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48-Hour Knowledge Knockdown! Prices Reduced Like Never Before! Have you ever looked at a map and wondered how it was created? Have you ever wanted to gain the skills to analyse spatial data? Look no further than our Spatial Analysis in ArcGIS bundle. With our QLS-endorsed Spatial Analysis in ArcGIS course, you'll gain a deep understanding of geographic information systems and how to utilise ArcGIS software for spatial data analysis. Plus, receive a free QLS hardcopy certificate upon completion, an essential addition to your credentials. But the learning doesn't stop there. Our bundle includes ten more relevant courses, all CPD-QS accredited. From ArcGIS for Hydrology to Web Scraping and Mapping Dam Levels in Python and Leaflet, you'll gain a comprehensive skill set in the field of spatial analysis. Don't just take our word for it. Our courses have been meticulously designed by experienced people to provide you with a theoretical understanding of the subject matter. And with our user-friendly platform, you can learn at your own pace and convenience. Unlock the power of spatial analysis with our bundle today. Enrol now and start your journey towards becoming a skilled spatial analyst. This Spatial Analysis in ArcGIS Bundle Package includes: Course 01: Award in Spatial Analysis in ArcGIS at QLS Level 2 10 Premium Additional CPD QS Accredited Courses - Course 01: ArcGIS for Hydrology Course 02: Remote Sensing in ArcGIS Course 03: QGIS Cartography Course 04: Business Intelligence and Data Mining Diploma Course 05: Python Data Science Course 06: Spatial Data Visualization and Machine Learning in Python Level 4 Course 07: Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4 Course 08: Learn to Use Python for Spatial Analysis in ArcGIS Course 09: Maps in R Shiny and Leaflet Course 10: The Basics of ArcGIS for Hydrology Why Prefer This Spatial Analysis in ArcGIS Bundle? You will receive a completely free certificate from the Quality Licence Scheme Option to purchase 10 additional certificates accredited by CPD Get a free Student ID Card - (£10 postal charges will be applicable for international delivery) Free assessments and immediate success results 24/7 Tutor Support After taking this Spatial Analysis in ArcGIS bundle courses, you will be able to learn: Develop a comprehensive understanding of spatial analysis and its applications in the industry. Gain practical experience using ArcGIS software for spatial data analysis and hydrology. Learn to use remote sensing techniques in ArcGIS for data collection and analysis. Master the art of cartography using QGIS software. Gain expertise in business intelligence, data mining, and data science using Python. Explore spatial data visualisation and machine learning using Python. Learn how to use R Shiny and Leaflet for creating interactive maps. ***Curriculum breakdown of Spatial Analysis in ArcGIS*** Module 01: Point Density Analysis Module 02: Raster Calculator and Vector Isolation Module 03: Raster to Topography Module 04: Raster Reclassification Module 05: Raster Overlay Module 06: Slope Analysis and Hydrology tools Module 07: Introduction to TIFF Files Module 08: Introduction to 3D Surfaces Module 09: Satellite Images and TIN Surfaces Module 10: Exercise How is the Spatial Analysis in ArcGIS Bundle Assessment Process? You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you successfully pass the exams CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals looking to expand their skill set in the field of spatial analysis. Graduates seeking to enhance their employability in the GIS industry. Individuals seeking to understand spatial data analysis for research purposes. Students pursuing a degree in GIS or a related field. Career path This bundle will be beneficial for anyone looking to pursue a career as: GIS Analyst: £22,000 - £35,000 per annum. GIS Developer: £30,000 - £50,000 per annum. Spatial Data Scientist: £30,000 - £70,000 per annum. Data Analyst: £25,000 - £40,000 per annum. Business Intelligence Analyst: £35,000 - £60,000 per annum. Hydrologist: £25,000 - £40,000 per annum. Certificates Award in Spatial Analysis in ArcGIS at QLS Level 2 Hard copy certificate - Included After successfully completing the course, you can order an original hardcopy Certificate of Achievement endorsed by the Quality Licence Scheme. This certificate will be delivered to your home, free of charge. To obtain the additional Quality Licence Scheme Endorsed Certificate, you will need to pay the corresponding fee based on the level of the courses: Level 1: £59 Level 2: £79 Level 3: £89 Level 4: £99 Level 5: £119 Level 6: £129 Level 7: £139 CPD QS Accredited Certificate Digital certificate - £10 Upon successfully completing the Bundle, you will need to place an order to receive a PDF Certificate for each course within the bundle. These certificates serve as proof of your newly acquired skills, accredited by CPD QS and will cost you £10 for each course. Also, the certificates are recognised throughout the UK and internationally. CPD QS Accredited Certificate Hard copy certificate - £29 International students are subject to a £10 delivery fee for their orders, based on their location.

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Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. Overview Create sophisticated SSIS packages for extracting, transforming, and loading data Use containers to efficiently control repetitive tasks and transactions Configure packages to dynamically adapt to environment changes Use Data Quality Services to cleanse data Successfully troubleshoot packages Create and Manage the SSIS Catalog Deploy, configure, and schedule packages Secure the SSIS Catalog SQL Server Integration Services is the Community Courseware version of 20767CC Implementing a SQL Data Warehouse. This five-day instructor-led course is intended for IT professionals who need to learn how to use SSIS to build, deploy, maintain, and secure Integration Services projects and packages, and to use SSIS to extract, transform, and load data to and from SQL Server. This course is similar to the retired Course 20767-C: Implementing a SQL Data Warehouse but focuses more on building packages, rather than the entire data warehouse design and implementation. Prerequisites Working knowledge of T-SQL and SQL Server Agent jobs is helpful, but not required. Basic knowledge of the Microsoft Windows operating system and its core functionality. Working knowledge of relational databases. Some experience with database design. 1 - SSIS Overview Import/Export Wizard Exporting Data with the Wizard Common Import Concerns Quality Checking Imported/Exported Data 2 - Working with Solutions and Projects Working with SQL Server Data Tools Understanding Solutions and Projects Working with the Visual Studio Interface 3 - Basic Control Flow Working with Tasks Understanding Precedence Constraints Annotating Packages Grouping Tasks Package and Task Properties Connection Managers Favorite Tasks 4 - Common Tasks Analysis Services Processing Data Profiling Task Execute Package Task Execute Process Task Expression Task File System Task FTP Task Hadoop Task Script Task Introduction Send Mail Task Web Service Task XML Task 5 - Data Flow Sources and Destinations The Data Flow Task The Data Flow SSIS Toolbox Working with Data Sources SSIS Data Sources Working with Data Destinations SSIS Data Destinations 6 - Data Flow Transformations Transformations Configuring Transformations 7 - Making Packages Dynamic Features for Making Packages Dynamic Package Parameters Project Parameters Variables SQL Parameters Expressions in Tasks Expressions in Connection Managers After Deployment How It All Fits Together 8 - Containers Sequence Containers For Loop Containers Foreach Loop Containers 9 - Troubleshooting and Package Reliability Understanding MaximumErrorCount Breakpoints Redirecting Error Rows Logging Event Handlers Using Checkpoints Transactions 10 - Deploying to the SSIS Catalog The SSIS Catalog Deploying Projects Working with Environments Executing Packages in SSMS Executing Packages from the Command Line Deployment Model Differences 11 - Installing and Administering SSIS Installing SSIS Upgrading SSIS Managing the SSIS Catalog Viewing Built-in SSIS Reports Managing SSIS Logging and Operation Histories Automating Package Execution 12 - Securing the SSIS Catalog Principals Securables Grantable Permissions Granting Permissions Configuring Proxy Accounts Additional course details: Nexus Humans 55321 SQL Server Integration Services 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 55321 SQL Server Integration Services 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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Leading Cross-Cultural Virtual Teams (On-Demand) High-performing teams are a must in this world of intense competition and higher expectations. Global virtual teaming has become a necessity as organizations become increasingly distributed and suppliers and clients actively engage in joint projects. Teams work across geographical and organizational boundaries to deliver solutions and services to global users where distance and differences, both geographic and cultural, amplify the effect of issues and factors that are relatively straightforward when managing a team of people in the same location. This course delivers practical concepts and techniques that participants will start using immediately on their global projects. What you will Learn At the end of this program, you will be able to: Define relationships among foundational concepts (leadership and three dimensions of diversity) and explain their potential impacts on project performance Describe key components of successful project leadership and build selected Transformational Leadership skills Prepare to convert project challenges stemming from personal or cultural diversity into potential competitive advantage Implement selected best practices to meet key challenges facing virtual project teams Foster and grow an environment that supports continued success for CCVTs Getting Started Foundation Concepts Basic definitions Critical success factors for leading cross-cultural virtual teams (CCVTs) A roadmap to success for leading CCVTs Leadership Excellence in Any Project Environment Leading effectively in a global environment Transformational leadership The four components of Transformational Leadership Leveraging Personal Diversity Overview of personal diversity Mind styles The theory of multiple intelligences Connecting Transformational Leadership and personal diversity Embracing Cultural Diversity Introduction to cultural intelligence The impact of culture Cultural Dimensions Theory The Culture Map Managing Virtual Diversity Overview of virtual diversity Virtual time management Virtual processes and technology Virtual leadership Creating an Environment for Success Supporting a cross-cultural virtual-team (CCVT-) friendly environment Building a foundation of trust Developing a team charter Recap and review Summary and Next Steps Personal action plan

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About Course Data Science and Data Analytics with Python: A Comprehensive Course for Beginners Unlock the power of data and gain insights that drive informed decisions with this comprehensive course on data science and data analytics with Python. This course is designed for beginners of all skill levels, with no prior programming experience required. You will learn the essential skills to embark on your data-driven journey, including: Data manipulation with NumPy and Pandas Data visualization with Matplotlib and Seaborn Statistical analysis with Python Machine learning and artificial intelligence You will also gain hands-on experience with real-world data projects, allowing you to apply your newfound knowledge to solve real-world problems. By the end of this course, you will be able to: Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems This course is the perfect launchpad for your data science journey. Whether you are looking to pivot your career, enhance your skill set, or simply quench your curiosity, this course will give you the foundation you need to succeed. Enroll today and start exploring the fascinating world of data science together! What Will You Learn? Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems Course Content Introduction to Python Data Science Introduction to Python Data Science Environment Setup Data Cleaning Packages Working with the Numpy package Working with Pandas Data science package Data Visualization Packages Working with Matplotlib Data Science package (Part - 1) Working with Matplotlib Data Science (Part - 2) A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsBeginners level knowledge for working with Data .Programming knowledge not required. Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics

Duration 2 Days 12 CPD hours This course is intended for This course is aimed at anyone currently working with data who is interested in using data visualisation to more effectively communicate their results. Overview At completion, delegates will understand how data visualisations can be best used to communicate actionable insights from data and be competent with the tools required to do it. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. Course Outline The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding. The companies doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. To attend this course delegates should be competent in the use of data analysis tools such as reporting tools, spreadsheet software or business intelligence tools. The course will explore the following topics through a series of interactive workshop sessions: Fundamentals of data visualisation Data characteristics & dimensions Mapping visual encodings to data dimensions Colour theory Graphical perception & communication Interaction design Visualisation different characteristics of data: trends, comparisons, correlations, maps, networks, hierarchies, text Designing effective dashboards

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