyond Additional course details: Nexus Humans Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 This course is designed for people who want to learn the Python programming language in preparation for using Python to develop software for a wide range of applications, such as data science, machine learning, artificial intelligence, and web development. Overview In this course, you will develop simple command-line programs in Python. You will: Set up Python and develop a simple application. Declare and perform operations on simple data types, including strings, numbers, and dates. Declare and perform operations on data structures, including lists, ranges, tuples, dictionaries, and sets. Write conditional statements and loops. Define and use functions, classes, and modules. Manage files and directories through code. Deal with exceptions. Though Python has been in use for nearly thirty years, it has become one of the most popular languages for software development, particularly within the fields of data science, machine learning, artificial intelligence, and web development?all areas in which Python is widely used. Whether you're relatively new to programming, or have experience in other programming languages, this course will provide you with a comprehensive first exposure to the Python programming language that can provide you with a quick start in Python, or as the foundation for further learning. You will learn elements of the Python 3 language and development strategies by creating a complete program that performs a wide range of operations on a variety of data types, structures, and objects, implements program logic through conditional statements and loops, structures code for reusability through functions, classes, and modules, reads and writes files, and handles error conditions. Lesson 1: Setting Up Python and Developing a Simple Application Topic A: Set Up the Development Environment Topic B: Write Python Statements Topic C: Create a Python Application Topic D: Prevent Errors Lesson 2: Processing Simple Data Types Topic A: Process Strings and Integers Topic B: Process Decimals, Floats, and Mixed Number Types Lesson 3: Processing Data Structures Topic A: Process Ordered Data Structures Topic B: Process Unordered Data Structures Lesson 4: Writing Conditional Statements and Loops in Python Topic A: Write a Conditional Statement Topic B: Write a Loop Lesson 5: Structuring Code for Reuse Topic A: Define and Call a Function Topic B: Define and Instantiate a Class Topic C: Import and Use a Module Lesson 6: Writing Code to Process Files and Directories Topic A: Write to a Text File Topic B: Read from a Text File Topic C: Get the Contents of a Directory Topic D: Manage Files and Directories Lesson 7: Dealing with Exceptions Topic A: Handle Exceptions Topic B: Raise Exceptions

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 4 Days 24 CPD hours This course is intended for This advanced course is the third in a series of three classes designed for RPG IV programmers. Programming experience using RPG IV is mandatory when enrolling in this course. You should have attended RPG IV Programming Fundamentals Workshop for IBM i (AS060) and RPG IV Programming Intermediate Workshop for IBM i (AS070). This course is not designed for RPG III programmers who want RPG IV. RPG III programmers should review the agenda carefully before they make a decision to attend this class. Overview Use address pointers and user spaces in RPG IV programs Write database triggers in RPG IV Develop ILE modular objects and package them in service programs Explain the purpose of ILE activation groups Explain the behavior of error handling and percolation in ILE Code an ILE error handling program Call application program interfaces (APIs) from RPG IV program Programmers who can write comprehensive RPG IV programs using the IBM i RPG IV compiler (v7), learn additional skills & techniques. Comprehensive exposure to advanced features of the Integrated Language Environment (ILE) RPG compiler and the IBM i. Programmers who can write comprehensive RPG IV programs using the IBM i RPG IV compiler (v7), learn additional skills & techniques. Comprehensive exposure to advanced features of the Integrated Language Environment (ILE) RPG compiler and the IBM i.

journey for the planetary alignment and channelling for the collective.