278 Big Data courses delivered Online

Social Media for Health & Care is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Social Media for Health & Care and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 03 hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Module 01: Social Media and Communication Social Media and Communication 00:19:00 Module 02: Social Media, Big Data and E-Healthcare Social Media, Big Data and E-healthcare 00:19:00 Module 03: Medical Social Media Medical Social Media 00:24:00 Module 04: Medical Social Media: Content, Characteristics and Appearance Medical Social Media: Content, Characteristics and Appearance 00:22:00 Module 05: Participatory Health through Social Media Participatory Health through Social Media 00:24:00 Module 06: Use of Social Media by Hospitals and Health Authorities Use of Social Media by Hospitals and Health Authorities 00:23:00 Module 07: Social Media and Health Behaviour Change Social Media and Health Behaviour Change 00:25:00 Module 08: Gamification and Behavioural Change: Techniques for Health Social Media Gamification and Behavioural Change: Techniques for Health Social Media 00:25:00 Module 09: Applications Applications 00:24:00

Description Digital Curation Diploma The world of digital data is vast, intricate, and constantly evolving. To navigate and master this expanse, one requires a specialised set of skills and knowledge. Enter the Digital Curation Diploma, a comprehensive online course that equips participants with the tools, techniques, and strategies to effectively curate, preserve, and present digital information. The course begins with an 'Introduction to Digital Curation', setting the foundation for understanding the core principles and practices that govern the digital realm. From managing collections to interpreting vast amounts of data, the importance of curation becomes evident in a digital age where information overload is a common challenge. Next, the course explores the 'Tools and Technologies in Digital Curation'. Here, participants will gain hands-on experience with the software and platforms pivotal to the curation process. Mastery of these tools will empower learners to seamlessly handle and organise digital content. A deep understanding of 'Metadata and Its Significance' follows. As the backbone of digital information, metadata offers context, clarity, and structure. Through this unit, the significance of metadata will be thoroughly analysed, offering insights into its role in enhancing searchability and accessibility. Equally vital is the section on 'Digital Preservation Strategies'. In a world where technological obsolescence is rapid, preserving digital artefacts requires strategic thinking. This segment teaches the methodologies and best practices to ensure that digital content stands the test of time. As curators navigate the digital space, they must also be vigilant about 'Rights Management and Licensing'. This essential unit will elucidate the intricacies of intellectual property, offering guidelines on how to ethically and legally curate content. 'Curating Multimedia and Interactive Content' offers a fresh perspective. With the rise of multimedia content, from videos to interactive infographics, the need for competent curation in this area is paramount. This module ensures participants are adept at handling diverse forms of content with finesse. From individual pieces of content, the course then shifts to 'Building Digital Collections and Exhibitions'. Assembling digital archives and creating online exhibitions demands a keen eye for detail and narrative structure. This segment provides the techniques to achieve just that. The course also delves into 'Data Curation and Big Data Management'. In an era where data drives decisions, understanding how to manage and curate vast datasets is critical. This unit imparts knowledge on data storage, organisation, and interpretation. Furthermore, 'Ethical Considerations in Digital Curation' addresses the moral responsibilities of a digital curator. Navigating the fine line between access and privacy, this unit fosters a sense of integrity and responsibility. Lastly, 'The Future of Digital Curation' paints a picture of what lies ahead. As technologies evolve and new challenges arise, this module equips participants with the foresight to stay ahead of the curve. In conclusion, the Digital Curation Diploma is not just another online course. It's a journey into the depths of the digital universe, offering a beacon of knowledge and expertise. For those keen on harnessing the potential of digital curation, this diploma is the ideal starting point. Join the course and become part of the next generation of digital curators, shaping the future of digital content and its legacy. What you will learn 1:Introduction to Digital Curation 2:Tools and Technologies in Digital Curation 3:Metadata and Its Significance 4:Digital Preservation Strategies 5:Rights Management and Licensing 6:Curating Multimedia and Interactive Content 7:Building Digital Collections and Exhibitions 8:Data Curation and Big Data Management 9:Ethical Considerations in Digital Curation 10:The Future of Digital Curation Course Outcomes After completing the course, you will receive a diploma certificate and an academic transcript from Elearn college. Assessment Each unit concludes with a multiple-choice examination. This exercise will help you recall the major aspects covered in the unit and help you ensure that you have not missed anything important in the unit. The results are readily available, which will help you see your mistakes and look at the topic once again. If the result is satisfactory, it is a green light for you to proceed to the next chapter. Accreditation Elearn College is a registered Ed-tech company under the UK Register of Learning( Ref No:10062668). After completing a course, you will be able to download the certificate and the transcript of the course from the website. For the learners who require a hard copy of the certificate and transcript, we will post it for them for an additional charge.

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course designed to teach experienced systems administrators how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: Understand the benefits of distributed computing Understand the Hadoop architecture (including HDFS and MapReduce) Define administrator participation in Big Data projects Plan, implement, and maintain Hadoop clusters Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.) Plan, deploy and maintain HBase on a Hadoop cluster Monitor and maintain hundreds of servers Pinpoint performance bottlenecks and fix them Apache Hadoop is an open source framework for creating reliable and distributable compute clusters. Hadoop provides an excellent platform (with other related frameworks) to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn from and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence. This is an introductory-level, hands-on lab-intensive course geared for the administrator (new to Hadoop) who is charged with maintaining a Hadoop cluster and its related components. You will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Introduction Hadoop history and concepts Ecosystem Distributions High level architecture Hadoop myths Hadoop challenges (hardware / software) Planning and installation Selecting software and Hadoop distributions Sizing the cluster and planning for growth Selecting hardware and network Rack topology Installation Multi-tenancy Directory structure and logs Benchmarking HDFS operations Concepts (horizontal scaling, replication, data locality, rack awareness) Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) Health monitoring Command-line and browser-based administration Adding storage and replacing defective drives MapReduce operations Parallel computing before MapReduce: compare HPC versus Hadoop administration MapReduce cluster loads Nodes and Daemons (JobTracker, TaskTracker) MapReduce UI walk through MapReduce configuration Job config Job schedulers Administrator view of MapReduce best practices Optimizing MapReduce Fool proofing MR: what to tell your programmers YARN: architecture and use Advanced topics Hardware monitoring System software monitoring Hadoop cluster monitoring Adding and removing servers and upgrading Hadoop Backup, recovery, and business continuity planning Cluster configuration tweaks Hardware maintenance schedule Oozie scheduling for administrators Securing your cluster with Kerberos The future of Hadoop

[vc_row][vc_column][vc_column_text] Description With the constant evolution of digital technology, most businesses have become digitalised, including banking and the economic landscape. This Digital Banking Diploma Course is designed to help you familiarise with the digital banking system. You will learn how to utilise its new tools and technologies, whether you are pursuing a career in this industry, or want to expand your knowledge of financial technology in general. This digital banking course starts by helping you to adapt to new generation banking, focusing on online banking, mobile banking and direct banking. Throughout this course, you will expand your knowledge of e-Banking trends, practices, and digital banking strategies, with a complete overview of digital transformation. You will also explore the role social media plays in today's banking services and will learn how to utilise both to boost business.  Want to stay on top of the digital transformation? Enrol in this course today and make the most of e-Banking innovations! Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing 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? Digital Banking Diploma 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 Digital Banking Diploma 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.[/vc_column_text][/vc_column][/vc_row] Story of Digital Banking -- An overview section Introduction 00:02:00 Moving from Traditional Banking to New-gen Banking Moving from Traditional Banking to New-gen Banking 00:08:00 Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept 00:07:00 Use of Social media in Banking and arrival of Fintech Firms Use of Social media in Banking and arrival of Fintech Firms 00:09:00 Innovative technologies IOT, AI, ML, Block-chain,, Big data etc Innovative technologies IOT, AI, ML, Blockchain,, Big data etc 00:10:00 Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank 00:11:00 Assessment Assignment - Digital Banking Diploma 00:00:00 Order Your Certificates and Transcripts Order Your Certificates and Transcripts 00:00:00

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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.

Duration 2 Days 12 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who are currently using Tableau to perform numerical or general data analysis, visualization, and reporting. They need to provide data visualizations from multiple data sources, or combine data to show comparisons, manipulate data through calculations, create interactive visualizations, or create visualizations that showcase insights from statistical analysis. This course is also designed for students who plan to obtain Tableau Desktop Certified Associate certification, which requires candidates to pass the Tableau Desktop Certified Associate exam. Overview Blend data multiple sources. Join data. Access data in PDFs. Refine visualizations with sets and parameters. Analyze data with calculations. Visualize data with advanced calculations. Perform statistical analysis and forecasting. Create geographic visualizations. Get answers with Ask and Explain The advent of cloud computing and storage has ushered in the era of "big data." With the abundance of computational power and storage, organizations and employees with many different roles and responsibilities can benefit from analyzing data to find timely insights and gain competitive advantage. Data-backed visualizations allow anyone to explore, analyze, and report insights and trends from data. Tableau© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Beyond the fundamental capabilities of creating data driven visualizations, Tableau allows users to manipulate data with calculations to show insights, make visualizations interactive, and perform statistical analysis. This gives users the ability to create and share data driven insights with peers, executives, and clients. Prerequisites Tableau Desktop: Part 1 Lesson 1: Blending Data from Multiple Sources Topic A: Blend Data Topic B: Refine Blends to Visualize Key Information Lesson 2: Joining Data Topic A: Create Joins Topic B: Troubleshoot Joins Topic C: Merge Data with Unions Lesson 3: Accessing Data in PDFs Topic A: Connect to PDFs Topic B: Clean Up and Organize PDF Data Lesson 4: Refining Visualizations with Sets and Parameters Topic A: Create Sets Topic B: Analyze Data with Sets Topic C: Apply Parameters to Refine Visualizations Topic D: Create Advanced Visualizations Lesson 5: Analyzing Data with Calculations Topic A: Create Calculated Fields to Analyze Data Topic B: Manipulate Data with Functions Topic C: Analyze Data with Table Calculations Lesson 6: Visualizing Data with Advanced Calculations Topic A: Create Groups and Bins with Calculations Topic B: Analyze Data with LOD Expressions Lesson 7: Performing Statistical Analysis and Forecasting Topic A: Perform Statistical Analysis Topic B: Forecast Data Trends Lesson 8: Creating Geographic Visualizations Topic A: Create Maps Topic B: Customize Mapped Data Lesson 9: Getting Answers with Ask and Explain Topic A: Ask Data Topic B: Explain Data Additional course details: Nexus Humans Tableau Desktop - Part 2 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Tableau Desktop - Part 2 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Are you ready to embark on an enlightening journey of wisdom with the Data and Web Analytics bundle, and pave your way to an enriched personal and professional future? If so, then Step into a world of knowledge with our course bundle - Data and Web Analytics CPD Certificate. Delve into eight immersive CPD Accredited courses, each a standalone course: Data Analytics HTML Web Development Crash Course SQL for Data Science, Data Analytics and Data Visualization Google Data Studio: Data Analytics Introduction to Data Analytics with Tableau Big Data Analytics with PySpark Power BI and MongoDB Big Data Analytics with PySpark Tableau Desktop and MongoDB Data Analysis and Forecasting in Excel Traverse the vast landscapes of theory, unlocking new dimensions of understanding at every turn. Let the Data and Web Analytics CPD Certificate bundle illuminate your path to wisdom. The Data and Web Analytics CPD Certificate bundle offers a comprehensive exploration into a rich tapestry of vast knowledge across five carefully curated courses. The journey is designed to enhance your understanding and critical thinking skills. Each course within the bundle provides a deep-dive into complex theories, principles, and frameworks, allowing you to delve into the nuances of the subject matter at your own pace. In the framework of the Data and Web Analytics CPD Certificate package, you are bestowed with complimentary PDF certificates for all the courses included in this bundle, all without any additional charge. Adorn yourself with the Data and Web Analytics bundle, empowering you to traverse your career trajectory or personal growth journey with self-assurance. Register today and ignite the spark of your professional advancement! So, don't wait further and join the Data and Web Analytics CPD Certificate community today and let your voyage of discovery begin! Learning Outcomes: Attain a holistic understanding in the designated areas of study with the Data and Web Analytics bundle. Establish robust bases across each course nestled within the Data and Web Analytics bundle. Decipher intricate concepts through the articulate content of the Data and Web Analytics bundle. Amplify your prowess in interpreting, scrutinising, and implementing theories. Procure the capacity to engage with the course material on an intellectual and profound level. Become proficient in the art of problem-solving across various disciplines. Stepping into the Data and Web Analytics bundle is akin to entering a world overflowing with deep theoretical wisdom. Each course within this distinctive bundle is an individual journey, meticulously crafted to untangle the complex web of theories, principles, and frameworks. Learners are inspired to explore, question, and absorb, thus enhancing their understanding and honing their critical thinking skills. Each course invites a personal and profoundly enlightening interaction with knowledge. The Data and Web Analytics bundle shines in its capacity to cater to a wide range of learning needs and lifestyles. It gives learners the freedom to learn at their own pace, forging a unique path of discovery. More than just an educational journey, the Data and Web Analytics bundle fosters personal growth, enabling learners to skillfully navigate the complexities of the world. The Data and Web Analytics bundle also illuminates the route to a rewarding career. The theoretical insight acquired through this bundle forms a strong foundation for various career opportunities, from academia and research to consultancy and programme management. The profound understanding fostered by the Data and Web Analytics bundle allows learners to make meaningful contributions to their chosen fields. Embark on the Data and Web Analytics journey and let knowledge guide you towards a brighter future. CPD 80 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals keen on deepening their firm understanding in the respective fields. Students pursuing higher education looking for comprehensive theory modules. Professionals seeking to refresh or enhance their knowledge. Anyone with a thirst for knowledge and a passion for continuous learning. Career path Armed with the Data and Web Analytics bundle, your professional journey can reach new heights. The comprehensive theoretical knowledge from this bundle can unlock diverse career opportunities across several fields. Whether it's academic research, consultancy, or programme management, the Data and Web Analytics bundle lays a solid groundwork. Certificates CPD Certificate Of Completion Digital certificate - Included 8 Digital Certificates Are Included With This Bundle CPD Quality Standard Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript - £9.99

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

This intermediate-level course will help you learn how to use multi-threading and asynchronous programming to speed up programs that are heavily bottlenecked by IO operations. The course covers core concepts such as implementing multiprocessing in Python, creating various readers and schedulers, and monitoring your coding progress.