3131 Development courses in Edinburgh delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for Application Consultant Business Process Architect Business Process Owner / Team Lead / Power User Developer Development Consultant Enterprise Architect Solution Architect System Architect Technology Consultant Overview This course will prepare you to: Get an overview about the workflow functions and functionality in SAP S/4HANA, S/4HANA Cloud and SAP Cloud Platform Explain the possible extensions of workflows in these technologies You want to learn about the workflow functionality in S/4HANA, S/4HANA Cloud and SAP Cloud Platform? This course provides a business overview of processes, which are working 'right out-of-the box'. It explains possible extensions and comes with several exercises to deepen the theoretical lessons. Introduction Explain workflow @SAP and in SAP S/4HANA Use SAP Fiori My Inbox App, Setup and Configuration Explain the installation and set up of the My Inbox app Access the My Inbox app Add a BWF system as a task provider Add a SAP BPM system as a task provider Use roles for SAP Fiori Define the gateway scenario and catalogs Use the task gateway service Perform further settings Implement BADIs Create dynamic columns for SWF_USER_ATTR Create push notifications for the SAP Fiori Launchpad Flexible Workflow Explain Flexible Workflow Use a Workflow Scenario Explain SAP S/4HANA Cloud workflow Responsibility Management SAP Cloud Platform Workflow Service Use SAP Cloud Platform Workflow for workflow application development Strategy Recommendations and Migration Options Discuss strategy recommendations for enterprise workflow with SAP Discuss migration options for existing workflows Additional course details: Nexus Humans BIT602 SAP Workflow with SAP Fiori 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 BIT602 SAP Workflow with SAP Fiori 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 This course is appropriate for advanced users, system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Students can apply the course skills to use Python in basic web development projects or automate or simplify common tasks with the use of Python scripts. Overview This skills-focused course is about 50% hands-on lab to lecture ratio, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert instructor, you'll learn how to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Work with with the standard library and its work-saving modules Create 'real-world', professional Python applications Know when to use collections such as lists, dictionaries, and sets Work with Pythonic features such as comprehensions and iterators Write robust code using exception handling Introduction to Python Programming Basics is a hands-on Python programming course that teaches you the key skills you?ll need to get started with programming in Python to a solid foundational level. The start of the course will lead you through writing and running basic Python scripts, and then guide you through how to use more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This course provides you with an excellent kick start for users new to Python and scripting, enabling you to quickly use basic Python skills on the job in a variety of ways. You?ll be able use Python in basic web development projects, or use it to automate or simplify common tasks with the use of Python scripts. The course also serves as a solid primer course / foundation for continued Python study in support for next level web development with Python, using Python in DevOps, Python for data science / machine learning or Python for systems admin or networking support. Python Quick View What is Python? Python timeline Advantages/disadvantages Installing Python Getting help The Python Environment Starting Python Using the interpreter Running a Python script Editors and IDEs Getting Started with Python Using variables Builtin functions String data Numberic data Converting types Console input/output Command line parameters Flow Control About flow control The if statement Relational and Boolean operators while loops Exiting from loops Array Types About array types Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions and generators Working with Files File overview Opening a text file Reading a text file Writing to a text file Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Returning values Parameters and arguments Variable scope Sorting The sorted() function Custom sort keys Lambda functions Sorting in reverse Using min() and max() Errors and Exception Handling Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Using packages Function and module aliases Getting Started with Object Oriented Programming and Classes About object-oriented programming Defining classes Constructors Understanding self Properties Instance Methods and data Class methods and data Inheritance Additional course details: Nexus Humans Introduction to Python Programming Basics (TTPS4800) 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 Introduction to Python Programming Basics (TTPS4800) 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 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

Course Overview The Cognitive Behavioural Therapy (CBT) Practitioner Certificate Course provides a comprehensive exploration of the theories, principles, and application of CBT. This course equips learners with the knowledge to understand the intricate relationship between thoughts, emotions, and behaviours, enabling them to foster positive change in various contexts. Designed for both aspiring practitioners and those seeking personal development, the course offers valuable techniques to address common psychological challenges, including anxiety, depression, and stress. Through structured learning modules, participants will develop a solid understanding of CBT frameworks and how they can be effectively implemented across different settings. By the end of the course, learners will have enhanced their critical thinking, problem-solving, and client support abilities, positioning them for greater confidence in professional or personal environments. Whether you are seeking to enhance your career prospects or enrich your own well-being, this course provides a rewarding foundation in the core methodologies of CBT. Course Description This professionally structured Cognitive Behavioural Therapy (CBT) Practitioner Certificate Course delves into the foundational theories of CBT, practical strategies for cognitive restructuring, and the step-by-step CBT process. Learners will gain insights into using CBT techniques for personal growth, managing anxiety and depression, and supporting children with autism. The course offers a balanced learning experience with theoretical frameworks and real-world application models to reinforce knowledge retention. Each module is carefully designed to build progressively, ensuring learners acquire critical analytical skills, emotional intelligence, and a strong ethical understanding of client-centred practice. Participants will be able to recognise cognitive distortions, design effective intervention plans, and support behavioural change with structured methods. With its inclusive approach, the course is ideal for those pursuing a foundation in mental health support or simply looking to apply CBT principles to everyday challenges. Successful completion will strengthen learners’ ability to contribute positively within therapeutic, educational, or care settings. Course Modules Module 01: Introduction to CBT Module 02: CBT Theories and Principles Module 03: CBT Tools and Strategies Module 04: CBT Process Module 05: CBT for Personal Growth Module 06: Overcoming Anxiety and Depression Module 07: CBT for Children with Autism (See full curriculum) Who is this course for? Individuals seeking to develop a strong understanding of cognitive behavioural therapy. Professionals aiming to enhance their therapeutic or client support capabilities. Beginners with an interest in mental health and behavioural sciences. Life coaches, educators, and support workers wishing to expand their skill set. Anyone looking to apply CBT principles for personal development and emotional resilience. Career Path Cognitive Behavioural Therapy Practitioner Mental Health Support Worker Life Coach or Personal Development Coach Behavioural Support Specialist Educational Support Assistant Youth and Community Worker Well-being Consultant Counselling Assistant

Course Overview This comprehensive course offers a deep dive into three essential technologies for data science: Python, JavaScript, and Microsoft SQL. Learners will gain foundational knowledge and practical skills in each of these key areas, which are crucial for handling data, creating interactive websites, and working with databases. By the end of the course, students will be proficient in writing Python code for data analysis, creating dynamic web content with JavaScript, and managing data with Microsoft SQL. The course is designed to equip learners with the technical skills needed to succeed in data science, making it a valuable investment for anyone looking to excel in this growing field. Course Description In this course, learners will explore the core principles of Python, JavaScript, and Microsoft SQL, all tailored to the needs of data science professionals. The curriculum covers Python’s data structures, functions, and libraries essential for data analysis, while JavaScript introduces students to web development skills, including client-side validation and data visualisation. The Microsoft SQL section focuses on data management, including filtering, joining, and structuring queries. Learners will develop a solid understanding of these technologies, which will enable them to manipulate data, automate processes, and design interactive applications. The course also includes real-world applications, ensuring learners are well-prepared for future opportunities in data science and web development. Course Modules: Module 01: JavaScript Getting Started Module 02: JavaScript Fundamentals Module 03: JavaScript Strings Module 04: JavaScript Operators Module 05: JavaScript Conditional Statements Module 06: JavaScript Control Flow Statements Module 07: JavaScript Functions Module 08: Data Visualization (Google Charts) Module 09: JavaScript Error Handling Module 10: JavaScript Client-Side Validations Module 11: Python Introduction Module 12: Python Basic Module 13: Python Strings Module 14: Python Operators Module 15: Python Data Structures Module 16: Python Conditional Statements Module 17: Python Control Flow Statements Module 18: Python Core Games Module 19: Python Functions Module 20: Python Args, KW Args for Data Science Module 21: Python Project Module 22: Publish Your Website for Live Module 23: MS SQL Statements Module 24: MS SQL Filtering Data Module 25: MS SQL Functions Module 26: MS SQL Joins Module 27: MS SQL Advanced Commands Module 28: MS SQL Structure and Keys Module 29: MS SQL Queries Module 30: MS SQL Structure Queries Module 31: MS SQL Constraints Module 32: MS SQL Backup and Restore (See full curriculum) Who is this course for? Individuals seeking to enhance their skills in data science. Professionals aiming to expand their knowledge in programming and database management. Beginners with an interest in Python, JavaScript, and SQL. Anyone looking to enter the field of data science or web development. Career Path Data Scientist Web Developer Database Administrator Data Analyst Front-End Developer Full Stack Developer Data Engineer

In this masterclass we'll unravel the complexities of the online world, shedding light on the most pressing current and emerging risks and opportunities faced by children and young people, from the perspective of the DSL, as Online Safety Lead.

Montessori and Waldorf Approaches for Early Childhood Course Overview This course provides an in-depth exploration of the Montessori and Waldorf approaches to early childhood education. Learners will gain insight into two of the most respected educational philosophies, examining their core principles, teaching strategies, and how they impact child development. By the end of the course, learners will have a solid understanding of these approaches and how they can be applied in diverse early childhood settings. The course offers a comprehensive perspective on fostering creativity, independence, and emotional growth in children, ensuring that learners are equipped to implement these methods effectively. Course Description The course delves deeply into the Montessori and Waldorf educational philosophies, covering key aspects such as child-centred learning, the role of the educator, and the creation of nurturing learning environments. Learners will explore the developmental stages of early childhood, how to encourage autonomy, and how each approach fosters social and emotional skills. Topics include understanding the use of educational materials in Montessori classrooms and the creative, artistic methods used in Waldorf education. Throughout the course, learners will build the knowledge needed to incorporate these approaches into early childhood practices, enhancing their educational expertise and ability to support children's growth and learning. Montessori and Waldorf Approaches for Early Childhood Curriculum Module 01: Montessori and Waldorf Approaches for Early Childhood (See full curriculum) Who is this course for? Individuals seeking to enhance their knowledge of early childhood education. Professionals aiming to develop expertise in alternative teaching methods. Beginners with an interest in child development and education. Educators looking to diversify their teaching methods. Career Path Early Childhood Educator Montessori Teacher Waldorf Teacher Educational Consultant Child Development Specialist

Sharing & Networking - Regular giving fundraising programmes. Session aimed at those working in supporter care, individual giving and leadership roles. THIS SESSION WILL NOT BE RECORDED

Javascript for Data Structures Course Overview This course, JavaScript for Data Structures, offers a comprehensive introduction to fundamental data structures using JavaScript. Learners will explore core concepts such as lists, stacks, queues, and sets, gaining a solid understanding of how data is organised and managed in programming. The course emphasises clear, logical thinking and problem-solving skills applicable to software development, data analysis, and computer science. By the end, participants will be able to implement key data structures effectively, enhancing their coding proficiency and preparing them for more advanced programming challenges or career opportunities in technology-related fields. Course Description This course delves into essential data structures within JavaScript, providing detailed coverage of lists, stacks, queues, and sets. Learners will study how these structures operate, their use cases, and how to manipulate them efficiently in code. The curriculum is designed to develop both theoretical understanding and coding ability through structured explanations and examples. Throughout the course, students will develop skills in data organisation, algorithmic thinking, and memory management principles. This knowledge is critical for writing optimised code and tackling complex computational problems in software development and data science domains. Javascript for Data Structures Curriculum Module 01: Introduction Module 02: Essential Concepts Module 03: List Data Structure Module 04: Stack Data Structure Module 05: Queue Data Structure Module 06: Set Data Structure Module 07: Final Thought (See full curriculum) Who Is This Course For? Individuals seeking to build strong foundations in data structures using JavaScript. Professionals aiming to enhance their software development skills. Beginners with an interest in programming and computer science. Students preparing for technical roles in coding or data analysis. Career Path Software Developer Front-End Developer Data Analyst Junior Programmer Computer Science Student

Refactor Javascript Course Overview This Refactor JavaScript course provides learners with essential techniques to improve and optimise their existing JavaScript code. Focusing on enhancing code readability, maintainability, and performance, the course guides learners through identifying common code issues and applying structured improvements. By mastering refactoring principles, participants will be able to transform complex, inefficient scripts into clean, modular, and scalable solutions. The course is designed to boost problem-solving abilities and coding discipline, preparing learners to write more efficient and professional JavaScript. This knowledge is vital for developers aiming to improve legacy codebases or enhance collaboration within development teams. Course Description This course covers core refactoring concepts specific to JavaScript, starting with recognising problematic code patterns known as code smells. Learners will explore techniques for refining code elements such as functions, variables, and classes, followed by strategies to reorganise overall code structure for improved clarity and performance. The content emphasises systematic approaches to restructuring code without changing its external behaviour, helping participants understand best practices and coding standards. Through detailed explanations and examples, learners will gain confidence in evaluating and improving existing JavaScript projects. The course aims to develop skills crucial for maintaining high-quality software and supporting ongoing development in dynamic environments. Refactor Javascript Curriculum: Module 01: Introduction Module 02: Code Smells Module 03: Code Elements Refactoring Module 04: Code Structure Refactoring Module 05: Conclusion (See full curriculum) Who is this course for? Individuals seeking to enhance their JavaScript coding quality. Professionals aiming to advance their software development skills. Beginners with an interest in JavaScript programming and software design. Developers involved in maintaining or improving existing codebases. Career Path Front-End Developer Full-Stack Developer Software Engineer JavaScript Developer Web Application Developer