489 Ecosystem courses in Cardiff delivered Online

Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified Renewable Energy Complete Course bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our 30 course mega bundle that will exceed your expectations within your budget. The Renewable Energy Complete Course related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then StudyHub proposes a preparatory bundle. This comprehensive Renewable Energy Complete Course bundle will help you build a solid foundation to become a proficient worker in the sector. This Renewable Energy Complete Course Bundle consists of the following 25 CPD Accredited Premium courses - Course 1: Solar Energy Course 2: Sustainable Energy, Development and Environmental Impacts Course 3: Oil and Gas Industry Course 4: Petroleum Refining Demystified Course 5: Online Course in Conservation Course 6: Environment Management Course 7: Environmental Health Course 8: Environmental Law 2021 Course 9: Meteorology Course 10: Land Management Course 11: Diploma in Water Treatment Course 12: Forestry Course 13: Agricultural Science Course 14: Botany Course 15: Wildlife Rescue and Rehabilitation Course 16: Architectural Studies Course 17: Cleaning: Disinfection, Waste Management and Chemical Safety Course 18: COSHH (Control of Substances Hazardous to Health) - Awareness Course 19: Spill Management Training Course 20: Horticulture & Organic Gardening Course 21: Homesteading Diploma Course 22: Floristry Academy Diploma Course 23: Arboriculture Course 24: Marine Biology Course - Online Diploma Course 25: Garden Design Course 26: Escaping Consumerism Course 27: Administration of Emergency Medical Gases Course 28: Accredited level 3 Oceanography Diploma Course 29: Hydrogen Sulphide Training: Safety and Awareness in Hazardous Environments Course 30: Public Realm Manager's Guide: Urban Planning and Management Course 31: Solar & Thermal Energy: Harnessing Renewable Power Sources Course 32: Sustainable Management of Renewable Energy Resources 5 Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques- Course 1: Career Development Plan Fundamentals Course 2: CV Writing and Job Searching Course 3: Interview Skills: Ace the Interview Course 4: Video Job Interview for Job Seekers Course 5: Create a Professional LinkedIn Profile Learning Outcome This tailor-made Renewable Energy Complete Course bundle will allow you to- Uncover your skills and aptitudes to break new ground in the related fields Deep dive into the fundamental knowledge Acquire some hard and soft skills in this area Gain some transferable skills to elevate your performance Maintain good report with your clients and staff Gain necessary office skills and be tech savvy utilising relevant software Keep records of your work and make a report Know the regulations around this area Reinforce your career with specific knowledge of this field Know your legal and ethical responsibility as a professional in the related field Course 1: Solar Energy Understand the principles of solar energy generation and its applications in various sectors. Learn to design and implement solar energy systems, including photovoltaic and solar thermal systems. Gain knowledge about the environmental and economic benefits of solar energy and its role in sustainable development. Course 2: Sustainable Energy, Development and Environmental Impacts Explore the concept of sustainable energy and its significance in addressing environmental challenges. Analyze the environmental impacts of different energy sources and their contribution to sustainable development. Develop strategies for promoting sustainable energy practices in various industries. Course 3: Oil and Gas Industry Gain insights into the fundamentals of the oil and gas industry, including exploration, production, and distribution. Understand the economic and geopolitical factors influencing the global oil and gas market. Learn about environmental regulations and sustainability practices within the industry. Course 4: Petroleum Refining Demystified Comprehend the processes involved in petroleum refining and its role in producing various fuel products. Analyze the challenges and technologies associated with cleaner and more efficient refining. Gain knowledge of safety measures and environmental considerations in petroleum refining. This Renewable Energy Complete Course Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments. Course 5: Online Course in Conservation Learn about the principles and methods of conservation biology and ecology. Understand the importance of biodiversity conservation and ecosystem management. Explore practical approaches to conserving natural resources and protecting endangered species. Course 6: Environment Management Develop skills in environmental management, including planning, monitoring, and assessment. Explore strategies for sustainable resource use and pollution control. Understand the regulatory frameworks and compliance requirements in environmental management. Course 7: Environmental Health Gain knowledge of environmental factors that impact public health. Learn about epidemiological methods for assessing and managing environmental health risks. Explore strategies for improving air and water quality and preventing environmental-related diseases. Course 8: Environmental Law 2021 Understand the legal frameworks and regulations governing environmental protection. Analyze case studies and recent developments in environmental law. Learn about compliance, enforcement, and the role of stakeholders in environmental legal issues. Course 9: Meteorology Acquire a foundational understanding of meteorology and weather forecasting. Learn about the science behind atmospheric phenomena and climate patterns. Explore the practical applications of meteorology in various industries. Course 10: Land Management Develop skills in land use planning, conservation, and sustainable land management. Learn about land tenure systems, property rights, and land-related policies. Explore techniques for land assessment, soil conservation, and land-use decision-making. Course 11: Diploma in Water Treatment Understand the principles of water treatment processes and their importance in ensuring clean and safe drinking water. Gain knowledge of various water treatment technologies and their applications in addressing water quality issues. Learn about the regulatory standards and quality control measures in water treatment. Course 12: Forestry Develop an understanding of forestry practices, including tree cultivation, maintenance, and sustainable harvesting. Explore the ecological and environmental aspects of forest ecosystems and biodiversity conservation. Learn about forestry management strategies and their role in sustainable resource utilization. Course 13: Agricultural Science Gain insights into the science of agriculture, including crop cultivation, soil management, and pest control. Understand the principles of sustainable farming and the use of technology in modern agriculture. Explore the challenges and opportunities in the agricultural sector. Course 14: Botany Study the fundamentals of botany, including plant anatomy, physiology, and taxonomy. Learn about plant diversity and the role of plants in ecosystems and human societies. Explore the applications of botany in fields such as agriculture, medicine, and conservation. Course 15: Wildlife Rescue and Rehabilitation Develop skills in rescuing and caring for injured or orphaned wildlife. Learn about wildlife rehabilitation techniques and ethical considerations. Understand the legal and regulatory aspects of wildlife rescue and rehabilitation. Course 16: Architectural Studies Explore the principles of architectural design, construction, and planning. Gain knowledge of architectural history and various architectural styles. Learn about sustainable architecture and its role in contemporary design. Course 17: Cleaning: Disinfection, Waste Management and Chemical Safety Understand the importance of cleaning, disinfection, and waste management in various settings. Learn about safe handling of chemicals and hazardous substances. Explore best practices for maintaining cleanliness and hygiene. Course 18: COSHH (Control of Substances Hazardous to Health) - Awareness Gain awareness of the COSHH regulations and their significance in workplace safety. Learn to identify hazardous substances and assess associated risks. Understand the measures and controls for safe handling of hazardous materials. Course 19: Spill Management Training Develop skills in responding to chemical spills and hazardous material incidents. Learn about containment and cleanup procedures for different types of spills. Understand the importance of risk assessment and prevention in spill management. Course 20: Horticulture & Organic Gardening Explore the principles of horticulture and organic gardening practices. Learn about plant propagation, soil health, and sustainable gardening techniques. Gain knowledge of organic pest control and environmentally friendly gardening. Course 21: Homesteading Diploma Gain knowledge and practical skills related to homesteading, including food production, self-sufficiency, and sustainable living. Learn about the principles of permaculture and how to create a self-sustaining homestead. Understand the basics of animal husbandry, crop cultivation, and homestead design. Course 22: Floristry Academy Diploma Develop expertise in floral design, arranging, and creating stunning flower arrangements. Learn about the different types of flowers, foliage, and their care and maintenance. Explore the art of floristry for various occasions, from weddings to special events. Course 23: Arboriculture Understand the science and practice of arboriculture, including tree care, maintenance, and preservation. Learn about tree biology, pruning techniques, and risk assessment in tree management. Gain knowledge of urban forestry and the importance of trees in urban environments. Course 24: Marine Biology Course - Online Diploma Explore marine ecosystems, biodiversity, and the role of marine organisms in aquatic environments. Learn about marine conservation, environmental threats, and the importance of protecting marine life. Gain insights into the field of marine biology and its relevance in scientific research. Course 25: Garden Design Develop skills in garden design, landscape planning, and creating outdoor spaces. Learn about garden styles, plant selection, and principles of garden aesthetics. Understand the practical aspects of garden construction and maintenance. Course 26: Escaping Consumerism Explore the concept of consumerism and its impact on individuals and society. Learn strategies for reducing consumption, living more sustainably, and embracing minimalism. Gain insights into the benefits of conscious consumer choices and alternative lifestyles. Certification After studying the complete Renewable Energy Complete Course training materials, you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of •8. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Course 27: Administration of Emergency Medical Gases Acquire knowledge of emergency medical gases, their uses, and safe administration. Learn about the regulatory requirements and guidelines for handling medical gases in emergencies. Develop skills in responding to medical emergencies that require the use of medical gases. Course 28: Accredited level 3 Oceanography Diploma Explore the field of oceanography, including ocean dynamics, marine ecosystems, and climate science. Gain knowledge of oceanographic research methods and data analysis techniques. Understand the role of oceanography in addressing environmental challenges. Course 29: Hydrogen Sulphide Training: Safety and Awareness in Hazardous Environments Learn about the properties of hydrogen sulphide (H2S) and its hazards in industrial environments. Acquire skills in detecting, preventing, and responding to H2S emergencies. Understand safety protocols and equipment used in H2S-prone settings. Course 30: Public Realm Manager's Guide: Urban Planning and Management Explore urban planning principles, city management, and the role of public realm managers. Learn about urban design, public spaces, and strategies for enhancing the quality of urban life. Gain insights into sustainable urban development and effective public realm management. Course 31: Solar & Thermal Energy: Harnessing Renewable Power Sources Understand the principles of solar and thermal energy generation and their applications. Learn about renewable energy technologies, including solar panels and thermal systems. Explore the benefits of harnessing solar and thermal energy for sustainable power generation. Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Renewable Energy Complete Course bundle! This bundle is also ideal for professionals looking for career advancement. Renewable Energy Researcher Clean Energy Advocate Solar Installation Manager Wind Farm Operations Manager Biomass Energy Developer Climate Change Analyst Sustainability Director Renewable Energy Auditor Biofuel Production Technician Solar Panel Inspector Green Supply Chain Manager Energy Policy Analyst Wind Turbine Designer Solar Project Coordinator Energy Storage Specialist Geothermal Plant Operator Hydropower Plant Manager Environmental Consultant Renewable Energy Consultant Clean Energy Project Manager Sustainable Architecture Designer Energy Efficiency Engineer Renewable Energy Planner Carbon Emissions Analyst Biomass Fuel Technician Solar Power Plant Manager Wind Energy Researcher Energy Management Analyst Renewable Energy Technician Bioenergy Analyst Solar Power Systems Designer Wind Turbine Maintenance Technician Hydropower Systems Engineer Environmental Scientist Sustainable Business Manager Green Energy Policy Advisor Wind Turbine Blade Technician Solar Energy Systems Engineer Sustainable Transportation Planner Renewable Energy Sales Representative Biomass Energy Systems Designer Carbon Offset Specialist Climate Risk Analyst Geothermal Energy Researcher Energy Efficiency Consultant Solar Energy Analyst Green Building Project Manager Wind Turbine Tower Technician Hydropower Plant Engineer Environmental Educator Clean Energy Investment Analyst Renewable Energy Project Developer Sustainable Product Designer Green Supply Chain Analyst Energy Policy Researcher Wind Energy Systems Engineer Solar Panel Manufacturing Technician Biofuel Production Engineer Energy Efficiency Auditor Hydropower Project Coordinator Environmental Impact Analyst Sustainable Agriculture Specialist Renewable Energy Market Analyst Biomass Power Plant Manager Solar Energy Systems Installer Wind Farm Construction Manager Green Energy Consultant Wind Turbine Systems Engineer Requirements Course 32: Sustainable Management of Renewable Energy Resources Develop expertise in the sustainable management of renewable energy sources. Learn about energy policy, renewable energy systems, and their environmental impact. Explore strategies for integrating renewable energy into existing energy grids and systems. Career path Renewable Energy Engineer Solar Power Technician Wind Turbine Technician Biomass Plant Operator Energy Analyst Energy Consultant Sustainability Coordinator Solar Sales Consultant Wind Energy Project Manager Green Building Consultant Energy Efficiency Specialist Geothermal Technician Hydropower Engineer Environmental Compliance Analyst

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) 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 Hands-on Predicitive Analytics with Python (TTPS4879) 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.

EFQM Certified Model Foundation Course The EFQM Foundation course will help you to benchmark and improve the performance of every organisation by using the new EFQM Model and RADAR diagnostic tool, version 2025! This is a two-day online course, delivered via a mix of work-rooms, presentations, videos, and one-to-one support. This course is credited as part of the admission to the EFQM Assessor, Performance Improvement Practitioner or Excellence Practitioner courses. Who is the EFQM Certified Model Foundation course for? This is the essential course for anyone who wants to find out about the EFQM Model and RADAR and how these tools can benefit an organisation. This course is suitable for anyone who wants to understand the new EFQM Model and how it can be used to make their organisation more effective. Whilst this training is effective as a stand-alone course, it is also a pre-requisite for anyone considering one of the EFQM qualification routes as a way of progressing their management development and career. At the end of the course, you will be able to: - demonstrate how the EFQM Model could benefit your organisation and how it could be used to overcome current and future challenges - explain how the Model is structured and how the different elements apply to your organisation - start applying the RADAR as both a diagnostic tool - to identify strengths and areas for improvement – and a performance improvement methodology - conduct a high-level self-assessment of your organisation - understand the opportunities provided by EFQM data and insights - gain an insight into the alternative uses of the EFQM Model The EFQM Foundation Course Training Programme Following the welcome and introduction, this course comprises of 9 modules: Module 0: Welcome & course objectives Module 1: Why we need a model to face & master complexity? Why the EFQM Model? Module 2: Introduction to the EFQM Model Module 3: The Model (part 1): Direction Module 4:The Model (part 2): Execution Module 5: The Model (part 3): Results Module 6: RADAR Module 7: Assessment Module 8: Data & Insights Module 9: Next steps Delivery The course is delivered through a virtual trainer led live class Cost £800 + VAT If you are not yet a member but are already thinking about joining CforC, you can find more information on how to become a member and the benefits by clicking here.

Unlock the secrets to sustainable growth and success at the ‘Leadership and Business Transformation Insights for SMEs’ workshop! This is a dynamic, practical workshop designed for small and medium-sized enterprises, entrepreneurs, and anyone eager to learn from real-world leadership experiences in Essex. Event Details: Date: Tuesday 20th May Time: 10:00am – 1:00pm Location: Online (ZOOM) For: Businesses in Essex (Excluding Southend and Thurrock) Discover how strong leadership drives successful business transformation. Through inspiring case studies and expert-led discussions, this workshop will explore how visionary leaders have reshaped their organisations, setting the stage for long-term competitive advantage. Who Should Attend: SME owners and managers Aspiring and current leaders Business consultants and professionals interested in transformation strategies Whether you're looking to lead change within your own business or simply want to gain practical tools and knowledge, this session is packed with valuable insights and takeaways. Book your spot today and take the first step toward impactful leadership and meaningful change! About the host: Ross Moran, Business Advisory Manager Over two decades focusing on new venture creation and business transformation, Ross has worked in multiple finance, management, and technology roles within small and large organisations. Implementing new business models and developing a deep understanding of how technology process improvements intersect with business lifecycles and ecosystems has given Ross a unique perspective on most aspects of business including market research, new product development, raising finance, sales, marketing, and business transformation. This workshop is provided courtesy of Backing Essex Business. Fully-funded by Essex County Council and delivered by Let’s Do Business Group. Backing Essex Business (Formerly Back to Business Essex) is here to support business growth across the county, promoting economic growth and creating jobs, by providing free business support, access to finance and training. This workshop is available to businesses within Essex, excluding Southend and Thurrock. For more information visit https: www.backingessexbusiness.co.uk Please click here to see the Backing Essex Business Privacy Policy

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

Duration 2 Days 12 CPD hours This course is intended for This class assumes some prior experience with Git, plus basic coding or programming knowledge. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment led by our expert team, students will explore: Getting Started with Collaboration Understanding the GitHub Flow Branching with Git Local Git Configuration Working Locally with Git Collaborating on Your Code Merging Pull Requests Viewing Local Project History Streaming Your Workflow with Aliases Workflow Review Project: GitHub Games Resolving Merge Conflicts Working with Multiple Conflicts Searching for Events in Your Code Reverting Commits Helpful Git Commands Viewing Local Changes Creating a New Local Repository Fixing Commit Mistakes Rewriting History with Git Reset Merge Strategies: Rebase This is a fast-paced hands-on course that provides you with a solid overview of Git and GitHub, the web-based version control repository hosting service. While the examples in this class are related to computer code, GitHub can be used for other content. It offers the complete distributed version control and source code management (SCM) functionality of Git as well as adding its own features. It provides access control and several collaboration features such as bug tracking, feature requests, task management, and wikis for every project. Getting Started with The GitHub Ecosystem What is Git? Exploring a GitHub Repository Using GitHub Issues Activity: Creating A GitHub Issue Using Markdown Understanding the GitHub Flow The Essential GitHub Workflow Branching with Git Branching Defined Activity: Creating a Branch with GitHub Introduction Class Diagram Interaction Diagrams Sequence Diagrams Communication Diagrams State Machine Diagrams Activity Diagram Implementation Diagrams Local Git Configuration Checking your Git version Git Configuration Levels Viewing your configurations Configuring your username and email Configuring autocrif Working Locally with Git Creating a Local copy of the repo Our favorite Git command: git status Using Branches locally Switching branches Activity: Creating a New File The Two Stage Commit Collaborating on Your Code Collaboration Pushing your changes to GitHub Activity: Creating a Pull Request Exploring a Pull Request Activity: Code Review Merging Pull Requests Merge Explained Merging Your Pull Request Updating Your Local Repository Cleaning Up the Unneeded Branches Viewing Local Project History Using Git Log Streaming Your Workflow with Aliases Creating Custom Aliases Workflow Review Project: GitHub Games User Accounts vs. Organization Accounts Introduction to GitHub Pages What is a Fork? Creating a Fork Workflow Review: Updating the README.md Resolving Merge Conflicts Local Merge Conflicts Working with Multiple Conflicts Remote Merge Conflicts Exploring Searching for Events in Your Code What is GitHub? What is Git bisect? Finding the bug in your project Reverting Commits How Commits are made Safe operations Reverting Commits Helpful Git Commands Moving and Renaming Files with Git Staging Hunks of Changes Viewing Local Changes Comparing changes with the Repository Creating a New Local Repository Initializing a new local repository Fixing Commit Mistakes Revising your last commit Rewriting History with Git Reset Understanding reset Reset Modes Reset Soft Reset Mixed Reset Hard Does gone really mean gone? Getting it Back You just want that one commit Oops, I didn?t mean to reset Merge Strategies: Rebase About Git rebase Understanding Git Merge Strategies Creating a Linear History Additional course details: Nexus Humans Introduction to GITHub for Developers (TTDV7551) 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 GITHub for Developers (TTDV7551) 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.

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The 'Ethereum & Blockchain Applications Development with Solidity' course offers a comprehensive introduction to Ethereum and blockchain technology. It covers the basics of Ethereum, Solidity programming language, advanced concepts, and explores various use cases of blockchain beyond cryptocurrency applications. Learning Outcomes: Understand the fundamentals of Ethereum and its role in the blockchain ecosystem. Gain proficiency in the Solidity programming language to develop smart contracts on the Ethereum platform. Explore advanced concepts in Ethereum development, including security, optimization, and best practices. Discover other applications of blockchain technology beyond cryptocurrencies, such as supply chain management, voting systems, and more. Access additional resources to further enhance knowledge and skills in Ethereum and blockchain application development. Why buy this Ethereum & Blockchain Applications Development with Solidity? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Ethereum & Blockchain Applications Development with Solidity there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Individuals with a keen interest in understanding blockchain technology and Ethereum's role within it. Software developers seeking to broaden their expertise into blockchain application development. Entrepreneurs aiming to leverage blockchain technology for innovative business solutions. Students in computer science or related fields desiring a comprehensive understanding of Ethereum and Solidity. Technology enthusiasts eager to explore the potential and workings of decentralized applications. Prerequisites This Ethereum & Blockchain Applications Development with Solidity does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Ethereum & Blockchain Applications Development with Solidity was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Blockchain Developer: £50,000 - £70,000 Annually Ethereum Developer: £55,000 - £75,000 Annually Smart Contract Developer: £60,000 - £80,000 Annually Cryptocurrency Analyst: £45,000 - £65,000 Annually DApp Developer (Decentralized Applications): £52,000 - £72,000 Annually Blockchain Project Manager: £58,000 - £78,000 Annually Course Curriculum Section 01: Introduction to This Course Course Introduction 00:02:00 What Is Solidity? 00:07:00 What Is Blockchain? 00:15:00 Centralised vs Decentralised vs Distributed Systems 00:12:00 Is Blockchain Truly Decentralised and Distributed? 00:08:00 Structure of a Block 00:10:00 What Is a Hash? 00:08:00 What Are Merkle Trees? 00:08:00 What Is a Ledger? 00:06:00 History of Blockchain 00:21:00 Why Use Blockchain? 00:10:00 What Are Cryptocurrencies? 00:09:00 What Is Cryptography? 00:09:00 Section 02: Ethereum Basics What Is Ethereum & How Does It Differ To Bitcoin? 00:10:00 Advantages and Disadvantages Compared To Bitcoin 00:10:00 Ethereum vs Ethereum Classic 00:09:00 Section 03: History & Overview What Are Smart Contracts? 00:17:00 What Is Gas? 00:09:00 What Is Ethereum Mining? 00:06:00 What Are Ethereum Virtual Machines (EVM)? 00:06:00 Section 04: Install Ethereum Client Setup on Mac OS X 00:04:00 Setup on Linux 00:04:00 Setup on Windows 00:02:00 Remix Online IDE 00:03:00 Remix IDE Overview 00:10:00 Section 05: Solidity Basics Simple Source Code Example 00:03:00 Comments 00:03:00 Data Types 00:08:00 Variable Literals 00:03:00 Conditional Statements 00:08:00 Loops 00:09:00 Ether and Time Units 00:07:00 Function Calls 00:06:00 Special Variables and Functions 00:03:00 Arrays 00:05:00 Structs 00:03:00 Enums 00:04:00 Interfacing with Other Contracts 00:04:00 Constructor Arguments 00:04:00 Contract Inheritance 00:05:00 Multiple Inheritance and Linearization 00:03:00 Abstract Contracts 00:04:00 Visibility Specifiers 00:07:00 Accessor Functions 00:02:00 Function Modifiers 00:05:00 Events 00:02:00 Esoteric Functions 00:02:00 Section 06: Advanced ICO (Initial Coin Offering) 00:11:00 2007/2008 Crisis 00:18:00 Cypherpunks 00:18:00 History of FIAT Currency 00:13:00 DAO (Decentralised Autonomous Organisations) 00:13:00 Section 07: Other Uses of Blockchain Education 00:15:00 Retail 00:21:00 Health Industry 00:18:00 Business 00:10:00 Governance 00:12:00 Last Will and Testament 00:12:00 Blood Diamonds 00:06:00 Housing 00:15:00 Proof of Ownership/Identity 00:11:00 Data Storage 00:13:00 Section 08: Resource Resource 00:00:00 Assignment Assignment - Ethereum & Blockchain Applications Development with Solidity 00:00:00

This course will help you explore the world of Big Data technologies and frameworks. You will develop skills that will help you to pick the right Big Data technology and framework for your job and build the confidence to design robust Big Data pipelines.

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.