1628 Database courses in Radcliffe delivered Online

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 5 Days 30 CPD hours This course is intended for This course is primarily intended for existing IT professionals who have some AD DS knowledge and experience and who aim to develop knowledge about identity and access technologies in Windows Server 2016. The secondary audience for this course includes IT professionals who are looking to consolidate their knowledge about AD DS and related technologies, in addition to IT professionals who want to prepare for the 70-742 exam. Overview After completing this course, students will be able to:Install and configure domain controllers.Manage objects in AD DS by using graphical tools and Windows PowerShell.Implement AD DS in complex environments.Implement AD DS sites, and configure and manage replication.Implement and manage Group Policy Objects (GPOs).Manage user settings by using GPOs.Secure AD DS and user accounts.Implement and manage a certificate authority (CA) hierarchy with AD CS.Deploy and manage certificates.Implement and administer AD FS.Implement and administer Active Directory Rights Management Services (AD RMS).Implement synchronization between AD DS and Azure AD.Monitor, troubleshoot, and establish business continuity for AD DS services. This course teaches IT Pros how to deploy and configure Active Directory Domain Services in a distributed environment, how to implement Group Policy, how to perform backup & restore, & how to troubleshoot Active Directory?related issues. Installing & Configuring DCs Overview of AD DS Overview of AD DS DCs Deploying DCs Lab: Deploying and administering AD DS Managing Objects in AD DS Managing user accounts Managing groups in AD DS Managing computer accounts Using Windows PowerShell for AD DS administration Implementing and managing organizational units Lab: Deploying and administering AD DS Lab: Administering AD DS Advanced AD DS Infrastructure Management Overview of advanced AD DS deployments Deploying a distributed AD DS environment Configuring AD DS trusts Lab: Domain and trust management in AD DS Implementing & Administering AD DS Sites & Replication Overview of AD DS replication Configuring AD DS sites Configuring and monitoring AD DS replication Lab: Managing and implementing AD DS sites and replication Implementing Group Policy Introducing Group Policy Implementing and administering GPOs Group Policy scope and Group Policy processing Troubleshooting the application of GPOs Lab: Implementing a Group Policy infrastructure Lab: Troubleshooting a Group Policy Infrastructure Managing User Settings with GPOs Implementing administrative templates Configuring Folder Redirection and scripts Configuring Group Policy preferences Lab: Managing user settings with GPOs Securing AD DS Securing domain controllers Implementing account security Audit authentication Configuring managed service accounts (MSAs) Lab: Securing AD DS Deploying & Managing AD CS Deploying CAs Administering CAs Troubleshooting and maintaining CAs Lab: Deploying and configuring a two-tier CA hierarchy Deploying & Managing Certificates Deploying and managing certificate templates Managing certificate deployment, revocation, and recovery Using certificates in a business environment Implementing and managing smart cards Lab: Deploying certificates Implementing & Administering AD FS Overview of AD FS AD FS requirements and planning Deploying and configuring AD FS Overview of Web Application Proxy Lab: Implementing AD FS Implementing & Administering AD RMS Overview of AD RMS Deploying and managing an AD RMS infrastructure Configuring AD RMS content protection Lab: Implementing an AD RMS infrastructure Implementing AD DS Synchronization with Azure AD Planning and preparing for directory synchronization Implementing directory synchronization by using Azure AD Connect Managing identities with directory synchronization Lab: Configuring directory synchronization Monitoring, Managing, & Recovering AD DS Monitoring AD DS Managing the AD DS database Recovering AD DS objects Lab: Recovering objects in AD DS

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Intermediate software developers Overview In this course, you will learn to: Set up the AWS SDK and developer credentials for Java, C#/.NET, Python, and JavaScript Interact with AWS services and develop solutions by using the AWS SDK Use AWS Identity and Access Management (IAM) for service authentication Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions Use Amazon Cognito for user authentication Use Amazon ElastiCache to improve application scalability Leverage the CI/CD pipeline to deploy applications on AWS In this course, you learn how to use the AWS SDK to develop secure and scalable cloud applications using multiple AWS services such as Amazon DynamoDB, Amazon Simple Storage Service, and AWS Lambda. You explore how to interact with AWS using code and learn about key concepts, best practices, and troubleshooting tips. Module 0: Course Overview Agenda Introductions Student resources Module 1: Introduction to AWS Introduction to the AWS Cloud Cloud scenarios Infrastructure overview Introduction to AWS foundation services Module 2: Introduction to Developing on AWS Getting started with developing on AWS Introduction to developer tools Introduction to management tools Module 3: Introduction to AWS Identity and Access Management Shared responsibility model Introduction to IAM Use authentication and authorization Module 4: Introduction to the Lab Environment Introduction to the lab environment Lab 1: Getting started and working with IAM Module 5: Developing Storage Solutions with Amazon Simple Storage Service Overview of AWS storage options Amazon S3 key concepts Best practices Troubleshooting Scenario: Building a complete application Lab 2: Developing storage solutions with Amazon S3 Module 6: Developing Flexible NoSQL Solutions with Amazon DynamoDB Introduction to AWS database options Introduction to Amazon DynamoDB Developing with DynamoDB Best practices Troubleshooting Scenario: Building an end-to-end app Lab 3: Developing flexible NoSQL solutions with Amazon DynamoDB Module 7: Developing Event-Driven Solutions with AWS Lambda What is serverless computing? Introduction to AWS Lambda Key concepts How Lambda works Use cases Best practices Scenario: Build an end-to-end app Module 8: Developing Solutions with Amazon API Gateway Introduction to Amazon API Gateway Developing with API Gateway Best practices Introduction to AWS Serverless Application Model Scenario: Building an end-to-end app Lab 4: Developing event-driven solutions with AWS Lambda Module 9: Developing Solutions with AWS Step Functions Understanding the need for Step Functions Introduction to AWS Step Functions Use cases Module 10: Developing Solutions with Amazon Simple Queue Service and Amazon Simple Notification Service Why use a queueing service? Developing with Amazon Simple Queue Service Developing with Amazon Simple Notification Service Developing with Amazon MQ Lab 5: Developing messaging solutions with Amazon SQS and Amazon SNS Module 11: Caching Information with Amazon ElastiCache Caching overview Caching with Amazon ElastiCache Caching strategies Module 12: Developing Secure Applications Securing your applications Authenticating your applications to AWS Authenticating your customers Scenario: Building an end-to-end app Module 13: Deploying Applications Introduction to DevOps Introduction to deployment and testing strategies Deploying applications with AWS Elastic Beanstalk Scenario: Building an end-to-end app Lab 6: Building an end-to-end app Module 14: Course wrap-up Course overview AWS training courses Certifications Course feedback

Duration 2 Days 12 CPD hours Overview Install and initialize WEM and integrate into Citrix Virtual Apps and Desktops and Citrix DaaS. Configure WEM features to improve the end user environment and virtual resource consumption. Migrate an on-premises WEM deployment to WEM service Designed for experienced IT professionals, you will discover why WEM is the go-to system optimization and logon optimization solution for a Citrix deployment's app and desktop workloads. You will learn how to plan, build, rollout, and manage on-premises WEM or WEM service and how to integrate it into Citrix Virtual Apps and Desktops or Citrix DaaS. You will leave this course with a good understanding of how to manage additional solutions and features in your Citrix Virtual Apps and Desktop or Citrix DaaS site Module 1: Introduction to Workspace Environment Management (WEM) WEM Features and Benefits Module 2: Planning ? WEM Architecture and Component Communications WEM On-Premises Components and Deployments WEM Service Components and Deployments WEM Component Communication Workflows Module 3: Planning - WEM On-Premises Deployment Installation On-Premises WEM: Leading Practice Installation Prerequisites and Steps On-Premises WEM: ADMX Template Configuration Choosing a Security Principal to run the WEM Infrastructure Service Creating the WEM Database Running the WEM Infrastructure Service Configuration Utility On-Premises WEM: Agent Installation Module 4: Planning ? WEM Service Deployment Installation WEM On-Premises vs WEM Service WEM Service: Leading Practice Installation Prerequisites and Steps WEM Service: ADMX Template Configuration WEM Service: Agent Installation Module 5: Planning ? WEM Consoles and Initial Setup On-Premises WEM and WEM Service Consoles WEM Initial Setup Migrating GPO settings to WEM Module 6: Planning ? WEM System and Log On Optimization WEM System Optimization Overview WEM CPU Management WEM Memory Management Additional System Optimization Features WEM Log On Optimization Overview WEM Assigned Actions WEM Environmental Settings Citrix Profile Management In WEM Module 7: Planning ? WEM Security and Lockdown Features WEM Security Management Features Privilege Elevation and Process Hierarchy Control WEM Transformer Module 8: Planning - The WEM Agent WEM Settings Processing and WEM Agent Caches WEM Agent Integration with Citrix Virtual Apps and Desktops and Citrix DaaS Module 9: Planning ? WEM Monitoring, Reporting, and Troubleshooting WEM Monitoring and Reporting WEM Agent Troubleshooting WEM Service Troubleshooting Module 10: Planning ? Upgrading WEM and Migration to WEM Service Upgrading Workspace Environment Management WEM On-Premises Migration to WEM Service Module 11: Rolling Out a WEM Deployment WEM Agent User Options on Windows Desktops Module 12: Managing a WEM Deployment Measuring WEM Success Additional course details: Nexus Humans CWS-220 Citrix Workspace Environment Management Deployment and Administration 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 CWS-220 Citrix Workspace Environment Management Deployment and Administration course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for Senior Executives CIOs and CTOs Business Intelligence Executives Marketing Executives Data & Business Analytics Specialists Innovation Specialists & Entrepreneurs Academics, and other people interested in Big Data Overview More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection. Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students. Workshop Application Use Cases Oz Metropolitan Architectural questions Team activity: Analyze Metroz Application Use Cases Application Vertical Slice Definition Minimizing risk of an unsound architecture Selecting a vertical slice Team activity: Identify an initial vertical slice for Metroz Application Processing Real time, near real time processing Batch processing Data access patterns Delivery and processing guarantees Machine Learning pipelines Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines Application Data Three V?s of Big Data Data Lifecycle Data Formats Transforming Data Team activity: Metroz Data Requirements Scalable Applications Scale up, scale out, scale to X Determining if an application will scale Poll: scalable airport terminal designs Hadoop and Spark Scalability Team activity: Scaling Metroz Fault Tolerant Distributed Systems Principles Transparency Hardware vs. Software redundancy Tolerating disasters Stateless functional fault tolerance Stateful fault tolerance Replication and group consistency Fault tolerance in Spark and Map Reduce Application tolerance for failures Team activity: Identify Metroz component failures and requirements Security and Privacy Principles Privacy Threats Technologies Team activity: identify threats and security mechanisms in Metroz Deployment Cluster sizing and evolution On-premise vs. Cloud Edge computing Team activity: select deployment for Metroz Technology Selection HDFS HBase Kudu Relational Database Management Systems Map Reduce Spark, including streaming, SparkSQL and SparkML Hive Impala Cloudera Search Data Sets and Formats Team activity: technologies relevant to Metroz Software Architecture Architecture artifacts One platform or multiple, lambda architecture Team activity: produce high level architecture, selected technologies, revisit vertical slice Vertical Slice demonstration Additional course details: Nexus Humans Big Data Architecture Workshop 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 Big Data Architecture Workshop course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create a data-driven application. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution.   Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files Additional course details: Nexus Humans Advanced Programming Techniques with 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 Advanced Programming Techniques with 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.

Register on the Data Analysis and Forecasting in Excel today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Data Analysis and Forecasting in Excel is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Data Analysis and Forecasting in Excel Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Data Analysis and Forecasting in Excel, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Data Analysis and Forecasting in Excel Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:06:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:13:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:08:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:06:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:09:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:09:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:06:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Duration 5 Days 30 CPD hours This course is intended for This introductory-level Python course is geared for experienced web developers new to Python who want to use Python and Django for full stack web development projects. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Develop full-stack web sites based on content stored in an RDMS Use python data types appropriately Define data models Understand the architecture of a Django-based web site Create Django templates for easy-to-modify views Map views to URLs Take advantage of the built-in Admin interface Provide HTML form processing Geared for experienced web developers new to Python, Introduction to Full Stack Web Development with Python and Django is a five-day hands-on course that teaches students how to develop Web applications using the Django framework. Students will explore the basics of creating basic applications using the MVC (model-view-controller) design pattern, as well as more advanced topics such as administration, session management, authentication, and automated testing. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar. Students will immediately be able to use Python to complete tasks in the real world. The Python Environment Starting Python Using the interpreter Running a Python script Getting help Editors and IDEs Getting Started Using variables Built in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control Conditional expressions Relational and Boolean operators while loops Lists and Tuples About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Working with Files File overview The with statement Opening a file Reading/writing files Dictionaries and Sets About dictionaries Creating and using dictionaries About sets Creating and using sets Functions Returning values Function parameters Variable Scope Sorting with functions Errors and Exception Handling Exception overview Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Creating packages Classes About OO programming Defining classes Constructors Properties Instance methods and data Class/static methods and data Inheritance Django Architecture Django overview Sites and apps Shared configuration Minimal Django layout Built in flexibility Configuring a Project Executing manage.py Starting the project Generating app files App configuration Database setup The development server Using cookiecutter Creating models Defining models Related objects SQL Migration Simplel model access Login for Nothing and Admin for Free Setting up the admin user Using the admin interface Views What is a view HttpResponse URL route configuration Shortcut: get_object_or_404() Class-based views Templates About templates Variable lookups The url tag Shortcut: render() Querying Models QuerySets Field lookups Chaining filters Slicing QuerySets Related fields Q objects Advanced Templates Use Comments Inheritance Filters Escaping HTML Custom filters Forms Forms overview GET and POST The Form class Processing the form Widgets Validation Forms in templates Automated Testing Why create tests? When to create tests Using Django's test framework Using the test client Running tests Checking code coverage

Overview The Computer Programming Specialist Certificates course covers fundamental concepts of computer programming, including basic terms, computer anatomy, software development, networking, internet security, application basics, web browsing, file management, and more. Participants will gain the necessary skills to become proficient in computer programming. Learning Outcomes: Develop a strong understanding of basic computer terms, the anatomy of a PC, and how a PC works. Gain knowledge about different types of software, operating systems, and legal issues related to computer programming. Learn about networking basics, internet concepts, internet security, and the role of computers in the workplace. Understand the basics of application development and working with various applications. Acquire skills in web browsing, managing web pages, and working with bookmarks. Learn how to manage files and folders, customize computer settings, and perform basic tasks on a computer. Familiarize yourself with printing techniques, file compression, and maintaining data security. Why buy this Computer Programming Specialist Certificate? 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 Computer Programming Specialist Certificate 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? Aspiring software developers seeking foundational knowledge. Individuals interested in a career shift to technology sectors. University students supplementing their IT or Computer Science degrees. Entrepreneurs needing coding skills for tech startups. Hobbyists eager to create personal digital projects. Prerequisites This Computer Programming Specialist Certificate does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Computer Programming Specialist Certificate 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 Software Developer: £25,000 - £70,000 Per Annum Database Administrator: £30,000 - £60,000 Per Annum Systems Analyst: £35,000 - £65,000 Per Annum Web Developer: £24,000 - £50,000 Per Annum IT Project Manager: £40,000 - £80,000 Per Annum Data Analyst: £26,000 - £60,000 Per Annum Course Curriculum Module 01 Basic Terms 00:15:00 Types of Computers 00:15:00 Anatomy of a PC 00:30:00 How a PC Works 00:15:00 CPU and Memory 00:30:00 Input Devices 00:15:00 Output Devices 00:15:00 Secondary Storage Devices 00:30:00 The Basics 00:15:00 Operating Systems and Applications 00:30:00 How is Software Built 00:15:00 Types of Software 00:15:00 Legal Issues 00:15:00 Module 02 Basic Terms 00:15:00 Advanced Terms 00:15:00 Networking Basics 00:15:00 Basic Internet Concepts 00:30:00 Internet Security 00:30:00 Computers in the Workplace 00:15:00 Tele-Commuting 00:15:00 The Electronic World 00:15:00 Ergonomics 00:15:00 Safety and the Environment 00:15:00 Being Proactive 00:15:00 Identifying Yourself 00:15:00 Protecting Your Data 01:00:00 Understanding Malware 00:15:00 Protecting Against Malware 00:15:00 Module 03 Application Basics 00:30:00 Basic Applications 01:00:00 Working with a Window 01:00:00 Working with WordPad 01:00:00 Working With Applications 01:00:00 Basics of Web Browsers 01:00:00 Browsing the Web 00:15:00 Working with Bookmarks 01:00:00 Working With Web Pages 01:00:00 Printing Web Pages 01:00:00 Module 04 First Steps 00:30:00 Basic Tasks 01:00:00 Using the Desktop 00:15:00 Customizing Your Computer 00:15:00 Printing 00:15:00 The Basics of Files and Folders 00:10:00 Managing Files and Folders, Part I 01:00:00 Managing Files and Folders, Part II 00:15:00 Viewing File or Folder Properties 00:30:00 Working With Files and Folders 00:30:00 Compressed Files 00:05:00 Assignment Assignment - Computer Programming Specialist Certificate 00:00:00

In the digital age, the ability to interpret and predict data trends is paramount. Introducing 'Data Analysis and Forecasting in Excel', a comprehensive course tailored to unveil the intricacies of Excel's powerful tools. Dive deep into the world of worksheets, discover the magic of PivotTables, and unravel the secrets of data visualisation. Whether you're a novice eager to delve into data or a seasoned analyst looking to refine your skills, this course promises a transformative journey into the realm of Excel analytics. The curriculum is designed with the utmost care to ensure a holistic understanding. From the basics of modifying worksheets to the advanced techniques of forecasting data, every module is a step towards mastering Excel. With a focus on real-world applications, learners will be equipped to harness the potential of Excel, making data-driven decisions with confidence and precision. Visualisation is at the heart of understanding data. This course not only teaches you how to analyse data but also how to represent it effectively using charts, PivotCharts, and the innovative Sparklines. By the end of this course, you'll be adept at mapping data, automating workbook functionalities, and employing lookup functions with finesse. Learning Outcomes: Master the techniques of modifying and organising worksheets for optimal data representation. Understand and implement effective list management strategies within Excel. Analyse complex datasets and derive meaningful insights. Design and create compelling visual representations using charts and other visual tools. Efficiently utilise PivotTables and PivotCharts for advanced data analysis. Integrate and manage data across multiple worksheets and workbooks. Implement lookup functions and audit formulas to ensure data accuracy and integrity. Why buy this Data Analysis and Forecasting in Excel course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Data Analysis and Forecasting in Excel 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 Who is this Data Analysis and Forecasting in Excel course for? Individuals keen on mastering Excel for data interpretation and visualisation. Business analysts aiming to enhance their data forecasting abilities. Students pursuing a career in data analytics or business intelligence. Managers and decision-makers seeking to make data-driven strategies. Researchers looking to streamline and enhance their data processing techniques. Career path Data Analyst: Average salary range £30,000 - £50,000 annually. Business Intelligence Analyst: Average salary range £35,000 - £55,000 annually. Market Research Analyst: Average salary range £27,000 - £45,000 annually. Financial Analyst: Average salary range £35,000 - £60,000 annually. Operations Research Analyst: Average salary range £40,000 - £65,000 annually. Management Analyst: Average salary range £45,000 - £70,000 annually. Prerequisites This Data Analysis and Forecasting in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Analysis and Forecasting in Excel 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00