1194 Courses

Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Introduction to Power Electronics Components Introduction to Power Electronics 00:13:00 Uncontrolled Switches 00:17:00 What Is The Benefit of Diode. 00:06:00 Semi-Controlled Switches Part 1 00:09:00 Semi-Controlled Switches Part 2 00:14:00 Semi-Controlled Switches Part 3 00:05:00 What Is The Benefit of Thyristor? 00:05:00 Fully Controlled Switches Part 1 00:17:00 Fully Controlled Switches Part 2 00:10:00 Fully Controlled Switches Part 3 00:12:00 Fundamentals of Rectifier Circuits Overview on Rectifiers 00:02:00 Rectifier Definition 00:01:00 Half Wave Uncontrolled Rectifier with RL Load 00:10:00 StartExample on Half Wave Uncontrolled Rectifier with R Load Part 1 00:06:00 StartExample on Half Wave Uncontrolled Rectifier with R Load Part 2 00:07:00 Half Wave Uncontrolled Rectifier with RL Load 00:10:00 Derivation of Current in R-L Load 00:08:00 Freewheeling Diode (Commutation Diode) 00:03:00 Half-wave R-L Load With FWD 00:09:00 Difference between Continuous and Discontinuous Mode in RL Load 00:07:00 Half Wave RL Load Continuous Mode with FWD 00:06:00 StartExample on Half Wave Uncontrolled Rectifier with FWD 00:07:00 Bridge Full Wave Uncontrolled Rectifier Part 2 00:05:00 Bridge Full Wave Uncontrolled Rectifier Part 2 00:05:00 Quick Revision on Bridge Full-wave Uncontrolled Rectifier 00:06:00 Firing Angle 00:02:00 Half-Wave Controlled Rectifier R Load 00:05:00 Half-Wave Controlled Rectifier R-L Load 00:04:00 Half Wave Controlled R-L Load with FWD 00:06:00 Example 1 00:07:00 Example 2 00:08:00 Example 3 00:13:00 StartExample 4 00:09:00 StartExample 5 00:09:00 Fully Controlled Bridge Rectifier Part 1 00:06:00 Fully Controlled Bridge Rectifier Part 2 00:06:00 Quick Revision on Bridge Full Wave Controlled Rectifier 00:02:00 StartExample 6 00:08:00 Half Controlled Bridge Rectifier 00:08:00 Half Controlled Bridge Rectifier with FWD 00:05:00 StartExample 7 00:07:00 StartExample 8 00:07:00 Performance Parameters 00:04:00 Power Factor 00:04:00 Fundamentals of AC Choppers Introduction to AC Choppers 00:02:00 Definition of AC Chopper 00:05:00 StartSwitching Techniques in AC Choppers 00:06:00 Applications on AC Choppers 00:03:00 Types of AC Choppers 00:02:00 AC Chopper with R Load 00:14:00 Example 1 on AC Chopper with R Load 00:06:00 Example 2 on AC Chopper with R Load 00:04:00 AC Chopper with L Load Part 1 00:13:00 AC Chopper with L Load Part 2 00:06:00 StartExample on AC Chopper with L Load 00:08:00 AC Chopper with RL Series Load 00:20:00 StartExample on AC Chopper with RL Series Load 00:07:00 AC Chopper with RL Parallel Load 00:25:00 StartExample on AC Chopper with RL Parallel Load 00:06:00 AC Chopper with Pure Capacitive Load 00:14:00 StartExample on AC Chopper with Pure Capacitive Load 00:04:00 AC Chopper Loaded by Heavy Rectifier 00:06:00 AC Chopper Loaded by AC Motor with Sinusoidal Back Emf 00:12:00 StartExample on AC Chopper Loaded by AC Motor with Sinusoidal Back Emf 00:08:00 Integral Cycle Control 00:11:00 Example on Integral Cycle Control 00:04:00 Fundamentals of DC Choppers Introduction to DC Choppers 00:02:00 Definition and Applications of DC Choppers 00:05:00 Step Down DC Chopper with R Load 00:12:00 Example on Step Down DC Chopper with R Load 00:08:00 Generation of Duty Cycle 00:09:00 Switching Techniques 00:09:00 Step Down DC Chopper with RLE Load Part 1 00:19:00 Step Down DC Chopper with RLE Load Part 2 00:15:00 Example 1 on Step Down DC Chopper with RLE Load 00:12:00 Example 2 on Step Down DC Chopper with RLE Load 00:02:00 Step Up DC Chopper with R or RL Load 00:09:00 Step Up DC Chopper with RE Load 00:15:00 Example on Step Up DC Chopper with RE Load 00:20:00 Buck Regulator Part 1 00:16:00 Buck Regulator Part 2 00:17:00 Example on Buck Regulator 00:03:00 Boost Regulator 00:23:00 Example on Boost Regulator 00:06:00 Buck-Boost Converter 00:17:00 Example on Buck-Boost Converter 00:05:00 Fundamentals of Inverters Introduction to Inverters 00:02:00 Definition of Inverter 00:04:00 Importance and Applications of Inverters 00:08:00 Single Phase Half Bridge R Load 00:16:00 Single Phase Half Bridge RL Load 00:08:00 Performance Parameters of Inverter 00:05:00 Example on Single Phase Half Bridge 00:10:00 Single Phase Bridge Inverter R Load 00:06:00 Single Phase Bridge Inverter RL Load 00:07:00 Example on Single Phase Bridge Inverter 00:06:00 Three Phase Inverters and Obtaining The Line Voltages 00:15:00 Three Phase Inverters and Obtaining The Phase Voltages 00:17:00 Example on Three Phase Inverters 00:06:00 Single Pulse Width Modulation 00:13:00 Multiple Pulse Width Modulation 00:13:00 Example on Multiple Pulse Width Modulation 00:04:00 Sinusoidal Pulse Width Modulation 00:16:00 Industrial Inverter 00:03:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

In today's fast-paced and competitive world, staying ahead requires constant growth and upskilling. Welcome to Electrical Machines for Electrical Engineering, an empowering journey designed to equip you with the essential knowledge and skills in Electrical Machines for Electrical Engineering to thrive in your professional endeavours. This comprehensive Electrical Machines for Electrical Engineeringcourse combines theoretical concepts with essential applications, providing you with a well-rounded understanding of the topic. Whether you're a seasoned professional seeking to enhance your expertise or a newcomer eager to embark on a new career path, this courseoffers the tools and insights necessary to unlock your true potential. This Electrical Machines for Electrical Engineering course holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Teaching Assistant course promises not just education, but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Enrol in Electrical Machines for Electrical Engineering today and embark on a transformative journey that will set you up for success in the dynamic and evolving world of Electrical Machines for Electrical Engineering. Unleash your potential and take the first step towards a rewarding and fulfilling career! Learning Outcomes By the end of this Electrical Machines for Electrical Engineering course, you will: Gain a deep understanding of the fundamental principles and theories in Electrical Machines for Electrical Engineering. Acquire the ability to analyse and solve complex problems related to the topic critically. Enhance your communication and teamwork skills, which are essential for collaborating effectively in professional settings. Apply the learned concepts in Electrical Machines for Electrical Engineeringto drive innovation and make strategic decisions within your field. Curriculum of Electrical Machines for Electrical Engineering: Unit 1: Introduction to Electric Machines Module 1- Introduction to Electric Machines Module 2- Types of Electric Machines and Principle of Electrical Generation Unit 2: DC Machines Module 1- Importance and Construction of DC Machines Module 2- Armature Winding and EMF Equation Module 3-Solved Example 1 Module 4-Solved Example 2 Module 5-Solved Example 3 Module 6-Solved Example 4 Module 7-Separately Excited DC Machine Module 8-Shunt and Series DC Machines Module 9-Solved Example 1 on Separately Excited DC Machine Module 10-Solved Example 2 on Separately Excited DC Machine Module 11-Solved Example 3 on Shunt Generator Module 12-Solved Example 4 on Shunt Generator Module 13-Solved Example 5 on Series DC Generator Module 14-Types and Applications of Compound DC Motors Module 15- Torque-Speed Characteristics and Speed Control of Separately Excited DC Motor Module 16- Torque-Speed Characteristics of Series DC Motor Module 17-Solved Example 1 on Speed Control Module 18-Solved Example 2 on Speed Control Module 19- Starting of DC Machine Module 20- Armature Reaction in DC Machines Module 21-Losses in DC Machines Unit 3: Construction of Transformers Module 1- What is a Transformer Module 2- Importance of Transformer Module 3-Iron Core of Transformer Module 4- Magnetic Circuit Inside Transformer Module 5- Windings of Transformer Module 6- Why are Windings Made of Copper Module 7- Classification of Windings Module 8- Insulating Material and Transformer Oil Module 9- Conservator of Transformer Module 10- Breather of Transformer Module 11- Bushings of Transformer Module 12- Tap Changer of Transformer Module 13- Cooling Tubes of Transformer Module 14- Buchholz Relay of Transformer Module 15- Explosion Vent Module 16- Methods of Cooling Module 17-Types of Transformers Module 18- Power Transformer and Distribution Transformer Module 19- Single Phase Core Type Transformer Module 20-Single Phase Shell Type Transformer Module 21- 3 Phase Core Type Module 22- 3 Phase Shell Type Module 23- Comparison between Shell and Core CSA Module 24- Comparison between Shell and Core Type Module 25- Notes Module 26-Video Explaining The Components in 3D and Real Life Unit 4: Fundamentals of Magnetic Circuits Module 1- Introduction to Magnetic Circuits Module 2- Induced Emf and Current Module 3- Ampere Right Hand Rule Module 4- Magnetic Circuit and Important Definitions Module 5- Linear and Non Linear Materials Module 6-Flux Linkage and Reluctance Module 7- Analogy between Electric and Magnetic Circuits Module 8- Fringing Effect Module 9- Example 1 Magnetic Circuits Module 10- Example 2 Module 11- Example 3 Module 12- Application on Magnetic Circuit - Transformers Unit 5: Theoretical Part on Transformers Module 1- Introduction to Transformers Module 2- Construction of Transformer Module 3-Theory of Operation Module 4- Ideal Transformer Module 5-Non Ideal Transformer Module 6- Effect of Loading on Transformer Module 7- Transformer Regulation Module 8- Transformer Losses Module 9- Transformer Efficiency Module 10- Transformer Rating Module 11- Question 1 Module 12- Question 2 Module 13- Question 3 Module 14- Example 1 Module 15- Voltage Relation of Transformer Module 16- Transformer Exact Equivalent Circuit Module 17- Concept of Refereeing Module 18- Approximate Equivalent Circuit Unit 6: Synchronous Machines Module 1- Construction and Principle of Operation of Synchronous Generator Module 2- Principle of Operation of Synchronous Motor Module 3- Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine Module 4-Solved Example 1 on Non Salient Machine Module 5-Solved Example 2 on Non Salient Machine Module 6-Solved Example 3 on Non Salient Machine Module 7- Solved Example 4 on Non Salient Machine Module 8-Solved Example 5 on Non Salient Machine Module 9-Solved Example 6 on Non Salient Machine Module 10- Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine Module 11-Solved Example 1 on Salient Machine Module 12- Solved Example 2 on Salient Machine Module 13-Solved Example 3 on Salient Machine Module 14- Parallel Operation of Two Generators Module 15- Synchronization of Machine with Grid Unit 7: Induction Machines Module 1- Construction and Theory of Operation of Induction Machines Module 2- Equivalent Circuit and Power Flow in Induction Motor Module 3- Torque-Speed Characteristics of Induction Motor Module 4- Solved Example 1 on Induction Motor Module 5-Solved Example 2 on Induction Motor Module 6-Solved Example 3 on Induction Motor Module 7-Solved Example 4 on Induction Motor Module 8-Solved Example 5 on Induction Motor Module 9- Methods of Speed Control of Induction Motor Module 10- Methods of Starting of Induction Motor Module 11-Solved Example on Motor Starter Module 12- Principle of Operation of Doubly Fed Induction Generator Module 13-Self Excited Induction Generator This Electrical Machines for Electrical Engineering course holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Teaching Assistant course promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals looking to expand their knowledge and skills in Electrical Machines for Electrical Engineering. Recent graduates seeking to enter the job market with a competitive edge. Individuals considering a career change into Electrical Machines for Electrical Engineering. Entrepreneurs aiming to gain insights into Electrical Machines for Electrical Engineering to boost their business strategies. Anyone interested in broadening their understanding of Electrical Machines for Electrical Engineering for personal or professional growth. Requirements No prior knowledge or experience is required to enrol in this Electrical Machines for Electrical Engineering course. Career path Completing Electrical Machines for Electrical Engineering can give you the initial boost to a world of exciting career opportunities.

The Teaching Assistant Level 3 Diploma course equips individuals with the knowledge and skills necessary to excel in a support role within educational settings. Covering topics such as classroom management, child development, and effective teaching strategies, this comprehensive program prepares teaching assistants to make a positive impact in classrooms and support the learning journey of students.

This comprehensive deep learning course with Python will start with the basics and work up to advanced topics such as using different frameworks in Python to solve real-world problems and building artificial neural networks with TensorFlow and Keras.

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.

Discover your special powers, receive insights and deep healing together with an abundance of light codes taking your life to the next level!

Discover your special powers, receive insights and deep healing together with an abundance of light codes taking your life to the next level!

Discover your special powers, receive insights and deep healing together with an abundance of light codes taking your life to the next level!

Discover your special powers, receive insights and deep healing together with an abundance of light codes taking your life to the next level!

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