1071 Courses delivered Online

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.

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

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.

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.

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

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

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

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Embark on a journey to master Microsoft Excel with our 'Excel Essentials for Office Administrators' course. Designed to transform beginners into proficient users, this comprehensive course is divided into two main sections: Excel Beginner and Excel Intermediate. In the initial phase, learners are introduced to the Excel interface, where they explore and identify its various elements. This is followed by practical activities such as creating basic worksheets, using the help system, and crafting formulas. As the course progresses, participants will delve into more advanced features like manipulating data, applying styles and formats, and managing worksheets. The intermediate section elevates your skills further, covering a wide range of topics from applying range names and specialized functions to creating sophisticated charts and PivotTables. Learning Outcomes Gain proficiency in navigating and utilizing the Excel interface. Develop the ability to create and manage complex worksheets effectively. Master a variety of Excel functions and formulas for diverse data processing needs. Learn advanced data management techniques including sorting, filtering, and using PivotTables. Acquire skills in visual data presentation and customization of Excel workbooks. Why choose this Excel Essentials for Office Administrators course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the 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. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Excel Essentials for Office Administrators course for? Office administrators and secretaries seeking to enhance their Excel skills. Professionals in various sectors requiring proficiency in Excel for data management. Students and individuals interested in learning Excel from a beginner to an intermediate level. Business owners needing to manage business data more efficiently. Anyone aiming to improve their productivity and data analysis skills through Excel. Career path Data Analyst: £25,000 - £50,000 Administrative Assistant: £18,000 - £30,000 Office Manager: £22,000 - £40,000 Business Analyst: £30,000 - £60,000 Financial Analyst: £28,000 - £55,000 Project Coordinator: £24,000 - £45,000 Prerequisites This Excel Essentials for Office Administrators does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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 Excel Beginner Identify the Elements of the Excel Interface 00:30:00 Activity - Identify the Elements of the Excel Interface 00:05:00 Create a Basic Worksheet 01:00:00 Activity - Create a Basic Worksheet 00:05:00 Use the Help System 00:30:00 Activity - Use the Help System 00:05:00 Create Formulas in a Worksheet 01:00:00 Activity - Create Formulas in a Worksheet 00:05:00 Insert Functions in a Worksheet 00:30:00 Activity - Insert Functions in a Worksheet 00:05:00 Reuse Formulas 00:30:00 Activity - Reuse Formulas 00:05:00 Manipulate Data 00:30:00 Activity - Manipulate Data 00:05:00 Insert, Manipulate, and Delete Cells, Columns, and Rows 00:30:00 Activity - Insert, Manipulate, and Delete Cells, Columns, and Rows 00:05:00 Search For and Replace Data 00:30:00 Activity - Search For and Replace Data 00:05:00 Spell Check a Worksheet 00:30:00 Activity - Spell Check a Worksheet 00:05:00 Modify Fonts 00:30:00 Activity - Modify Fonts 00:05:00 Add Borders and Colors to Cells 01:00:00 Activity - Add Borders and Colors to Cells 00:05:00 Apply Number Formats 00:30:00 Activity - Apply Number Formats 00:05:00 Align Cell Contents 00:30:00 Activity - Align Cell Contents 00:05:00 Apply Cell Styles 00:30:00 Activity - Apply Cell Styles 00:05:00 Define the Basic Page Layout for a Workbook 01:00:00 Activity - Define the Basic Page Layout for a Workbook 00:05:00 Refine the Page Layout and Apply Print Options 00:30:00 Activity - Refine the Page Layout and Apply Print Options 00:05:00 Format Worksheet Tabs 00:30:00 Activity - Format Worksheet Tabs 00:05:00 Manage Worksheets 00:30:00 Activity - Manage Worksheets 00:05:00 Manage the View of Worksheets and Workbooks 00:30:00 Activity - Manage the View of Worksheets and Workbooks 00:05:00 Customize General and Language Options 00:30:00 Activity - Customize General and Language Options 00:05:00 Customize Formula Options 00:30:00 Activity - Customize Formula Options 00:05:00 Customize Proofing and Save Options 01:00:00 Activity - Customize Proofing and Save Options 00:05:00 Customize the Ribbon and Quick Access Toolbar 00:30:00 Activity - Customize the Ribbon and Quick Access Toolbar 00:05:00 Customize the Functionality of Excel by Enabling Add-Ins 00:30:00 Activity - Customize the Functionality of Excel by Enabling Add-Ins 00:05:00 Customize Advanced and Trust Center Options 00:30:00 Activity - Customize Advanced and Trust Center Options 00:05:00 Activities and Exercise Files - Microsoft Excel 2016 for Beginners 00:00:00 Excel Intermediate Apply Range Names 00:30:00 Use Specialized Functions 00:30:00 Use Text Functions 00:30:00 Use Logical Functions 00:30:00 Use Lookup Functions 00:30:00 Use Date Functions 00:30:00 Use Financial Functions 00:30:00 Create and Modify Tables 00:30:00 Sort and Filter Data 00:30:00 Use Subtotal and Database Functions to Calculate Data 00:30:00 Create Charts 00:30:00 Modify and Format Charts 00:30:00 Create a Trendline 00:30:00 Create Advanced Charts 00:30:00 Create a PivotTable 00:30:00 Filter Data by Using Slicers 00:30:00 Analyze Data with PivotCharts 00:30:00 Insert and Modify Graphic Objects 00:30:00 Layer and Group Graphic Objects 00:30:00 Incorporate SmartArt 00:30:00 Customize Workbooks 00:30:00 Manage Themes 00:30:00 Create and Use Templates 00:30:00 Protect Files 00:30:00 Preparing a Workbook for Multiple Audiences 00:30:00 Activities and Exercise Files - Microsoft Excel 2016 Intermediate 00:00:00

Description This course is aimed at the excel user who already knows the basics of Excel 2007. This course will help you to go beyond the basics - to reach a higher-intermediate level. With shortcuts, tricks and tips - you will be able to work smarter and faster. If you want to be fairly competent on the software, then this course will be very handy. Its a lot quicker to be shown things, then to try and muddle through and work things out by yourself. Guaranteed, there'll be some items which we cover, that you have no idea that Excel was capable of doing! We don't want you to spend a day of your life in the classroom... learn 99 quick and very useful, practical things which you can apply on your job or on your projects. We'll cover: Working with Data - using series, symbols and special characters, hide rows and freeze panels Formulas and Functions - Calculate the duration between two dates/times, best loan terms, create conditional formula and conditional sums Copying Data - transposing rows into columns and paste specials Using Excel lists - sort and filter a list, remove duplicate records, count filtered records, look up information in a list Data Patterns - Pivot tables, pivot charts, what-if analysis Creating charts - histogram, trendlines, piecharts, error bars Presenting data - formatting columns and numbers Saving and printing worksheets - printing multiple worksheets, area, cell ranges, repeat headings of a row or column Extending excel - hyperlinks, embed a chart, importing a worksheet Customizing Excel - custom workspace, custom view, macros The target audience is those who have a basic level with Excel and want to learn other handy functions and features. We use Excel 2007 only in this course. If you have Excel 2003, this course will be difficult to follow as although the functions and features exist in 2003, the layout changed very dramatically between the two versions. Excel 2007 isn't too dissimilar from 2010. Where necessary, we provide a spreadsheet - but as long as you have Excel 2007, you'll be able to copy and do exactly what you see on the screen by pausing the video and following along. The course will take approx 7.5 hours to complete. Take this course if you want to take your basic understanding of Excel to a higher intermediate-level. What Will I Learn? Work with Formulas and Functions Copy data and formats Use excel lists Create charts Present worksheets nicely Save and print worksheets Who is the target audience? This is for those who are beginners in Excel and want to take it further to higher intermediate level - using Excel 2007 You should know the 'basics' in Excel and we take it from near-beginner, to higher intermediate Requirements Students will need to have Excel 2007 installed, as this is the system used in the teaching Introduction to the course and your tutor Data Enter numbers and fractions 00:05:00 Dates and Times 00:08:00 Name Cells and Ranges 00:04:00 Validate Data entry using a pick list FREE 00:07:00 Extend a series of dates with autofill 00:04:00 Add a symbol or special character 00:04:00 Compare multiple spreadsheets using freeze panels 00:06:00 Hide rows 00:04:00 Keyboard 00:10:00 Speak Cells 00:04:00 Find and replace data 00:10:00 Formulas and Functions Add values 00:03:00 Function wizard 00:06:00 Formulas with comments 00:04:00 OneNote 00:06:00 Define a constant 00:04:00 Apply names in functions 00:05:00 Figure out the best loan terms 00:04:00 Internal Rates of Return 00:04:00 Nth largest value 00:04:00 Large, Small, Max, Min 00:04:00 Conditional formula 00:03:00 Conditional formula with names 00:04:00 Conditional sum 00:03:00 Count If 00:02:00 Inner calculator 00:02:00 Square Roots 00:03:00 Calculate the duration between two times 00:04:00 Calculate days between two dates 00:04:00 Copying Data, Formats etc., Copy a range 00:03:00 Transpose a row into a column FREE 00:02:00 Chart formatting 00:07:00 Copy styles to another workbook 00:07:00 Paste special and copying worksheets 00:06:00 Track changes while Editing 00:06:00 Lists Enter list data using a form 00:05:00 Searching through a data list 00:04:00 Import a word list into excel 00:04:00 Sort a list 00:02:00 Filter a list 00:02:00 Sort by multiple criteria FREE 00:03:00 Find averages in a sorted group 00:05:00 Filter by multiple criteria 00:03:00 Remove duplicate records from a list 00:03:00 Count filtered records 00:07:00 Filter by multiple criteria in the same column 00:06:00 Chart a filtered list 00:02:00 Look up information in a List 00:05:00 Data Patterns Create a PivotTable 00:05:00 Modify a PivotTable and layout 00:03:00 Find the average of a field 00:04:00 Create a calculated field 00:03:00 Calculated fields and charts FREE 00:02:00 Hide rows and columns in a PivotTable 00:02:00 AutoFormat a PivotTable 00:01:00 Create a PivotChart 00:03:00 Turning on the Data Analysis function so that statistical information can be run 00:02:00 Describe Data with Statistics 00:03:00 Discover associations within your data 00:03:00 Product Numbers 00:02:00 What-if analysis 00:05:00 Goal seek 00:06:00 Creating Charts Create a Chart 00:06:00 Modify Chart details 00:04:00 Change the Chart Type 00:03:00 Add a Trendline to a Chart 00:06:00 Remove Chart Data 00:02:00 Add chart data 00:02:00 Missing chart data 00:04:00 Error bars 00:04:00 Pull a slice from a Pie Chart 00:03:00 Label slices of a Pie Chart 00:04:00 Histogram 00:06:00 Paste a chart into Word 00:03:00 Amending a chart in Word 00:02:00 Paste-link a Chart into Word 00:05:00 Worksheets Format Numbers as Percentages 00:04:00 Format Currencies in Currency and Accounting Formats 00:03:00 Format Column Headings 00:05:00 Format Quickly with Format painter FREE 00:02:00 Insert a background image into your worksheet 00:03:00 Create a Transparent image 00:03:00 Saving and Printing Worksheets Save a workbook as a Template 00:07:00 Save a workbook as an XML spreadsheet 00:05:00 Print multiple cell ranges on One Page 00:03:00 Print multiple worksheets of a workbook 00:01:00 Page set up, header, footer, margins - 1 page printing 00:04:00 Repeat Headings of a Row or Column 00:07:00 Print functions to show calculations & comments 00:07:00 Extending Excel Hyperlink a worksheet to another office document 00:03:00 Embed a chart within PowerPoint 00:05:00 Publish an Interactive Workbook 00:05:00 Import a Worksheet into Access 00:09:00 Use Excel Data to create labels in Word 00:10:00 Customizing Excel Launch a specific Workbook when Excel Opens 00:03:00 Save Time by Creating a Custom View 00:03:00 Create a Custom Number Format 00:06:00 Changing Text to Columns 00:05:00 Create a Macro to Format Numbers 00:06:00 Online Live Webinar Course-S3_W4_L1 - 42 - Excel Made simple 01:00:00