1150 Courses in Cardiff delivered Online

Earn your EYFS Teaching Diploma and enhance your skills in Early Years Foundation Stage education. Our comprehensive program provides a deep understanding of child development, curriculum planning, and effective teaching strategies. Prepare to excel in the field of early childhood education with this accredited diploma, equipping you with the knowledge and confidence to create a positive impact on young learners' lives.

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

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.

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!

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.

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