1072 Data Analysis courses delivered Online

Overview This comprehensive course on SQL NoSQL Big Data and Hadoop will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This SQL NoSQL Big Data and Hadoop comes with accredited certification from CPD, 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? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this SQL NoSQL Big Data and Hadoop. It is available to all students, of all academic backgrounds. Requirements Our SQL NoSQL Big Data and Hadoop 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 14 sections • 130 lectures • 22:34:00 total length •Introduction: 00:07:00 •Building a Data-driven Organization - Introduction: 00:04:00 •Data Engineering: 00:06:00 •Learning Environment & Course Material: 00:04:00 •Movielens Dataset: 00:03:00 •Introduction to Relational Databases: 00:09:00 •SQL: 00:05:00 •Movielens Relational Model: 00:15:00 •Movielens Relational Model: Normalization vs Denormalization: 00:16:00 •MySQL: 00:05:00 •Movielens in MySQL: Database import: 00:06:00 •OLTP in RDBMS: CRUD Applications: 00:17:00 •Indexes: 00:16:00 •Data Warehousing: 00:15:00 •Analytical Processing: 00:17:00 •Transaction Logs: 00:06:00 •Relational Databases - Wrap Up: 00:03:00 •Distributed Databases: 00:07:00 •CAP Theorem: 00:10:00 •BASE: 00:07:00 •Other Classifications: 00:07:00 •Introduction to KV Stores: 00:02:00 •Redis: 00:04:00 •Install Redis: 00:07:00 •Time Complexity of Algorithm: 00:05:00 •Data Structures in Redis : Key & String: 00:20:00 •Data Structures in Redis II : Hash & List: 00:18:00 •Data structures in Redis III : Set & Sorted Set: 00:21:00 •Data structures in Redis IV : Geo & HyperLogLog: 00:11:00 •Data structures in Redis V : Pubsub & Transaction: 00:08:00 •Modelling Movielens in Redis: 00:11:00 •Redis Example in Application: 00:29:00 •KV Stores: Wrap Up: 00:02:00 •Introduction to Document-Oriented Databases: 00:05:00 •MongoDB: 00:04:00 •MongoDB Installation: 00:02:00 •Movielens in MongoDB: 00:13:00 •Movielens in MongoDB: Normalization vs Denormalization: 00:11:00 •Movielens in MongoDB: Implementation: 00:10:00 •CRUD Operations in MongoDB: 00:13:00 •Indexes: 00:16:00 •MongoDB Aggregation Query - MapReduce function: 00:09:00 •MongoDB Aggregation Query - Aggregation Framework: 00:16:00 •Demo: MySQL vs MongoDB. Modeling with Spark: 00:02:00 •Document Stores: Wrap Up: 00:03:00 •Introduction to Search Engine Stores: 00:05:00 •Elasticsearch: 00:09:00 •Basic Terms Concepts and Description: 00:13:00 •Movielens in Elastisearch: 00:12:00 •CRUD in Elasticsearch: 00:15:00 •Search Queries in Elasticsearch: 00:23:00 •Aggregation Queries in Elasticsearch: 00:23:00 •The Elastic Stack (ELK): 00:12:00 •Use case: UFO Sighting in ElasticSearch: 00:29:00 •Search Engines: Wrap Up: 00:04:00 •Introduction to Columnar databases: 00:06:00 •HBase: 00:07:00 •HBase Architecture: 00:09:00 •HBase Installation: 00:09:00 •Apache Zookeeper: 00:06:00 •Movielens Data in HBase: 00:17:00 •Performing CRUD in HBase: 00:24:00 •SQL on HBase - Apache Phoenix: 00:14:00 •SQL on HBase - Apache Phoenix - Movielens: 00:10:00 •Demo : GeoLife GPS Trajectories: 00:02:00 •Wide Column Store: Wrap Up: 00:05:00 •Introduction to Time Series: 00:09:00 •InfluxDB: 00:03:00 •InfluxDB Installation: 00:07:00 •InfluxDB Data Model: 00:07:00 •Data manipulation in InfluxDB: 00:17:00 •TICK Stack I: 00:12:00 •TICK Stack II: 00:23:00 •Time Series Databases: Wrap Up: 00:04:00 •Introduction to Graph Databases: 00:05:00 •Modelling in Graph: 00:14:00 •Modelling Movielens as a Graph: 00:10:00 •Neo4J: 00:04:00 •Neo4J installation: 00:08:00 •Cypher: 00:12:00 •Cypher II: 00:19:00 •Movielens in Neo4J: Data Import: 00:17:00 •Movielens in Neo4J: Spring Application: 00:12:00 •Data Analysis in Graph Databases: 00:05:00 •Examples of Graph Algorithms in Neo4J: 00:18:00 •Graph Databases: Wrap Up: 00:07:00 •Introduction to Big Data With Apache Hadoop: 00:06:00 •Big Data Storage in Hadoop (HDFS): 00:16:00 •Big Data Processing : YARN: 00:11:00 •Installation: 00:13:00 •Data Processing in Hadoop (MapReduce): 00:14:00 •Examples in MapReduce: 00:25:00 •Data Processing in Hadoop (Pig): 00:12:00 •Examples in Pig: 00:21:00 •Data Processing in Hadoop (Spark): 00:23:00 •Examples in Spark: 00:23:00 •Data Analytics with Apache Spark: 00:09:00 •Data Compression: 00:06:00 •Data serialization and storage formats: 00:20:00 •Hadoop: Wrap Up: 00:07:00 •Introduction Big Data SQL Engines: 00:03:00 •Apache Hive: 00:10:00 •Apache Hive : Demonstration: 00:20:00 •MPP SQL-on-Hadoop: Introduction: 00:03:00 •Impala: 00:06:00 •Impala : Demonstration: 00:18:00 •PrestoDB: 00:13:00 •PrestoDB : Demonstration: 00:14:00 •SQL-on-Hadoop: Wrap Up: 00:02:00 •Data Architectures: 00:05:00 •Introduction to Distributed Commit Logs: 00:07:00 •Apache Kafka: 00:03:00 •Confluent Platform Installation: 00:10:00 •Data Modeling in Kafka I: 00:13:00 •Data Modeling in Kafka II: 00:15:00 •Data Generation for Testing: 00:09:00 •Use case: Toll fee Collection: 00:04:00 •Stream processing: 00:11:00 •Stream Processing II with Stream + Connect APIs: 00:19:00 •Example: Kafka Streams: 00:15:00 •KSQL : Streaming Processing in SQL: 00:04:00 •KSQL: Example: 00:14:00 •Demonstration: NYC Taxi and Fares: 00:01:00 •Streaming: Wrap Up: 00:02:00 •Database Polyglot: 00:04:00 •Extending your knowledge: 00:08:00 •Data Visualization: 00:11:00 •Building a Data-driven Organization - Conclusion: 00:07:00 •Conclusion: 00:03:00 •Assignment -SQL NoSQL Big Data and Hadoop: 00:00:00

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

Follow your dreams by enrolling on the Counselling, Psychology and Cognitive Development course today and develop the experience, skills and knowledge you need to enhance your professional development. Counselling, Psychology and Cognitive Development will help you arm yourself with the qualities you need to work towards your dream job. Study the Counselling, Psychology and Cognitive Development training course online with Janets through our online learning platform and take the first steps towards a successful long-term career. The Counselling, Psychology and Cognitive Development course will allow you to enhance your CV, impress potential employers, and stand out from the crowd.  This Counselling, Psychology and Cognitive Development course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Study the Counselling, Psychology and Cognitive Development course through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the Counselling, Psychology and Cognitive Development course, to ensure you are supported every step of the way. Get a digital certificate as proof of your Counselling, Psychology and Cognitive Development course completion. Janets is one of the top online training course providers in the UK, and we want to make education accessible to everyone! Learn the essential skills you need to succeed and build a better future for yourself with the Counselling, Psychology and Cognitive Development course. The Counselling, Psychology and Cognitive Development course is designed by industry experts and is tailored to help you learn new skills with ease.  The Counselling, Psychology and Cognitive Development is incredibly great value and allows you to study at your own pace. With full course access for one year, you can complete the Counselling, Psychology and Cognitive Development when it suits you. Access the Counselling, Psychology and Cognitive Development course modules from any internet-enabled device, including computers, tablets, and smartphones. The Counselling, Psychology and Cognitive Development course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the Counselling, Psychology and Cognitive Development now and start learning instantly! Please note that this course does not entitle you to join the HCPC register or recognised as psychologist. 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 and it will add your CPD points. What You Get Out Of Studying Counselling, Psychology and Cognitive Development With Janets: Receive a digital Certificate upon successful completion of the Counselling, Psychology and Cognitive Development course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Description The Counselling, Psychology and Cognitive Development training course is delivered through Janets' online learning platform. Access the Counselling, Psychology and Cognitive Development content from any internet-enabled device whenever or wherever you want to. The Counselling, Psychology and Cognitive Development course has no formal teaching deadlines, meaning you are free to complete the course at your own pace. Method of Assessment  To successfully complete the Counselling, Psychology and Cognitive Development course, students will have to take an automated multiple-choice exam. This exam will be online and you will need to score 60% or above to pass the Counselling, Psychology and Cognitive Development course. After successfully passing the Counselling, Psychology and Cognitive Development course exam, you will be able to apply for a CPD-accredited certificate as proof of your Counselling, Psychology and Cognitive Development qualification. Certification All students who successfully complete the Counselling, Psychology and Cognitive Development course can instantly download their digital certificate. You can also purchase a hard copy of the Counselling, Psychology and Cognitive Development course certificate, which will be delivered by post for £9.99. Who Is This Course For: The Counselling, Psychology and Cognitive Development is ideal for those who already work in this sector or are an aspiring professional. This Counselling, Psychology and Cognitive Development course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The Counselling, Psychology and Cognitive Development is open to all students and has no formal entry requirements. To study the Counselling, Psychology and Cognitive Development course, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Career Path: The Counselling, Psychology and Cognitive Development is ideal for anyone who wants to pursue their dream career in a relevant industry. Learn the skills you need to boost your CV and go after the job you want. Complete the Counselling, Psychology and Cognitive Development and gain an industry-recognised qualification that will help you excel in finding your ideal job. Course Content Perspectives in Psychology What is Psychology 00:08:00 The Biological Approach 00:10:00 Behaviourist and Cognitive Approaches 00:10:00 Person-Centred Approaches 00:09:00 Research Methods in Psychology 00:12:00 Debates in Psychology 00:13:00 Social Psychology Social Influence: Compliance, Obedience and Conformity 00:10:00 Social Cognition 00:09:00 Applied Social Psychology 00:10:00 Cognitive Psychology and Its Applications Perception 00:10:00 Attention 00:07:00 Remembering (Memory) 00:10:00 Forgetting (Memory) 00:07:00 Language 00:10:00 Thinking (Cognition) 00:07:00 Attitudes 00:10:00 Problem-Solving and Artificial Intelligence 00:09:00 Child Development Issues in Child Development 00:05:00 Cognitive Development 00:07:00 The Development of Language and Communication 00:06:00 Social Perception (Interpersonal Perception) 00:06:00 Moral Development 00:09:00 The Psychology of Atypical (Abnormal) Behaviour The definition and Diagnosis of Atypical (Abnormal) Behaviour 00:07:00 Treatments of atypical (abnormal) behaviour 00:07:00 Emotional disorders 00:05:00 Research Methods Research Methods 00:06:00 Research Issues 00:06:00 Data Analysis 00:07:00 Thank You and Good Bye! 00:02:00 Resources Resources - Psychology Diploma 00:00:00 Mock Exam Mock Exam- Counselling, Psychology and Cognitive Development 00:20:00 Final Exam Final Exam- Counselling, Psychology and Cognitive Development 00:20:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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

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

Mechanical Engineering: Mechanical Engineering Would you like to work in the field of mechanical engineering? Our mechanical engineering course will help you understand engineering mathematics, fundamental physics, and an introduction to mechanical engineering. This mechanical engineering course explains heat transport, thermodynamics, and materials science. This mechanical engineering course discusses aerodynamics and fluid mechanics. Moreover, the mechanical engineering course covers kinematics, structural analysis, machine design, and the mechanics of solids. Through the mechanical engineering course, you will comprehend dynamics, control systems, and capstone design projects. Additionally, the mechanical engineering course describes technology, sustainability, and renewable energy techniques. If you are interested in learning about experimental techniques, appropriate data analysis, professional growth, and engineering ethics, enrol our mechanical engineering course soon! Special Offers of this Mechanical Engineering: Mechanical Engineering Course: This Mechanical Engineering: Mechanical Engineering Course includes a FREE PDF Certificate. Lifetime access to this Mechanical Engineering: Mechanical Engineering Course Instant access to this Mechanical Engineering: Mechanical Engineering Course 24/7 Support Available to this Mechanical Engineering: Mechanical Engineering Course Mechanical Engineering: Mechanical Engineering Elevate your career with our in-depth Mechanical Engineering Course! This program covers essential engineering mathematics, fundamental physics, and an introduction to core mechanical engineering concepts. You will delve into heat transport, thermodynamics, and materials science. Advanced topics include aerodynamics, fluid mechanics, kinematics, structural analysis, and machine design. Our curriculum also includes the mechanics of solids, dynamics, control systems, and engaging capstone design projects. Additionally, you'll learn about cutting-edge technology, sustainability, and renewable energy techniques. Develop practical skills with hands-on experimental methods, accurate data analysis, and a strong emphasis on professional growth and engineering ethics. Enroll today to become a proficient and innovative mechanical engineer! Who is this course for? Mechanical Engineering: Mechanical Engineering Anyone interested in mechanical engineering should pursue the mechanical engineering course. Requirements Mechanical Engineering: Mechanical Engineering To enrol in this Mechanical Engineering: Mechanical Engineering Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Mechanical Engineering: Mechanical Engineering Course Be energetic and self-motivated to complete our Mechanical Engineering: Mechanical Engineering Course Basic computer Skill is required to complete our Mechanical Engineering: Mechanical Engineering Course If you want to enrol in our Mechanical Engineering: Mechanical Engineering Course, you must be at least 15 years old. Career path Mechanical Engineering: Mechanical Engineering Successful completion of the mechanical engineering course can lead to a variety of rewarding career options in mechanical engineering-related industries.

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

CRM: Customer Relationship Management Online Are you excited to start a job as front desh executive or the job which have direct interaction with customers? Then our comprehensive CRM Course (Customer Relationship Management) is perfect for you. This CRM Course (Customer Relationship Management) delves into customer-centric strategies and emphasizing the use of CRM tools for enhanced customer interactions. The CRM Course (Customer Relationship Management) participants gain insights into customer data analysis, segmentation and effective communication techniques. The CRM Course (Customer Relationship Management) fosters skills in CRM system implementation and aligning sales. Moreover, the CRM Course (Customer Relationship Management) involves marketing and service functions. The CRM Course (Customer Relationship Management) helps in optimizing overall business performance through strengthened customer relationships. As the CRM Course (Customer Relationship Management) is a great method to progress your profession the what are you waiting? Sign up for this CRM Course (Customer Relationship Management) immediately! Main Course: CRM: Customer Relationship Management Free courses included with CRM: Customer Relationship Management Course: Along with CRM: Customer Relationship Management Course you will get free Close Protection Course Along with CRM: Customer Relationship Management Course you will get free Security Management Course Special Offers of this CRM: Customer Relationship Management Course: This CRM: Customer Relationship Management Course includes a FREE PDF Certificate. Lifetime access to this CRM: Customer Relationship Management Course Instant access to this CRM: Customer Relationship Management Course 24/7 Support Available to this CRM: Customer Relationship Management Course CRM: Customer Relationship Management Online Our CRM Course (Customer Relationship Management) provides an introduction to Customer Relationship Management (CRM) along with its all functions. Also, the CRM Course (Customer Relationship Management) explains CRM strategies, and data analysis in CRM and CRM Databases. Moreover, this CRM Course (Customer Relationship Management) includes difficulties handling processes. Additionally, the CRM Course (Customer Relationship Management) explain how to deepen the customer relationship and the future of CRM. Who is this course for? CRM: Customer Relationship Management Anyone can take this CRM Course (Customer Relationship Management). Requirements CRM: Customer Relationship Management To enroll in this CRM: Customer Relationship Management Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our CRM: Customer Relationship Management Course. Be energetic and self-motivated to complete our CRM: Customer Relationship Management Course. Basic computer Skill is required to complete our CRM: Customer Relationship Management Course. If you want to enrol in our CRM: Customer Relationship Management Course, you must be at least 15 years old. Career path CRM: Customer Relationship Management After completing this CRM Course (Customer Relationship Management), you can work as a manager, customer service manager, CRM analyst, and many other positions!

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

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