Duration 2 Days 12 CPD hours This course is intended for This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards in Excel. To ensure success, you should have baseline skill using Microsoft Excel worksheets, particularly in creating workbooks with formulas and function Overview #NAME? Analyzing data to find issues, insights and opportunities, is now a critical part of many job roles. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways. Microsoft© Excel© is designed for this purpose. Excel can connect to a wide range of data sources, perform robust data analysis and create diverse and robust data-backed visualizations to show insights, trends, and create reports. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action. 1 - DATA ANALYSIS FUNDAMENTALS Introduction to Data Science Create and Modify Tables Sort and Filter Data 2 - VISUALIZING DATA WITH EXCEL Visualize Data with Charts Modify and Format Charts Apply Best Practices in Chart Design 3 - ANALYZING DATA WITH FORMULAS AND FUNCTIONS Analyze Data with Formulas and Named Ranges Analyze Data with Functions Implement Data Validation, Forms, and Controls Create Conditional Visualizations with Lookup Functions 4 - ANALYZING DATA WITH PIVOTTABLES Create a PivotTable Analyze PivotTable Data 5 - PRESENTING VISUAL INSIGHTS WITH DASHBOARDS IN EXCEL Visualize Data with PivotCharts Filter Data Using Slicers and Timelines Create a Dashboard in Excel 6 - CREATING GEOSPATIAL VISUALIZATIONS WITH EXCEL Create Map Charts in Excel Customize Map Charts in Excel 7 - PERFORMING STATISTICAL ANALYSIS Visualize Trendlines and Sparklines with Excel Analyze Data with the Data Analysis ToolPa 8 - GETTING AND TRANSFORMING DATA Connect to Data with Queries Clean and Combine Data Shape and Transform Data 9 - MODELING AND ANALYZING DATA WITH POWER PIVOT Install Power Pivot in Excel Create Data Models with Power Pivot Create Power Pivots Perform Advanced Data Analysis and Visualization 10 - PRESENTING INSIGHTS WITH REPORTS (OPTIONAL) Plan a Report Create a Report
Are you ready to dive deep into the world of data analytics? Look no further than our Data Analytics with Tableau bundle, featuring 11 comprehensive courses that will give you the skills and knowledge needed to succeed in the world of data analysis. Begin with the QLS-endorsed Advanced Diploma in Data Analytics with Tableau at QLS Level 6, and receive a free hardcopy certificate upon completion. This prestigious certification will set you apart from your peers. Continue your learning journey with ten additional courses, all CPD-QS accredited, covering everything from SQL Masterclass to GDPR compliance. Our courses are designed to provide a theoretical understanding of data analytics that will serve as a strong foundation for your future career in the field. Whether you're just starting out in data analytics or are a seasoned professional looking to expand your knowledge, our Data Analytics with Tableau bundle is the perfect choice for you. Enrol now and take the first step towards a brighter future in the exciting world of data analytics. This Data Analytics with Tableau Bundle Package includes: Course 01: Advanced Diploma in Data Analytics with Tableau at QLS Level 6 10 Premium Additional CPD QS Accredited Courses - Course 01: Data Analysis Course 02: SQL Masterclass: SQL For Data Analytics Course 03: Data Science & Machine Learning with R Training Course 04: Google Data Studio Course 05: Excel Data Analysis Course 06: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 07: Business Intelligence and Data Mining Diploma Course 08: Business Data Analysis Course 09: Statistical Analysis Course 10: GDPR Why Prefer This Data Analytics with Tableau 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 Data Analytics with Tableau bundle courses, you will be able to learn: Gain a thorough understanding of data analytics concepts and tools. Master Tableau and Excel for data analysis and visualisation. Learn how to work with SQL and relational databases for data management. Develop skills in data science and machine learning using R. Understand the principles of business intelligence and data mining. Gain knowledge of statistical analysis and interpretation of results. Acquire a comprehensive understanding of GDPR compliance and regulations. ***Curriculum breakdown of Data Analytics with Tableau*** Module 01: Introduction to the Course Module 02: Project 1: Discount Mart (Sales and Profit Analytics) Module 03: Project 2: Green Destinations (HR Analytics) Module 04: Project 3: Superstore (Sales Agent Tracker) Module 05: Northwind Trade (Shipping Analytics) Module 06: Project 5: Tesla (Stock Price Analytics) Module 07: Bonus: Introduction to Database Concepts Module 08: Tableau Stories How is the Data Analytics with TableauBundle 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 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals interested in pursuing a career in data analytics. Professionals seeking to enhance their data analysis skills. Business analysts, data scientists, and statisticians. Anyone looking to gain a theoretical foundation in data analytics. Career path Data Analyst: £20k-£48k per year Business Intelligence Analyst: £24k-£60k per year Data Scientist: £33k-£75k per year Business Analyst: £24k-£50k per year Data Engineer: £28k-£80k per year Statistician: £25k-£45k per year Note: Salary ranges are subject to change depending on location, experience, and industry. Certificates Advanced Diploma in Data Analytics with Tableau at QLS Level 6 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 License 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.
Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution
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Let's learn the basic concepts for developing chatbots with machine learning models. This compact course will help you learn to use the power of Python to evaluate your chatbot datasets based on conversational notes, online resources, and websites. Garner hands-on practice in text generation with Python for chatbot development.
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Here's what you get: Step by step IT Security Specialist Diploma lessons One to one assistance from IT Security Specialist Diplomaprofessionals if you need it Innovative exams to test your knowledge after the IT Security Specialist Diplomacourse 24/7 customer support should you encounter any hiccups Top-class learning portal Unlimited lifetime access to all twenty-five IT Security Specialist Diploma courses Digital Certificate, Transcript and student ID are all included in the price PDF certificate immediately after passing Original copies of your IT Security Specialist Diploma certificate and transcript on the next working day Easily learn the IT Security Specialist Diploma skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This IT Security Specialist Diploma training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in IT Security Specialist Diploma Requirements To participate in this IT Security Specialist Diploma course, all you need is - A smart device A secure internet connection And a keen interest in IT Security Specialist Diploma Career path You will be able to kickstart your IT Security Specialist Diploma career because this course includes various courses as a bonus. This IT Security Specialist Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore IT Security Specialist Diploma career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
Learn Python OOP language used diversely in applications like data science, game/web development, machine learning, and AI. This course provides all you need to master OOPs like classes, objects, data abstraction, methods, overloading, and inheritance. The course primarily aims to help you tackle complex programming and use OOP paradigms efficiently.
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The course is crafted to help you understand not only the role and impact of recommender systems in real-world applications but also provide hands-on experience in developing complete recommender systems engines for your customized dataset using projects. This learning-by-doing course will help you master the concepts and methodology of Python.