Description: Microsoft Access is a database management system that has lots of features and functions to offer. To create mailing labels, work with SQL and publish a Web database in Microsoft Access, you need to learn at an advanced level. Through this course, you will learn the advanced skills, knowledge, and information about Microsoft Access 2010. You can then create and use the advanced forms and tasks to do even more in Access.In this course you will learn the necessary skills, knowledge and information of Microsoft Access 2010. Who is the course for? Professionals who want to learn about the Microsoft Access 2010 People who have an interest in the advanced features of the Access 2010 Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: The Microsoft Access 2010 Advanced Level course is a useful qualification to possess and would be beneficial for following careers: Software Engineer Technical Support Technical Sales Business Analyst Web Developer Software Tester. Microsoft Access 2010 Advanced Level Module One - Getting Started 00:30:00 Module Two - Advanced Table Tasks 01:00:00 Module Three - Advanced Form Tasks 01:00:00 Module Four - Advanced Reporting Tasks 01:00:00 Module Five - Understanding Relationships 01:00:00 Module Six - Advanced Query Tasks 01:00:00 Module Seven - Working with SQL 01:00:00 Module Eight - Linking Data 01:00:00 Module Nine - Importing Data 01:00:00 Module Ten - Exporting Data 01:00:00 Module Eleven - Advanced Database Tools 01:00:00 Module Twelve - Wrapping Up 00:30:00 Activities Activities - Microsoft Access 2010 Advanced Level 00:00:00 Mock Exam Mock Exam-Microsoft Access 2010 Advanced Level 00:20:00 Final Exam Final Exam-Microsoft Access 2010 Advanced Level 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
If you are a newbie in the field of ethical hacking or want to become an ethical hacker, this course is just what will get you started. This is a comprehensive course with real-world examples to help you understand the fundamentals of hacking and cyber security.
Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.
Data Analyst Course is Now The Most Demanding Course to Advance Your Career! Data Analysis Course is for those who want to advance in this field. Throughout this course, you will learn the essential skills and gain the knowledge needed to become well versed in Data Analyst. Data Analyst course includes: Course 01: Diploma in Data Analysis Fundamentals Course 02: Excel Pivot Tables for Data Reporting Course 03: Complete Microsoft SQL Server from Scratch: Bootcamp Our course starts with the basics of Data Analysis and gradually progresses towards advanced topics. Therefore, each lesson of this course intuitive and easy to understand. Data Analyst Course Learning Outcomes: Upon successful completion of this highly appreciated Data Analysis Course, you'll be a skilled professional, besides- You can provide services related to Data Analysis with complete knowledge and confidence. You'll be competent and proficient enough to start a Data Analytics related Data Analyst on your own. Furthermore, you can train up others and grow an efficient peer community on your locality and serve people. It will enhance your portfolio, you can use the certificate as proof of your efficiency to the employer. It will boost up your productivity, you can use the skill and credentials, and become more competent in your vocation with increased earning! So, stand out in the job market by completing the Data Analyst (Data Analytics) Course. Get an accredited certificate and add it to your resume to impress your employers. Along with the Data Analysis course, you also get: Lifetime Access Unlimited Retake Exam & Tutor Support Easy Accessibility to the Course Materials- Anytime, Anywhere - From Any Smart Device (Laptop, Tablet, Smartphone Etc.) 100% Learning Satisfaction Guarantee Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny, bite-sized modules by industry specialists. And you will get answers to all your queries from our experts. So, enrol and excel in your career with Compliance Central. Curriculum Topics: Agenda and Principle Process Voice of Customer Data Analysis Tools Pareto Chart, Histogram, Run Chart, Control Chart Data Performance Presentation Pivot Table Fundamental SQL Statement Basics and Operations CPD 40 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Data Analysis course. Requirements To enrol in this Data Analysis course, all you need is a basic understanding of the English Language and an internet connection. Career path After completing this course, you can explore trendy and in-demand jobs related to Data Analysis. Data Analyst: £25,000 to £45,000 per year Business Intelligence Analyst: £30,000 to £55,000 per year Data Scientist: £35,000 to £65,000 per year Data Engineer: £40,000 to £70,000 per year Market Research Analyst: £22,000 to £40,000 per year Database Administrator: £30,000 to £55,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included 3 CPD Accredited PDF Certificate Hard copy certificate Hard copy certificate - £9.99 CPD Accredited Hard Copy Certificate for £9.99 each. Delivery Charge: Inside the UK: Free Outside of the UK: £9.99
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Duration 1 Days 6 CPD hours This course is intended for The intended audience for this course would be those who have been using Office 365 for some time and are now looking at optimizing their existing business processes and designing new ones. Overview #NAME? This course delivers an instructor-led product showcase for Microsoft Power Automate from start to finish in an engaging and practical way. Power Automate is a diverse product, turning business processes into automated, consistent and visual workPower Automates. Power Automate is designed to interweave the various products in Office 365 as well as connect to other on-premises and web-based solutions. This course will give you the confidence to select the right actions and workPower Automate logic for your business workPower Automates. 1 - An Introduction to Power Automate What is Microsoft Power Automate? The benefits of automation How to get to Power Automate Lab 1: Setup your tenant Setup Office 365 Download Course Files Customise your App Launcher Create accounts for colleagues After completing this module, students will be able to: Know what Microsoft Power Automate is The Benefits of using Power Automate to automate processes How to access a Power Automate 2 - Getting Started with Power Automate Using Power Automate templates Navigating in Power Automate Editing a Power Automate Publish and trigger a Power Automate Turn off or delete a Power Automate Lab 1: Building processes in Office 365 Create a Team with a channel Build an absence business process Testing the absence process Optional: Create Feedback Form Optional: Power Automate to Notify of Bad Ratings Optional: Test your Form and Power Automate After completing this module, students will be able to: How to use Power Automate tempaltes How to navigate around Power Automate How to edit Power Automates How to publish and trigger Power Automates How to turn off or delete Power Automates 3 - Power Automate Logic Adding conditions Designing switches Using apply to each Configuring do until logic Adding a scope Lab 1: Scheduling documentation reviews Setup a policy library in SharePoint Design a policy review schedule Testing the policy review process Optional: Notify if a file nears review After completing this module, students will be able to: How to add condtions in a Power Automate How to design switches for a Power Automate How to use apply to each How to configure do until logic How to add a scope 4 - Integration Standard and premium connectors Connecting to web services Using Power Automate with on-premises data Lab 1: Using Power Automate and SQL to Review Sales Create a new orders list Designing the price check process Testing the price check process Optional: Update with managers After completing this module, students will be able to: How to use Standard and Premium connectors How to connect to web services How to using Power Automate with on-premises data 5 - The Mobile App Downloading the mobile app Signing in and account management Building and managing Power Automates Creating buttons Feeds and approvals Lab 1: Optional: Using the Power Automate mobile app Setting up the Power Automate mobile app Create a new Power Automate in the mobile app Using Power Automate buttons in the app Uninstall the Power Automate mobile app After completing this module, students will be able to: How to download the mobile app How to sign into the mobile app How to build and manage Power Automates in the mobile app How to create buttons in the mobile app How to feed and use approvals in the mobile app 6 - Administration and Maintenance Maintaining a Power Automate View history and analytics Sharing a Power Automate Export and import Power Automates Office 365 administration for Power Automate Environments Data policies Data integration Lab 1: Maintaining your Power Automates Share a Power Automate with a colleague Disabling an active Power Automate Deleting a Power Automate After completing this module, students will be able to: How to maintain a Power Automate How to view history and analytics for a Power Automate How to share a Power Automate How to export and import Power Automates How to administrate a Power Automate in Office 365 How to use data policies in a Power Automate How to use data integration in a Power Automate
Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.
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