993 Courses

Overview: If you want to gain a solid understanding of Dog Grooming and Dog Training and fast track your dream career, then take a step in the right direction with this industry-standard, comprehensive Dog Grooming and Dog Training designed by expert instructors. The Dog Grooming and Dog Training will help you develop your skills, confidence, and knowledge in this sector, adding real value to your CV and personal development. Dog Grooming and Dog Training has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows. The only thing you need to take Dog Grooming and Dog Training is Wi-Fi and a screen. You'll never be late for class again. Whether you are looking to brighten up your CV, just starting out in the industry, looking for a career change or just fancy learning something new, this online Dog Grooming and Dog Training is perfect! Benefits you'll get choosing Apex Learning for this Dog Grooming and Dog Training course: FREE Dog Grooming and Dog Training CPD-accredited certificate Get a free student ID card with Dog Grooming and Dog Training training (£10 applicable for international delivery) Lifetime access to the Dog Grooming and Dog Training course materials The Dog Grooming and Dog Training program comes with 24/7 tutor support Get instant access to this Dog Grooming and Dog Training course Learn Dog Grooming and Dog Training training from anywhere in the world The Dog Grooming and Dog Training training is affordable and simple to understand The Dog Grooming and Dog Training training is an entirely online Description: Begin your journey with Apex Learning right away! This Dog Grooming and Dog Training diploma offers learners the opportunity to acquire skills that are highly valued in the field of Dog Grooming and Dog Training. With this Certification, graduates are better positioned to pursue career advancement and higher responsibilities within the Dog Grooming and Dog Training setting. The skills and knowledge gained from this Dog Grooming and Dog Training course will enable learners to make meaningful contributions to Dog Grooming and Dog Training-related fields, impacting their experiences and long-term development. ★★★ Course Curriculum of Dog Grooming and Dog Training Bundle ★★★ Course 01: Dog Groomer Training Module 1: The History of Dog Grooming Module 2: Why Do We Groom? Module 3: Anatomy Module 4: Breed Groups and Coat Types Module 5: Equipment and Techniques Module 6: Keep Your Dog Healthy and Clean Module 7: Things to Look for Before You Groom a Dog Module 8: Pre-grooming and General Care Module 9: Preparation Module 10: Skin Conditions Module 11: How to Bathe Your Dog Module 12: How to Get Your Dog to Love Bath Time Module 13: Drying Your Dog After a Bath Module 14: Bathing and Drying: General Considerations Module 15: Grooming Details (Clipping, Scissors, Ears, Teeth, Feet, Bottoms) Module 16: Basic First Aid P.S. The delivery inside the U.K. is Free. International students have to pay a £3.99 postal charge. Who is this Dog Grooming and Dog Training course for? There is no experience or previous certifications required for enrolment in this Dog Grooming and Dog Training. It is available to all students, of all academic backgrounds. Requirements Our Bundle is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This Dog Grooming and Dog Training course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this Dog Grooming and Dog Training course, it can be studied in your own time at your own pace. Career path Having this Dog Grooming and Dog Training CPD certificate will increase the value of your CV and open you up to multiple sectors. Course Curriculum: Module 1: The History of Dog Grooming Module 2: Why Do We Groom? Module 3: Anatomy Module 4: Breed Groups and Coat Types Module 5: Equipment and Techniques Module 6: Keep Your Dog Healthy and Clean Module 7: Things to Look for Before You Groom a Dog Module 8: Pre-grooming and General Care Module 9: Preparation Module 10: Skin Conditions Module 11: How to Bathe Your Dog Module 12: How to Get Your Dog to Love Bath Time Module 13: Drying Your Dog After a Bath Module 14: Bathing and Drying: General Considerations Module 15: Grooming Details (Clipping, Scissors, Ears, Teeth, Feet, Bottoms) Module 16: Basic First Aid

Duration 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

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 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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 intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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.

Course Overview: According to a report by the World Economic Forum, data analysts and scientists are among the top emerging job roles. The "Data Analytics with Tableau" course is tailored to equip learners with the vital skills required to excel in this dynamic field. The course delves into the intricacies of data visualisation and analysis using Tableau, a leading software in the industry. It's not merely about understanding data but transforming it into actionable insights that drive business decisions. The course is structured to provide a comprehensive understanding of various aspects of data analytics, including sales, HR, and shipping analytics.Don't miss this opportunity to advance your career with cutting-edge skills in data analytics. Enrol in "Data Analytics with Tableau" now and embark on a journey of professional growth and endless possibilities! Key Features of the Course: CPD Certificate: Upon completion, you will receive a prestigious Continuing Professional Development (CPD) certificate, recognised globally for enhancing your career prospects. 24/7 Learning Assistance: Our dedicated support team ensures you receive prompt assistance, providing a seamless learning experience. Who is This Course For? This course is tailored for individuals who aspire to become data analysts, business intelligence professionals, marketing strategists, or decision-makers seeking to leverage data effectively. No experience with Tableau or coding is required, making it accessible and engaging for beginners. What You Will Learn: Data Analytics with Tableau, This course covers a wide range of topics, starting with connecting and preparing data, where you will learn how to import, clean, and transform data to make it analysis-ready within Tableau. Next, you will master the art of building insightful charts and visualisations using Tableau's rich set of tools, enabling you to communicate data trends and insights effectively. Additionally, you will explore the creation of captivating headline cards and interactive dashboards, gaining expertise in presenting key information and facilitating data exploration. Real-world projects, including Discount Mart, Green Destinations, Super Store, Northwind Trade, and Tesla, will provide you with outstanding experience in applying Tableau to solve practical data challenges. Lastly, you will develop a solid understanding of database concepts and learn to create compelling data stories using Tableau's storytelling features. By the end of this course, you will have the skills and confidence to make data-driven decisions and communicate insights effectively using Tableau. Why Enrol in This Course: Join the recently updated top-reviewed Data Analytics course with Tableau to keep you at the forefront of the field. Expand your analytical skills, unlock career opportunities, and stay current in the rapidly evolving world of data analytics by mastering Tableau, the industry-standard tool for visual analytics. Requirements: No prior experience with Tableau or coding is required. All you need is a computer with internet access, a curious mind, and a passion for exploring the world of data analytics. Career Path: By acquiring data analytics skills with Tableau, you open doors to exciting career paths, such as: Data Analyst (Average Salary: £35,000 - £45,000) Business Intelligence Analyst (Average Salary: £40,000 - £55,000) Marketing Analyst (Average Salary: £30,000 - £40,000) Financial Analyst (Average Salary: £35,000 - £50,000) Data Visualization Specialist (Average Salary: £40,000 - £60,000) Database Administrator (Average Salary: £40,000 - £55,000) Data Scientist (Average Salary: £45,000 - £70,000) Certification: Upon successful completion of the course, you will receive a CPD certificate, internationally recognised for its validation of your expertise in data analytics with Tableau. Enrol now and embark on a transformative journey to become a proficient data analyst and visualisation expert with Tableau! Course Curriculum 9 sections • 41 lectures • 06:47:00 total length •Introduction to the Course: 00:02:00 •What is Tableau? An Introduction to Tableau: 00:03:00 •How this course is Structured: 00:01:00 •Installing the Free Full Version of Tableau: 00:02:00 •Project Brief for Discount Mart: 00:03:00 •Connecting and Preparing Data for Discount Mart: 00:15:00 •Building Charts on Tableau for Discount Mart (Part 1): 00:33:00 •Building Charts on Tableau for Discount Mart (Part 2): 00:16:00 •Creating Headline Cards on Tableau for Discount Mart: 00:10:00 •Building and Publishing Dashboards on Tableau: 00:15:00 •Project Brief for Green Destinations: 00:02:00 •Connecting and Preparing Data for Green Destinations: 00:09:00 •Building Charts on Tableau (Part 1) for Green Destinations: 00:28:00 •Building Charts on Tableau (Part 2) for Green Destinations: 00:08:00 •Creating Headline Cards on Tableau: 00:15:00 •Building a Dashboard for Green Destinations: 00:12:00 •Publish your Dashboard to Tableau Public: 00:02:00 •Project Brief for Super Store: 00:02:00 •Connecting and Preparing Data for Super Store: 00:17:00 •Building Charts on Tableau (Part 1) for Super Store: 00:34:00 •Building Charts on Tableau (Part 2) for Super Store: 00:23:00 •Building a Dashboard: 00:18:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Project Brief for Northwind Trade: 00:03:00 •Connecting and Preparing Data for Northwind Trade: 00:14:00 •Building Charts on Tableau for Northwind Trade: 00:37:00 •Building and Publishing Dashboards for Northwind Trade: 00:10:00 •Project Brief for Tesla: 00:02:00 •Creating a Data Source through Google Sheet Functions: 00:05:00 •Connect to the Data for Tesla: 00:04:00 •Building Charts on Tableau for Tesla: 00:22:00 •Building Headline Cards: 00:09:00 •Building a Tesla Dashboard: 00:08:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Introduction to Database Concepts: 00:01:00 •Understanding Relational Databases: 00:04:00 •Relationships of Database Entities: 00:02:00 •Primary and Foreign Keys: 00:01:00 •Data types and Naming Conventions: 00:04:00 •Creating Stories on Tableau: 00:05:00 •Resources - Data Analytics with Tableau: 00:00:00

Overview This comprehensive course on Business Intelligence and Data Mining Masterclass will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Business Intelligence and Data Mining Masterclass comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Business Intelligence and Data Mining Masterclass. It is available to all students, of all academic backgrounds. Requirements Our Business Intelligence and Data Mining Masterclass is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 1 sections • 24 lectures • 04:56:00 total length •Module 01: What is Business Intelligence?: 00:05:00 •Module 02: Starting Case in understanding BI needs in diff phase of business: 00:07:00 •Module 03: Decision Making Process and Need of IT systems: 00:20:00 •Module 04: Problem Structure and Decision Support System: 00:11:00 •Module 05: Introduction to BI Applications: 00:18:00 •Module 06: Dashboard presentation systems: 00:07:00 •Module 07: Different Types of Charts used in 131 Dashboards: 00:30:00 •Module 08: Good Dashboard and BSC: 00:13:00 •Module 09: Examples of Bad Dashboards 1: 00:07:00 •Module 10: Examples of Bad Dashboards 2: 00:01:00 •Module 11: Process of KPI Development: 00:26:00 •Module 12: Overview of Data warehouse: 00:08:00 •Module 13: More explaining of data warehouse and steps in processing: 00:09:00 •Module 14: Data Warehouse Architecture -Tiers: 00:18:00 •Module 15: Data Warehouse - components: 00:15:00 •Module 16: Approach to develop data structure and Models of database: 00:16:00 •Module 17: Basics of Data Mining - Meaning: 00:35:00 •Module 18: Basics of Data Mining - Stages of DM: 00:25:00 •Module 19: Data Mining Technique - Classification: 00:07:00 •Module 20: Data mining - Clustering: 00:02:00 •Module 21: Data Mining - Association Rules: 00:05:00 •Module 22: Data Mining Applications - Banking: 00:03:00 •Module 23: Data Mining Applications - CRM: 00:04:00 •Module 24: Data Mining Applications - other industries: 00:04:00

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

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