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Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Duration 2.75 Days 16.5 CPD hours This course is intended for Complete beginners who have never programmed before to experienced developers coming from another programming language. Overview You will learn how to leverage the power of Python to solve tasks. You will build games and programs that use Python libraries. You will be able to use Python for your own work problems or personal projects. You will create a portfolio of Python based projects you can share. Learn to use Python professionally, learning both Python 2 and Python 3! Create games with Python, like Tic Tac Toe and Blackjack! Learn advanced Python features, like the collections module and how to work with timestamps! Learn to use Object Oriented Programming with classes! Understand complex topics, like decorators. Understand how to use both the Jupyter Notebook and create .py files Get an understanding of how to create GUIs in the Jupyter Notebook system! Build a complete understanding of Python from the ground up! Our Introduction to Python course is designed to take complete beginners or experienced developers up to speed on Python?s capabilities, setting up students for success in using Python for their specific field of expertise. Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. Learn how to use Python for real-world tasks, such as working with PDF Files, sending emails, reading Excel files, scraping websites for information, working with image files, and much more! This course will teach you Python in a practical manner and provides a full coding screencast and a corresponding code notebook to review the concepts and exercises conducted in class. Please note, this course is able to be offered in either 3 full day sessions or 5 partial day sessions. See the schedule below. This course includes 6-months access to the full course content in on-demand format to support post-class reference and review. Command Line Basics Python System Setup Jupyter Notebooks Python Data Types Key Data Structures Logic and Control Flow Functions Debugging Modules Object Oriented Programming File I/O Testing Decorators Generators Automation of Tasks Web Scraping Graphical User Interfaces Additional course details: Nexus Humans Introduction to Python 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 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for The introductory-level course is geared for software developers, project managers, and IT professionals seeking to enhance their understanding and practical skills in version control and collaboration using GitLab. It's also well-suited for those transitioning from another version control system to GitLab, or those responsible for software development lifecycle within their organization. Whether you are an individual looking to boost your proficiency or a team leader aiming to drive productivity and collaboration, this course will provide the necessary expertise to make the most of GitLab's capabilities. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Gain a firm understanding of the fundamentals of Git and GitLab, setting a solid foundation for advanced concepts. Learn to effectively manage and track changes in your code, ensuring a clean and reliable codebase. Discover ways to streamline your daily tasks with aliases, stashing, and other GitLab workflow optimization techniques. Develop skills in creating, merging, and synchronizing branches, enabling seamless collaboration and version control. Equip yourself with the knowledge to use Git as a powerful debugging tool, saving time and effort when troubleshooting issues. Understand the basics of continuous integration and continuous deployment (CI/CD) in GitLab, helping you automate the software delivery process. Immerse yourself in the dynamic world of GitLab, a leading web-based platform for version control and collaboration, through our intensive two-day course, GitLab Quick Start. Version control systems, such as GitLab, are the backbone of modern software development, enabling teams to work cohesively and maintain a structured workflow. By mastering GitLab, you can improve efficiency, encourage collaboration, and ensure accuracy and reliability within your projects, adding significant value to your organization. Throughout the course you?ll explore various aspects of GitLab, starting from the fundamental principles of source code management to advanced concepts like rebasing and continuous integration/design. Key topics covered include Git and GitLab basics, reviewing and editing commit history, mastering GitFlow and GitLab Flow, branching and merging strategies, and understanding remote repositories. You'll also learn how to utilize Git as a debugging tool and explore the power of GitLab's built-in CI/CD capabilities. The core value of this course lies in its practical application. You'll learn how to effectively manage changes in code with GitLab, allowing you to maintain audit trails, create reproducible software, and seamlessly move from another version control system. Then you?ll learn how to enhance your workflow efficiency using aliases for common commands, saving changes for later use, and ignoring build artifacts. You?ll also explore GitLab's CI/CD, which will enable you to automate your software delivery process. These hands-on labs will walk you through creating, merging, and synchronizing remote branches, configuring Git, troubleshooting using Git as a debugging tool, and setting up GitLab Runner for CI/CD. Each lab is designed to simulate real-world projects, offering you a first-hand experience in managing and contributing to a version control system like GitLab. Introduction to Source Code Management The Core Principles of Change Management The Power to Undo Changes Audit Trails and Investigations Reproducible Software Changing code-hosting platform Moving from another version control system Git and GitLab Introduction and Basics Introduction to Git GitFlow GitLab Flow Trees and Commits Configuring Git Adding, Renaming, and Removing Files Reviewing and Editing the Commit History Reviewing the Commit History Revision Shortcuts Fixing Mistakes Improving Your Daily Workflow Simplifying Common Commands with Aliases Ignoring Build Artifacts Saving Changes for Later Use (Stashing) Branching Branching Basics Listing Differences Between Branches Visualizing Branches Deleting Branches Tagging Merging Merging Basics Merge Conflicts Merging Remote Branches Remote Repositories Remote Repositories Synchronizing Objects with Remotes Tracking Branches Centralizing and Controlling Access Introduction to GitLab Git Repositories on GitLab Daily Workflow Reviewing Branching and Merging Branch Review Merging Basics Rebasing Rebasing Basics Rebasing with Local Branches Rebasing with Remote Branches Interactive Rebasing Squashing Commits Getting Out of Trouble Git as a Debugging Tool Using the Blame Command to See File History Performing a Binary Search Continuous Integration / Continuous Design (CI/CD) How to install GitLab Runner Adding to our example project Breaking down .gitlab-ci.yml Adding .gitlab-ci.yml to our example project Deconstructing an advanced .gitlab-ci.yml file GitLab CI/CD web UI Optional: Resetting Trees Introduction to Resetting Resetting Branch Pointers Resetting Branches and the Index Resetting the Working Directory Making Good Use of the Reset Command Optional More on Improving Your Daily Workflow Interactively Staging Changes Optional: Including External Repositories Submodules Subtrees Choosing Between Submodules and Subtrees Workflow Management Branch Management

Duration 1 Days 6 CPD hours This course is intended for This course is intended for business professionals in a variety of roles who want to learn about Agile methodologies as a prelude to Agile adoption or migration, and for those who work on projects that require more flexibility and adaptability than traditional project management approaches. Overview In this course, participants will identify the Agile project management principles and use the Scrum methodology of Agile to manage projects. You will: Identify basic concepts, core values, principles, and methodologies of Agile. Address the myths, challenges, and benefits of Agile. Define the Scrum methodology of Agile. Execute sprint ceremonies using Scrum tools and techniques. Agile project management is growing in popularity as a method for delivering value quickly. This course presents the tenets of Agile methodologies using the Scrum framework as a primary example to demonstrate the Agile approaches, their benefits, and challenges. Getting Started with Agile Overview of Agile Core Values of Agile Principles of Agile Common Methodologies of Agile Addressing the Myths, Challenges, and Benefits of Agile Overcome the Myths and Misunderstandings of Agile Overcome the Challenges of Agile The Benefits of Agile Introducing the Scrum Methodology Identify Roles and Responsibilities in Scrum Define the Sprint Ceremonies Executing Sprint Ceremonies Estimate a Scrum Project Conduct a Sprint Planning Meeting Conduct a Sprint Conduct a Sprint Review Meeting Conduct a Sprint Retrospective Meeting Additional course details: Nexus Humans Introduction to Agile and Scrum Methodologies 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 Agile and Scrum Methodologies 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 3.5 Days 21 CPD hours This course is intended for Intermediate Users of Office 365 and Excel Overview Creating Advanced Formulas Analyzing Data with Logical and Lookup Functions Organizing Worksheet Data with Tables Visualizing Data with Charts Analyzing Data with PivotTables, Slicers, and PivotCharts Inserting Graphics Enhancing Workbooks This course builds upon the foundational Microsoft Office Excel 2016, you create advanced workbooks and worksheets using advanced formulas and organizing your data into tables. Excel Intermediate Learn how to navigate Pivot Tables, (for example, Create a Pivot Table/ add data/ Add calculations); Formulas, Data organization (for example, multiple worksheets) Excel Advanced Data Analysis (for example, sparklines) , Macros (making changes to macros) and Building A Fast Dashboard (PivotCharts, slicers, etc.) Office 365 Training Getting More with OneDrive Office 365 Training When is a Team a Team? Includes Using Video with Audio, Exploring Teams/Navigating among Teams etc.

Duration 2 Days 12 CPD hours This course is intended for The primary audience for this course is as follows: Network Video Engineer Voice/UC/Collaboration/Communications Engineer Collaboration Tools Engineer Collaboration Sales/Systems Engineer This is a two day instructor-led course that focuses on the skills and knowledge needed to implement and configure a Cisco TelePresence Management Suite and Cisco TelePresence Management Suite Extensions. Students will configure TMS, TMSPE, TMSXE, VCS and UCM for management of endpoints. Students will also learn to Configure and Schedule Conferencing, Administrative Tasks, Set up Microsoft Active Directory Users, Manage Conferences and Provision Devices. Installing Cisco Telepresence Management Server Windows Server Installation SQL Server Installation Server Pre-requisites and configuration Installing TMS Installing TMS Provisioning Extensions Release and Option Keys Upgrading TMS Backup TMS Configuring Cisco TelePresence Management Suite (TMS) Initial Configuration Endpoint Configuration Adding User Accounts and Profiles Groups and Permissions Active Directory Lookup Configuration Templates Setting Configuration VCS Configuration for TMS Direct Endpoint Management VCS/TMS Direct Managed Endpoint Features CUCM Configuration for TMS Direct Endpoint Management ? CUCM TMS Responsibilities CUCM Responsibilities Findme Configuration Phonebooks & Phonebook Sources Booking Conferencing Conference Creation Advanced Conference Settings Booking & Scheduling Conference Monitoring Dial Plans, Configuration Templates Scheduler/Smart Scheduler Reporting on TMS Reporting Basics Creating a Report Using Reporting Templates Bridge Utilization Call Detail Records Billing Code Statistics Conferences System Managing and Troubleshooting TMS Using the Logs Cisco TMS Ticketing System Troubleshooting VCS Registrations Troubleshooting CUCM Registrations System Maintenance

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Cloud professionals who intend to take the Professional Cloud Architect certification exam. Overview Candidates will be able to identify skill gaps and further areas of study. Candidates will also be directed to appropriate target learning resources. Students in this course will prepare for the Professional Cloud Architect Certification Exam. They will rehearse useful skills including exam question reasoning and case comprehension, tips and review of topics from the Infrastructure curriculum. Understanding the Professional Cloud Architect Certification Position the Professional Cloud Architect certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Cloud Architect and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies MountKirk Games Dress4Win TerramEarth Designing and Implementing Review the layered model from Design and Process Provide exam tips focused on business and technical design Designing a solution infrastructure that meets business requirements Designing a solution infrastructure that meets technical requirements Design network, storage, and compute resources Creating a migration plan Envisioning future solution improvements Resources for learning more about designing and planning Configuring network topologies Configuring individual storage systems Configuring compute systems Resources for learning more about managing and provisioning Designing for security Designing for legal compliance Resources for learning more about security and compliance Optimizing and Operating Analyzing and defining technical processes Analyzing and defining business processes Resources for learning more about analyzing and optimizing processes Designing for security Designing for legal compliance Resources for learning more about security and compliance Advising development/operation teams to ensure successful deployment of the solution Resources for learning more about managing implementation Easy buttons Playbooks Developing a resilient culture Resources for learning more about ensuring reliability Next Steps Present Qwiklabs Challenge Quest for the Professional CA Identify Instructor Led Training courses and what they cover that will be helpful based on skills that might be on the exam Connect candidates to individual Qwiklabs, and to Coursera individual courses and specializations. Review/feedback of course Additional course details: Nexus Humans Preparing for the Professional Cloud Architect Examination 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 Preparing for the Professional Cloud Architect Examination 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 PostgreSQL is a powerful, open-source, object-relational database system known for being reliable, secure, and flexible. For administrators, learning PostgreSQL equips you with the skills needed to handle complex and high-performance databases in our data-driven world. Big-name companies like Apple, Cisco, Fujitsu, and IBM trust PostgreSQL for their critical applications, which highlights its significance and broad industry adoption. By getting the hang of PostgreSQL, administrators can boost their career opportunities and play a key role in the success of data-focused businesses. PostgreSQL Server Administration is a three-day hands-on course geared for administrators seeking to sharpen their skills and elevate their database management capabilities. Throughout the course you?ll explore a wide range of essential topics, from server architecture and user accounts to monitoring and routine maintenance. Throughout the course, you'll gain invaluable insights and practical techniques that will empower you to optimize, secure, and manage your PostgreSQL environment effectively. As you navigate through server configuration, database reporting, backup and restore procedures and more, you'll have the opportunity to apply your newfound knowledge to real-world scenarios. By the end of the course, you'll be equipped with the confidence and skillset required to tackle a wide array of administrative challenges and to effectively manage your PostgreSQL databases. Additional course details: Nexus Humans PostgreSQL Server Administration (TTDB7020) 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 PostgreSQL Server Administration (TTDB7020) 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 4 Days 24 CPD hours This course is intended for This course is for people who have on the job experience doing project management activities and running projects, regardless of their job title. It is for those who wish to become certified project managers, or those that want to build or reinforce a foundation in project management. This course is ideal for a person who wants to grow and formalize their project management skills on an industry neutral, global standard, the Project Management Institute. Overview After completing this course, students will be able to: Demonstrate an understanding of the various project life cycles and processes. Distinguish between predictive and adaptive approaches. Demonstrate an understanding of project management planning. Demonstrate an understanding of project roles and responsibilities. Explain the importance of the role the project manager plays. Determine how to follow and execute and respond to planned strategies or frameworks (e.g., communication, risks, etc.). Demonstrate an understanding of common problem-solving tools and techniques. Identify the suitability of a predictive, plan-based approach for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Determine and give examples of the activities within each process. Demonstrate an understanding of a project management plan schedule. Determine how to document project controls of predictive, plan-based projects. Explain when it is appropriate and sustainable to use an adaptive approach for the organizational structure. Compare the pros and cons of adaptive and predictive, plan-based projects. Identify the suitability of adaptive approaches for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Identify organizational process assets and environmental factors that facilitate the use of adaptive approaches. Determine how to plan project iterations. Determine how to document project controls for an adaptive project. Distinguish between the components of different adaptive methodologies (e.g., Scrum, Extreme Programming (XP), Scaled Adaptive Framework (SAFe), Kanban, etc.). Determine how to prepare and execute task management steps. Demonstrate an understanding of business analysis (BA) roles and responsibilities. Demonstrate the importance of communication for a business analyst between various teams and stakeholders. Determine how to gather requirements and using the best approach for a situation. Explain the application of a product roadmap. Determine how project methodologies influence business analysis processes. Validate requirements through product delivery. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks.