79 MongoDB courses in Nottingham delivered On Demand

Description GraphQL is a query and manipulation language of API that accomplishes queries with existing data. It is alternative to REST that is maintained by people, community, companies, and individuals across the world. To know more details about it, look at the GraphQL with NodeJs: Beginner to Advanced course. It will guide you further in your quest to regard this topic. The contents of this course will assist you to learn its basic to advance functions knowing how to start with GraphQL and NodeJs, do CURD Operations with NodeJs, MongoDB, and GraphQL, and fragment, union, and interfaces with GraphQL. The GraphQL with NodeJs: Beginner to Advanced course will assist you to learn how to set page number, make caching and batching, filtering, sorting and to know about the subscription and data loaders in GraphQL. It also enables you to test the data authentication and authorization with Jest in MngoDB, NodeJs, and GraphQL. The purpose of the course is to make you efficient in this field providing with all required information must. Learn vibrantly with the help of this course. Certification: After completing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? GraphQL with NodeJs: Beginner to Advanced is certified by CPD Qualifications Standards and CiQ. 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 background. Requirements Our GraphQL with NodeJs: Beginner to 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 After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Getting Started Create Express Server in NodeJs FREE 00:04:00 Create GraphQL Server using express 00:08:00 Understand GraphQL Resolver Arguments 00:03:00 Connect GraphQL App with MongoDB using Mongoose 00:04:00 CURD(Create, Read,Update,Delete) Operations with Nodejs, GraphQL, and MongoDB Create Record in MongoDB Using GraphQL Mutation 00:06:00 Get Records From MongoDB Using GraphQL Query 00:02:00 Update Records From MongoDB Using GraphQL Mutation 00:02:00 Delete Record From MongoDB Using GraphQL Mutation 00:02:00 Authentication and Authorization in GraphQL, Nodejs and MongoDB Create GraphQL Server with GraphQL Yoga 00:03:00 Split up your schema definition, resolvers, and Query type into multiple files 00:07:00 Create a Mongoose User model for Authentication in GraphQL 00:03:00 Register and Encrypt User Data and Return JWT Payload with Graph 00:07:00 Operations and Variables in GraphQL 00:02:00 Validate Input in GraphQL with Joi 00:04:00 Authenticate a User using a JSON Web Token in GraphQL 00:03:00 Merge GraphQL Resolvers into a Single Object using lodash.merge 00:02:00 Create a Middleware for Authentication in GraphQL 00:07:00 Apply Authentication Middleware on GraphQL Resolvers 00:03:00 Create Nested Resolvers to remove duplicate code from individual 00:07:00 Pagination, Filtering, And Sorting in GraphQL Paginate List of Data in GraphQL 00:04:00 Filter Nodes with Matching Rule GraphQL Queries 00:03:00 Sort GraphQL Query Results by Field 00:02:00 Cursor Based Pagination 00:09:00 Fragments, Interfaces, and Unions in GraphQL Send Multiple Queries in a Single Request using Aliases in GraphQL 00:02:00 Enhancing Fields Reusability with Fragments in GraphQL 00:02:00 Create Enum to represents a collection of related values 00:03:00 Create an Interface to represent the reusable fields in GraphQL 00:06:00 Interface Demo with - ResolveType 00:05:00 Create Union to return more than object type from GraphQL field 00:11:00 Subscriptions and DataLoaders in GraphQL Introduction to Subscriptions 00:01:00 Adding real-time functionality with GraphQL Subscriptions 00:06:00 Why Data Loaders in GraphQL 00:02:00 Create DataLoader in GraphQL 00:05:00 Batching in GraphQL 00:05:00 Caching in GraphQL 00:03:00 Testing with Jest in GraphQL and NodeJs Integrate Jest Testing Framework with GraphQL, and NodeJs 00:05:00 Write Unit test for Resolvers in GraphQL 00:04:00 Write Integration Test for Queries And Mutations in GraphQL 00:04:00 Order your Certificate Order Your Certificate 00:00:00

Get ready for an exceptional online learning experience with the Big Data Analysis & Data Science Diploma bundle! This carefully curated collection of 20 premium courses is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations. The Big Data Analysis & Data Science Diploma is a dynamic package, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Data Analysis & Data Science Diploma package has something for everyone. As part of the Big Data Analysis & Data Science Diploma package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Data Analysis & Data Science Diploma bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth! This bundle comprises the following courses: CPD Quality Standards Courses: Big Data Analytics with PySpark Power BI and MongoDB Big Data Analytics with PySpark Tableau Desktop and MongoDB Building Big Data Pipelines with PySpark MongoDB and Bokeh Develop Big Data Pipelines with R & Sparklyr & Tableau Develop Big Data Pipelines with R, Sparklyr & Power BI Complete Python Machine Learning & Data Science Fundamentals Learning Outcome: Gain comprehensive insights into multiple fields. Foster critical thinking and problem-solving skills across various disciplines. Understand industry trends and best practices through the Data Analysis & Data Science Diploma Bundle. Develop practical skills applicable to real-world situations. Enhance personal and professional growth with the Data Analysis & Data Science Diploma. Build a strong knowledge base in your chosen course via the Data Analysis & Data Science Diploma. Benefit from the flexibility and convenience of online learning. With the Data Analysis & Data Science Diploma package, validate your learning with a CPD certificate. Each course in this bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Embrace the future of learning with the Big Data Analysis & Data Science Diploma, a rich anthology of 15 diverse courses. Each course in the Data Analysis & Data Science Diploma bundle is handpicked by our experts to ensure a wide spectrum of learning opportunities. ThisBig Data Analysis & Data Science Diploma bundle will take you on a unique and enriching educational journey. The bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Big Data Analysis & Data Science Diploma bundle offers you the flexibility and convenience to learn at your own pace. Make the Data Analysis & Data Science Diploma package your trusted companion in your lifelong learning journey. CPD 25 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Big Data Analysis & Data Science Diploma bundle is perfect for: Lifelong learners looking to expand their knowledge and skills. Professionals seeking to enhance their career with CPD certification. Individuals wanting to explore new fields and disciplines. Anyone who values flexible, self-paced learning from the comfort of home. Career path Unleash your potential with the Big Data Analysis & Data Science Diploma bundle. Acquire versatile skills across multiple fields, foster problem-solving abilities, and stay ahead of industry trends. Ideal for those seeking career advancement, a new professional path, or personal growth. Embrace the journey with the Big Data Analysis & Data Science Diploma bundle package. Certificates Certificate Of Completion Digital certificate - Included Certificate Of Completion Hard copy certificate - Included You will get a complimentary Hard Copy Certificate.

Recent statistics indicate a soaring demand for proficiency in Microsoft Power BI & Microsoft Excel, reflecting these tools' indispensable role in modern data analytics and business intelligence. With the digital landscape evolving rapidly, organisations seek adept professionals capable of harnessing the power of data for strategic decision-making. Our comprehensive Microsoft Power BI & Microsoft Excel QLS Endorsed Diploma bundle, comprising a range of QLS endorsed and CPD QS accredited courses, is meticulously designed to equip learners with advanced skills in Microsoft Power BI & Microsoft Excel, alongside essential competencies in big data analytics and career development. In today's data-driven world, proficiency in Microsoft Power BI & Microsoft Excel is not merely advantageous but imperative. As businesses strive to extract actionable insights from vast datasets, the demand for skilled professionals proficient in these tools continues to surge. Our Microsoft Power BI & Microsoft Excel bundle offers a holistic approach, combining technical expertise with personal development modules, ensuring learners emerge as well-rounded professionals equipped to thrive in the competitive landscape of data analytics and business intelligence. Bundle Includes: QLS Endorsed Courses: Course 01: Advanced Diploma in Microsoft Power BI at QLS Level 7 Course 02: Advanced Diploma in Microsoft Excel Complete Course 2019 at QLS Level 7 CPD QS Accredited Courses: Course 03: Big Data Analytics with PySpark Power BI and MongoDB Course 04: Big Data Analytics with PySpark Tableau Desktop and MongoDB Course 05: Develop Big Data Pipelines with R, Sparklyr & Power BI Course 06: Microsoft Office 365 Automation Course Course 07: Microsoft Outlook - 25 Must-Know Tips and Tricks Course 08: Microsoft Access - 25 Must-Know Tips and Tricks Course 09: Microsoft Excel - 25 Must-Know Formulas and Functions Course 10: Data Analysis and Forecasting in Excel Take your career to the next level with our Microsoft Power BI & Microsoft Excel bundle that includes technical courses and five guided courses focused on personal development and career growth. 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Acquire essential automation skills through the Microsoft Office 365 Automation Course, streamlining workflow processes and increasing productivity. Enhance communication and presentation abilities through networking, public speaking, and decision-making courses. Gain insights into effective career development strategies, including CV writing, job searching, and professional networking. Apply critical thinking skills to evaluate complex data sets and make informed business decisions. Embark on a transformative journey of skill enhancement with our comprehensive Microsoft Power BI & Microsoft Excel course bundle focusing on Microsoft Power BI & Microsoft Excel. Delve into advanced techniques and methodologies essential for proficient data analysis and visualization. Through a series of meticulously crafted modules, participants will master the intricacies of Power BI, enabling them to transform raw data into actionable insights. 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This Microsoft Power BI & Microsoft Excel course is ideal for: Professionals seeking to enhance their proficiency in Microsoft Power BI & Microsoft Excel. Individuals aspiring to pursue careers in data analytics and business intelligence. Students and recent graduates looking to bolster their skill set for employment opportunities. Entrepreneurs aiming to leverage data-driven insights for business growth. Professionals seeking to advance their career prospects through enhanced communication and presentation skills. Individuals keen on developing a strategic approach to career development and networking. Requirements You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Upon completion of this Microsoft Power BI & Microsoft Excel bundle course, participants can pursue diverse career paths, including: Data Analyst Business Intelligence Analyst Data Scientist Financial Analyst Business Consultant Project Manager IT Manager Certificates 13 CPD Quality Standard Certificates Digital certificate - Included 2 QLS Endorsed Certificates Hard copy certificate - Included

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

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Register on the SQL NoSQL Big Data and Hadoop today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The SQL NoSQL Big Data and Hadoop is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The SQL NoSQL Big Data and Hadoop Receive a e-certificate upon successful completion of the 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) 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 Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This 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 online training is open to all students and has no formal entry requirements. To study the SQL NoSQL Big Data and Hadoop, 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. Course Content Section 01: Introduction 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 Section 02: Relational Database Systems 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 Section 03: Database Classification Distributed Databases 00:07:00 CAP Theorem 00:10:00 BASE 00:07:00 Other Classifications 00:07:00 Section 04: Key-Value Store 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 Section 05: Document-Oriented Databases 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 Section 06: Search Engines 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 Section 07: Wide Column Store 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 00:04:00 Section 08: Time Series Databases 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 Section 09: Graph Databases 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 Section 10: Hadoop Platform 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 Section 11: Big Data SQL Engines 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 Section 12: Distributed Commit Log 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 Section 13: Summary 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 Resources Resources - SQL NoSQL Big Data And Hadoop 00:00:00

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You will receive a completely free certificate from the Quality Licence Scheme Option to purchase 10 additional certificates accredited by CPD Get a free Student ID Card - (£10 postal charges will be applicable for international delivery) Free assessments and immediate success results 24/7 Tutor Support After taking this Statistical Analysis and Data Science bundle courses, you will be able to learn: Develop a comprehensive understanding of statistical analysis and data science principles Gain expertise in data analytics tools such as Tableau, PySpark, MongoDB, R, SQL, SAS, and Hadoop Learn advanced data science techniques, including machine learning, data mining, and business intelligence Acquire skills in data visualisation, data cleansing, and data analysis in Excel Apply statistical concepts and methods to real-world scenarios Build a strong foundation in data-driven decision-making Develop problem-solving skills and learn how to make data-driven decisions ***Curriculum breakdown of Statistical Analysis*** Module 01: The Realm of Statistics Module 02: Basic Statistical Terms Module 03: The Center of the Data Module 04: Data Variability Module 05: Binomial and Normal Distributions Module 06: Introduction to Probability Module 07: Estimates and Intervals Module 08: Hypothesis Testing Module 09: Regression Analysis Module 10: Algorithms, Analytics and Predictions Module 11: Learning From Experience: The Bayesian Way Module 12: Doing Statistics: The Wrong Way Module 13: How We Can Do Statistics Better How is the Statistical Analysis and Data ScienceBundle Assessment Process? 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CPD QS Accredited Certificate Hard copy certificate - Included International students are subject to a £10 delivery fee for their orders, based on their location. Diploma in Statistical Analysis at QLS Level 5 Hard copy certificate - Included

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