145 Data Analysis courses in Leicester delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Duration 5 Days 30 CPD hours This course is intended for The audience includes implementers, developers, system administrators, project teams, database administrators and engine project technical teams. The audience also includes consultants that are looking to gain an understanding of Maximo Asset Management 7.6.0.x and the engine. Overview After completing this course, you should be able to perform the following tasks: List the components of Tivoli's process automation engine Understand Maximo modules and applications Understand Tivoli's Process Automation Engine Create the foundation data necessary for Maximo Asset Management Customize the engine database and applications Automate IBM Service Management applications using workflows Use the Maximo Work Centers Use the Integration Framework to import and export data This course is designed for anyone planning to use Maximo Asset Management and Tivoli?s process automation engine with one of the IBM System Management (ISM) products. It is a course that introduces you to the features and functions of both products. IBM Maximo Asset Management Overview This unit focuses on Maximo as an overall product and how Maximo assists companies with their asset management lifecycle. Tivoli Process Automation Engine This unit describes the functions of Tivoli?s process automation engine and introduces the products that are based on the engine. This unit also introduces Start Centers and basic navigation. Architecture and components This unit covers the architecture of Tivoli?s process automation engine. The various components that make up the system are described. The unit will address Java EE servers and the basic use of WebSphere© as it relates to the engine. The unit then covers the organization of the administrative workstation and system properties. The unit briefly describes the setup of the system for using attachments. Foundation Data This unit covers the creation of foundation data for Tivoli?s process automation engine. The foundation data is the software constructs that are necessary in the basic configuration of the product. These constructs include organizations, sites, locations, classifications, and various engine financial configurations. Security Security addresses the need to protect system resources from unauthorized access by unauthenticated users. Resources in the system are protected by Authentication and Authorization. Database architecture This unit illustrates the possible database configurations using the Database Configuration application. It also presents specific command lines that you can run to configure the changes made on the attributes of business objects using the Database Configuration application. Work Management Work Management is a collection of components and products that work together to form a powerful process and work management system. This unit provides a look at work management and focuses on using Work Management to generate, process, and complete work orders. Customizing an application This unit provides an overview of the Application Designer and Migration Manager. You will learn how to change, duplicate and create applications. You will learn the process to move from development, integration testing, user acceptance testing and moving to production. Automation This unit provides a high-level overview of key automation application programs and their functionality. It describes cron tasks, which are used to automate jobs in the system. The unit then discusses various communication tools in the system such as Communication Templates and the E mail Listener application. Finally, automated means of notification using escalations and actions are covered. Workflow This unit focuses on workflow. You learn about the Workflow Designer and its tools. You also learn how to modify an existing workflow and how to manage the included workflows. Reporting This unit provides an overview of the data analysis and reporting options that you can use in the system to analyze data. You create query by example (QBE) reports, result sets, key performance indicators (KPI), and query-based reports (QBRs). Students can optionally review Appendix A to learn how to create a simple enterprise report using Business Intelligence Reporting Tools (BIRT) designer. This report provides an example of how developers create more complex, widely used reports for users. Integration Framework In this unit, a high-level overview of the Integration Framework is provided. The Integration Framework architecture and components are described and basic configuration steps are described. The configuration and steps for loading and exporting data to and from the system are covered. You have the opportunity to practice them also. Budget Monitoring This unit provides information on a new feature introduced in Maximo 7.6.0.8, the Budget Monitoring application. In this application, you can create budget records to monitor transactions in a financial period. Inspection Tools and Tasks This unit introduces the new Inspection application. You can use the Inspections tools to create online inspection forms by using your desktop computer or laptop, and you can use the forms to complete an inspection by using your desktop computer, laptop, or tablet. Troubleshooting This unit focuses on troubleshooting as a systematic approach to solving a problem. The goal is to determine why something does not work as expected and to resolve the problem. It discusses the configuration of logging in the application. It also covers basic troubleshooting techniques, some important component logs, and information about obtaining help from Tivoli Support. Additional course details: Nexus Humans U5TR712 - IBM Maximo Asset Management - System Administration and Development v7.6x 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 U5TR712 - IBM Maximo Asset Management - System Administration and Development v7.6x 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 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

This Tableau Desktop Training course is a jumpstart to getting report writers and analysts with little or no previous knowledge to being productive. It covers everything from connecting to data, through to creating interactive dashboards with a range of visualisations in two days of your time. For Private options, online or in-person, please send us details of your requirements: This Tableau Desktop Training course is a jumpstart to getting report writers and analysts with little or no previous knowledge to being productive. It covers everything from connecting to data, through to creating interactive dashboards with a range of visualisations in two days of your time. Having a quick turnaround from starting to use Tableau, to getting real, actionable insights means that you get a swift return on your investment of time and money. This accelerated approach is key to getting engagement from within your organisation so everyone can immediately see and feel the impact of the data and insights you create. This course is aimed at someone who has not used Tableau in earnest and may be in a functional role, eg. in sales, marketing, finance, operations, business intelligence etc. The course is split into 3 phases and 9 modules: PHASE 1: GET READY MODULE 1: LAUNCH TABLEAU Check Install & Setup Why is Visual Analytics Important MODULE 2: GET FAMILIAR What is possible How does Tableau deal with data Know your way around How do we format charts Dashboard Basics – My First Dashboard MODULE 3: DATA DISCOVERY Connecting to and setting up data in Tableau How Do I Explore my Data – Filters & Sorting How Do I Structure my Data – Groups & Hierarchies, Visual Groups How Tableau Deals with Dates – Using Discrete and Continuous Dates, Custom Dates Phase 2: GET SET MODULE 4: MAKE CALCULATIONS How Do I Create Calculated Fields & Why MODULE 5: MAKE CHARTS Charts that Compare Multiple Measures – Measure Names and Measure Values, Shared Axis Charts, Dual Axis Charts, Scatter Plots Showing Relational & Proportional Data – Pie Charts, Donut Charts, Tree Maps MODULE 6: MAKE TABLES Creating Tables – Creating Tables, Highlight Tables, Heat Maps Phase 3: GO MODULE 7: ADD CONTEXT Reference Lines and Bands MODULE 8: MAKE MAPS Answering Spatial Questions – Mapping, Creating a Choropleth (Filled) Map MODULE 9: MAKE DASHBOARDS Using the Dashboard Interface Dashboard Actions This training course includes over 25 hands-on exercises and quizzes to help participants “learn by doing” and to assist group discussions around real-life use cases. Each attendee receives a login to our extensive training portal which covers the theory, practical applications and use cases, exercises, solutions and quizzes in both written and video format. Students must use their own laptop with an active version of Tableau Desktop 2018.2 (or later) pre-installed. What People Are Saying About This Course “Excellent Trainer – knows his stuff, has done it all in the real world, not just the class room.”Richard L., Intelliflo “Tableau is a complicated and powerful tool. After taking this course, I am confident in what I can do, and how it can help improve my work.”Trevor B., Morrison Utility Services “I would highly recommend this course for Tableau beginners, really easy to follow and keep up with as you are hands on during the course. Trainer really helpful too.”Chelsey H., QVC “He is a natural trainer, patient and very good at explaining in simple terms. He has an excellent knowledge base of the system and an obvious enthusiasm for Tableau, data analysis and the best way to convey results. We had been having difficulties in the business in building financial reports from a data cube and he had solutions for these which have proved to be very useful.”Matthew H., ISS Group

This course has been specifically designed to assist professionals applying for Real Estate positions where a Real Estate Financial Modelling test is a requisite part of the interview process.

ChatGPT for Marketing and Productivity with AI Tools Course Overview: This course provides an in-depth exploration of ChatGPT and other AI tools in the context of marketing and productivity. Designed for individuals keen on integrating AI into their business strategies, it covers essential techniques and applications to enhance marketing efforts and streamline work processes. Learners will gain insights into leveraging AI for targeted campaigns, content creation, and automation, while also learning how to increase personal and team productivity using AI tools. By the end of the course, learners will have a clear understanding of how to apply AI-driven solutions to achieve measurable results in marketing and productivity. Course Description: In this course, learners will explore the dynamic field of AI-powered marketing and productivity tools. Key topics include the AI Marketing Playbook, which introduces learners to the fundamentals of using AI in marketing, followed by strategies for utilising ChatGPT and other AI tools for content creation, social media campaigns, and customer engagement. Additionally, learners will discover various AI tools designed to optimise productivity, including project management, data analysis, and communication tools. This course provides a comprehensive approach, equipping learners with the knowledge to harness AI’s capabilities in improving both marketing efforts and workplace efficiency. ChatGPT for Marketing and Productivity with AI Tools Curriculum: Module 01: The AI Marketing Playbook Module 02: How to Use ChatGPT and AI for Marketing Module 03: Productivity with AI Tools (See full curriculum) Who is this course for? Individuals seeking to enhance their marketing efforts with AI. Professionals aiming to boost their productivity using AI-driven tools. Beginners with an interest in AI technologies and marketing. Business owners looking to streamline marketing and productivity. Career Path: Digital Marketing Specialist Marketing Automation Expert AI Solutions Specialist Productivity Consultant Marketing Manager

Whetstone Communications and comms2point0 are pleased to bring you the Data Bites series of free webinars. Our aim is to boost interest and levels of data literacy among not-for-profit communicators.

Course Overview The DeepSeek Masterclass: A Complete DeepSeek Zero to Hero! is designed to provide learners with a comprehensive understanding of DeepSeek AI from the ground up. Whether you are new to artificial intelligence or seeking to deepen your expertise, this course offers a structured journey through DeepSeek's functionalities and real-world applications. Learners will discover how to navigate DeepSeek for software development, business innovation, and educational advancement. Through this masterclass, individuals will build a strong theoretical foundation, explore diverse use cases, and emerge with the confidence to implement DeepSeek-driven strategies in a range of professional environments. By the end of the programme, learners will have developed the knowledge and insights necessary to use DeepSeek as a transformative tool across multiple disciplines. Course Description This in-depth course covers a wide range of essential topics, including the foundations of artificial intelligence, DeepSeek system setup, and its applications across various sectors such as business, education, and software development. Learners will explore how DeepSeek can be leveraged to create smart solutions for students, empower business professionals, and support teaching practices. The masterclass delivers an immersive learning experience that blends conceptual knowledge with strategic application insights. Participants will build expertise in utilising DeepSeek to enhance efficiency, support innovation, and foster professional growth. Whether learners are looking to enter the AI space or to future-proof their careers, this course equips them with the essential skills and understanding to confidently engage with DeepSeek technologies in a competitive landscape. Course Modules Module 01: Getting Started Module 02: Foundations of Artificial Intelligence (AI) Module 03: Setting up DeepSeek AI for Beginners Module 04: DeepSeek for Software Developers Module 05: DeepSeek for Business Professionals Module 06: DeepSeek Smart Solutions for Students Module 07: The Power of DeepSeek Module 08: DeepSeek for Teaching Professionals (See full curriculum) Who is this course for? Individuals seeking to master DeepSeek AI from basic to advanced levels. Professionals aiming to integrate DeepSeek solutions into their organisations. Beginners with an interest in artificial intelligence, software development, or educational technology. Educators and trainers wishing to incorporate AI-based strategies into teaching. Career Path AI Solutions Specialist Software Developer (AI Focus) Business Innovation Consultant Educational Technology Specialist Data Analysis Support Roles AI Application Support Officer Digital Transformation Assistant

Learn with Case Study - Market Research Course Overview: This course, "Learn with Case Study - Market Research," provides an in-depth understanding of the principles and techniques used in market research. It is designed to equip learners with the knowledge necessary to assess market trends, consumer behaviour, and competitive landscapes effectively. Through the use of real-world case studies, participants will gain valuable insights into the application of market research methodologies in various industries. By the end of the course, learners will be able to conduct research, analyse data, and make informed decisions that drive business strategies and growth. This course is ideal for those seeking to enhance their market research skills and apply them to professional practice. Course Description: In this course, learners will explore the core concepts of market research, including data collection, analysis techniques, and the interpretation of findings. The course integrates case studies to demonstrate how these methods are applied in real-life scenarios across different sectors. Key topics covered include survey design, focus groups, consumer behaviour analysis, and competitor research. Learners will develop the ability to evaluate and synthesise market data to inform strategic business decisions. The course encourages critical thinking, data interpretation, and strategic application, ensuring that learners can effectively utilise market research to support business objectives. By the end of the course, participants will have the skills to execute comprehensive market research projects. Learn with Case Study - Market Research Curriculum: Module 01: Introduction to Market Research Module 02: Data Collection Techniques Module 03: Case Study: Market Research in Action Module 04: Data Analysis and Interpretation Module 05: Consumer Behaviour and Market Segmentation Module 06: Reporting and Presenting Research Findings (See full curriculum) Who is this course for? Individuals seeking to improve their market research skills. Professionals aiming to enhance their strategic decision-making abilities. Beginners with an interest in understanding market dynamics. Those working in marketing, sales, or business strategy roles. Career Path: Market Research Analyst Marketing Manager Business Development Specialist Consumer Insights Analyst Data Analyst

Microsoft Office 2016 Complete Course Course Overview: The "Microsoft Office 2016 Complete Course" is designed to provide learners with comprehensive knowledge and essential skills in the core Microsoft Office applications. This course offers in-depth coverage of Microsoft Word, Excel, PowerPoint, Outlook, and Access, enabling participants to confidently use these programs in professional environments. By the end of the course, learners will be equipped to create, manage, and analyse documents, spreadsheets, presentations, emails, and databases with proficiency. This course is an invaluable resource for those looking to enhance their productivity and improve their digital skills, making them more competitive in the job market. Course Description: The "Microsoft Office 2016 Complete Course" delves into the key functionalities of Microsoft Office, with modules dedicated to each major application. Learners will explore the features of Word for document creation and editing, Excel for data analysis and management, PowerPoint for effective presentations, Outlook for email and calendar management, and Access for database handling. Each module is structured to help learners understand the software’s core functions and how to apply them in real-world scenarios. Upon completion, learners will have developed a strong foundation in using Office 2016, boosting their ability to operate efficiently and effectively in modern workplaces. This course is suitable for individuals seeking to increase their office productivity and streamline their daily tasks. Microsoft Office 2016 Complete Course Curriculum: Module 01: Microsoft Word 2016 Module 02: Microsoft Excel 2016 Module 03: Microsoft PowerPoint 2016 Module 04: Microsoft Outlook 2016 Module 05: Microsoft Access 2016 (See full curriculum) Who is this course for? Individuals seeking to improve their office productivity skills. Professionals aiming to advance in roles requiring Microsoft Office proficiency. Beginners with an interest in data management, communication, and office software. Those wishing to enhance their CV and increase career opportunities in administrative and support roles. Career Path: Office Administrator Executive Assistant Data Analyst Personal Assistant Administrative Support Specialist Project Coordinator