1069 Courses delivered Online

Course Overview Learn the Latest Skills | Acknowledged by CPD & QLS | MCQ Based Exam & Tutor Support | Interactive Video Training  The popular Counselling and Psychology Course will guide you through psychology’s core concepts, critical viewpoints, and applications. In addition, it offers comprehensive details on child cognitive development, how to handle abnormal behaviour, psychology research methodologies, and psychological approaches. You will have a variety of skills necessary to work in the health and social care sector, such as in hospitals, health centres, and child mental health services, by completing the Counselling and Psychology Course. Please note that this course does not entitle you to join the HCPC register or be acknowledged as a psychologist. However, through this course, you will come across all the basic guidelines of psychology to boost and shine your knowledge in this particular field of Psychology, which will add to your CPD points. What Will You Learn? Demonstrate knowledge of the major perspectives in psychology Recognize the major theories used in contemporary psychology Apply social psychological theories, principles and research findings to gain a better understanding of social issues Understand the cognitive development of children Recognize prevalent mental illnesses in both children and adults. Treatment for abnormal behaviour and knowledge of abnormal behaviour's diagnosis Apply data analysis in psychology and expert research techniques. What classes are included in this package? Earn a digital certificate upon successful completion acknowledged by UK and internationally acknowledged lesson There are no set schedules, so you can work at your own pace. Our email and live chat specialists are available to assist you 24 hours a day, 7 days a week. On weekdays, you’ll have access to a full-time tutor. Learn in a user-friendly, cutting-edge online learning environment. High-quality e-learning study materials Benefit from instant feedback through mock exams and multiple-choice assessments Who Should Take This Course? This course is an essential learning exercise for anybody considering a career in counselling, and the welfare or healthcare sectors, where communication and empathy are valued commodities. No formal lesson is required before enrolling on the course. Career Path Training offered by Counselling and Psychology could potentially benefit a range of roles, but would particularly enhance careers in: SEN Teacher Counselling Psychologist Life Coach Social Care Worker Psychotherapist Clinical Psychologist Child Psychologist School Counsellor Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessments Assignment Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £99. Please note that overseas students may be charged an additional £10 for postage. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment On successful completion of the Counselling and Psychology, you will be required to sit an online multiple-choice assessment. You will need to score 60% or above to pass the course. After successfully passing the exam, you will be able to apply for a Quality Licence Scheme endorsed certificate of achievement. The assessment will be evaluated automatically and the results will be given to you immediately. Retake fee If you do not pass the exam first time, you can purchase the Retake Exam for £1.99 and try again. Course Contents Perspectives in Psychology Social Psychology Cognitive Psychology and Its Applications Child Development The Psychology of Atypical (Abnormal) Behaviour Research Methods

Data Entry Administrator Diploma with Transcription and Translation Diploma Welcome to the Data Entry Administrator Diploma with Transcription and Translation. This multifaceted course aims to provide you with comprehensive skills in data entry, alongside a specialised focus on Transcription and Translation. The demand for professionals who can provide accurate and fast transcription and translation services is rapidly growing. This course prepares you to meet that demand head-on. Learning Outcomes: Gain foundational knowledge in Transcription basics. Understand the role of context in Transcription. Attain skills to improve Transcription accuracy. Master the tools used in Transcription and Translation. Acquaint yourself with the translation industry's dynamics. Develop strategies for effective translation. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Data Entry Administrator Diploma with Transcription and Translation Diploma: Basics of Transcription: Begin your journey by understanding the fundamentals of Transcription, the cornerstone for developing specialised skills in the field. Context in Transcription: Here, you'll delve into the nuances of context, learning how it influences the accuracy and effectiveness of Transcription. Transcription Accuracy: Accuracy is paramount in Transcription. This module will equip you with techniques to enhance your Transcription accuracy. Tools in Transcription: This module introduces you to the tools integral to Transcription, from software to hardware, to optimise your workflow. Translation Industry in the Realm of Transcription: An essential overview of the translation industry, explaining how Transcription skills can be effectively utilised within it. Translation Strategies Complementing Transcription: Finalize your training by learning the best strategies for translating content in a manner that complements your Transcription skills.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) 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 Hands-on Predicitive Analytics with Python (TTPS4879) 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.

Data dashboards provide key information to stakeholders so that they can make informed decisions. While there are plenty of software solutions for building these essential data products, there is much less guidance on how to design dashboards to meet the diverse needs of users.  This course is for anyone who is building or implementing dashboards, and wants to know more about design principles and best practice. You could be using business intelligence software (such as Power BI or Tableau), or implementing bespoke solutions.  The course will give your team the ability to evaluate user needs and levels of understanding, make informed decisions about chart selections, and make effective use of interactivity dynamic data.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve.  Sample learning content  Session 1: Data with a purpose Understanding the different types of dashboard. Information overload and other common dashboard pitfalls. Assessing user needs and levels of data fluency. Session 2: Planning a dashboard Assessing diverse user needs and levels of data fluency. Taking a User Experience (UX) approach to design and navigation. Applying an interative and collaborative approach to onboarding. Session 3: Graphs, charts and dials  Understanding how graphical perception informs chart choices. Making intelligent design choices to help users explore. Design principles for layout and navigation. Session 4: Using interactivity  Making effective use of filters to slice and dice data sets. Using layers of information to enable drilldown data exploration. Complenting dashboards with automated alerts and queries. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial “Alan was great to work with, he took us through the concepts behind data visualisation which means our team is now equipped for the future. He has a wide range of experience across the topic that is delivered in a clear, concise and friendly manner. We look forward to working with Alan again in the future.” John Masterson | Chief Product Officer | ImproveWell

This course bundle is made up of three separate certification courses: 1. PRINCE2® Foundation; 2. PRINCE2® Practitioner; 3. IASSC Lean Six Sigma Black Belt. The PRINCE2® Foundation And Practitioner course includes the official certification exams. By passing the Foundation and Practitioner exams, you will be an officially certified PRINCE2® Practitioner. The IASSC Lean Six Sigma Black Belt course includes the official IASSC Six Sigma Black Belt exam. By passing this exam, you will be officially certified by the IASSC as a Six Sigma Black Belt. You have 14 months to complete all of the courses in this bundle and take the exams. Read below to find out more about the courses contained within this bundle.

Getting Started The MBA in Educational Leadership and Management Top Up programme is a dynamic educational offering that aims to equip future educational leaders with essential skills. This programme places a strong emphasis on effective leadership, educational policy, and management within a variety of educational settings. Graduates from this programme emerge well-prepared to take on leadership roles within academic institutions and drive positive changes in the field of education. The MBA in Educational Leadership and Management is designed to empower educators and education professionals with advanced knowledge and skills in leadership and management. This programme presents an excellent opportunity for individuals with a relevant postgraduate diploma or an equivalent qualification to "top up" their credentials to earn a full MBA degree. Throughout this programme, students engage deeply with the intricacies of educational leadership and management, gaining valuable insights into the latest theories, practices, and strategies relevant to the educational sector. The curriculum strongly focuses on critical areas such as leadership theory, organisational management, policy development, and educational change management. The programme provides students with the tools needed to address the complex challenges that educational organisations face today, ultimately enhancing the quality of education. This MBA in Educational Leadership and Management enhances career prospects and actively contributes to improving educational systems. The programme comprises two phases; the first is the Qualifi Level 7 Diploma in Educational Management and Leadership, awarded by Qualifi and delivered by the School of Business and Technology London. The second phase is the MBA in Educational Leadership and Management Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this programme. About Awarding Body Anglia Ruskin University began in 1858 as the Cambridge School of Art founded by William Beaumont. It was then merged with the Cambridge shire College of Arts and Technology and the Essex Institute of Higher Education and was renamed Anglia Polytechnic. It was then given university status in 1992 and renamed Anglia Ruskin University in 2005. The university has campuses in the UK (Cambridge, Chelmsford, London and Peterborough), as well as they are partnered with institutions around the world including Berlin, Budapest, Trinidad, Singapore and Kuala Lumpur. Assessment Assignments and Project No examinations Entry Requirements A bachelor's degree Applicant without a bachelor's degree but holding significant relevant experience will be considered for entry on a case-by-case basis. A good command of English (IELTS 6.0 or equivalent). Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. Structure Phase -1 - Qualifi Level 7 Diploma in Educational Management and Leadership The QUALIFI Level 7 Diploma in Educational Management and Leadership is made up of 120 credits, which equates to hours 1200 of TQT. Learners must complete two mandatory units and choose four optional units to achieve a minimum of 120 credits. Mandatory Units Leadership Qualities and Practice in Education Unit Reference -T/618/3135 TQT : 200 Credit : 20 The unit will explore how team performance can be evaluated and optimised to realise strategic business and operational objectives. Contemporary Issues in Education: Theory, Policy and Practice Unit Reference - A/618/3136 TQT : 200 Credit : 20 This unit provides learners with an understanding of the link between educational research, policy and practice.   Optional Units Managing Change in an Educational Context Unit Reference - F/618/3137 TQT : 200 Credit : 20 This unit aims to develop learners' understanding of educational leadership and management in supporting change and developing leadership in their educational context. Pedagogy and Practice in Education Unit Reference - J/618/3138 TQT : 200 Credit : 20 This unit aims to develop learners' theoretical and practical grounding in approaches to teaching and learning related to subject academic knowledge and educational practices. Leading Reflective Practice in Education Unit Reference - L/618/3139 TQT : 200 Credit : 20 This unit aims to develop learners' understanding of reflective practice to apply this to their and other's roles in an educational context, leading to planning for personal development. Research Methods in Education Unit Reference - F/618/3140 TQT : 200 Credit : 20 This unit aims to develop research skills, including different approaches, proposal formulation, planning, data analysis, and exploring research's relationship with evidence-based practice. Postgraduate Study of Childhood, Education and Family Support Unit Reference - A/650/6687 TQT : 200 Credit : 20 The unit will offer a framework for each individual's evaluation of their academic and professional action plans for personal and professional learning. Research Methods for Childhood, Education and Family Support Unit Reference - D/650/6688 TQT : 200 Credit : 20 This unit aims to help learners identify and develop a focus on research and approaches to data analysis, such as phenomenological and hermeneutic approaches and descriptive statistics. Triangulating Theory and Practice Unit Reference - F/650/6689 TQT : 200 Credit : 20 This unit aims to assist educators in comprehending the theories that drive recommendations for best practices and calls for action in a challenging and quickly evolving professional context. Contemporary Issues in Education Unit Reference - K/650/6690 TQT : 200 Credit : 20  This unit aims to introduce learners to various emerging topics from many educational sectors.    Phase 2 - MBA in Educational Leadership and Management Top-Up Programme Structure Developing Effective Management Systems Dissertation (Major Project) Delivery Methods The programme comprises two phases; the first is the Qualifi Level 7 Diploma in Educational Management and Leadership, awarded by Qualifi and delivered by the School of Business and Technology London. The School of Business and Technology London offers flexible learning methods, including online and blended learning, allowing students to choose the mode of study that suits their preferences and schedules. The program is self-paced and facilitated through an advanced Learning Management System. Students can easily interact with tutors through the SBTL Support Desk Portal System for course material discussions, guidance, assistance, and assessment feedback on assignments. School of Business and Technology London provides exceptional support and infrastructure for online and blended learning. Students benefit from dedicated tutors who guide and support them throughout their learning journey, ensuring a high level of assistance. The second phase is the MBA in Educational Leadership and Management Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this programme. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Overview This comprehensive course on Interactive Dashboards with Data Studio will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Interactive Dashboards with Data Studio 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 Interactive Dashboards with Data Studio. It is available to all students, of all academic backgrounds. Requirements Our Interactive Dashboards with Data Studio 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 2 sections • 5 lectures • 02:41:00 total length •Module 01: Introduction to GDS: 00:36:00 •Module 02: Data Visualization: 01:29:00 •Module 03: Geo-visualization: 00:16:00 •Module 04: A Socio-Economic Case Study: 00:20:00 •Assignment - Interactive Dashboards with Data Studio: 00:00:00

Microsoft Excel Complete Course - Beginner Intermediate & Advanced To make learning Microsoft Excel easier for you, we have thoughtfully bundled our three greatest courses: Microsoft Excel Beginners, Intermediate, and Advanced. At this price, you won't find a better deal anywhere else. One of the most popular applications for visualizing and analyzing data that has been created to date is Microsoft Excel. These days, practically every industry and household use this helpful program for personal purposes. Excel is used by business owners for a plethora of tasks, including data analysis, visualizing data, tracking hours worked, money, and statements. This Microsoft Excel Complete Course can be very helpful to you whether you are a newbie, have some training and experience with the program, or haven't used Excel in a long time and need a thorough refresher to develop your skills. After completing this course, you will be a proficient Excel user. In a short period of time, our simple lessons will impart the knowledge in a very easy way. There won't be a rush because you can study whenever you want and at your own speed. After completing the course, your confidence in using Excel will increase. Course Highlights Microsoft Excel Complete Course - Beginner Intermediate & Advanced is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Microsoft Excel Complete Course - Beginner Intermediate & Advanced into 73 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 11 hours, 6 minutes hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Microsoft Excel Complete Course - Beginner Intermediate & Advanced Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Microsoft Excel Complete Course - Beginner Intermediate & Advanced is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Microsoft Excel Complete Course - Beginner Intermediate & Advanced is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Microsoft Excel Complete Course - Beginner Intermediate & Advanced Microsoft Excel 2019 New Features Introduction to Microsoft Excel 2019 New Features 00:07:00 CONCAT 00:02:00 IFS 00:01:00 MAXIFS 00:01:00 MINIFS 00:01:00 SWITCH 00:02:00 TEXTJOIN 00:01:00 Map Chart 00:02:00 Funnel Chart 00:01:00 Better Visuals 00:06:00 Pivot Table Enhancements 00:02:00 Power Pivot Updates 00:01:00 Getting Started With Microsoft Office Excel Navigate the Excel User Interface 00:28:00 Use Excel Commands 00:28:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 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 Formatting A Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:08:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working With Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:24:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working With Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:06:00 Visualizing Data With Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:13:00 Using PivotTables And Pivot Charts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with Pivot Charts 00:08:00 Filter Data by Using Timelines and Slicers 00:11:00 Working With Multiple Worksheets And Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:06:00 Using Lookup Functions And Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:09:00 Sharing And Protecting Workbooks Collaborate on a Workbook 00:20:00 Protect Worksheets and Workbooks 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 00:09:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Excel Templates Excel Templates 00:00:00 Resources Microsoft Excel 2019 00:00:00 Assignment Assignment - Microsoft Excel Complete Course - Beginner Intermediate & Advanced 00:00:00

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.

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently