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Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

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

Duration 2 Days 12 CPD hours This course is intended for Server administrators Network engineers Systems engineers Consulting systems engineers Technical solutions architects Network administrators Storage administrators Network managers Sales engineers Cisco integrators and partners Overview After taking this course, you should be able to: Describe Cisco UCS server hardware Describe Cisco UCS connectivity Describe the Cisco HyperFlex Data Platform, its data writing and reading processes, and data optimization Describe and configure Cisco UCS service profiles Describe and configure Cisco UCS service profile templates Describe and implement iSCSI on Cisco UCS Describe and implement Cisco UCS firmware updates Describe and implement Cisco UCS backups This introductory course shows you how to deploy, secure, operate and maintain the Cisco Unified Computing system (Cisco UCS) B-Series blade server, Cisco UCS C-Series and S-Series rack servers, and Cisco HyperFlex product family, for use in data centers. Describing Cisco UCS Server Hardware Cisco UCS B-Series Blade Servers Cisco UCS C-Series Rack Servers Cisco UCS S-Series Rack Servers Cisco Virtual Interface Cards Hyperconvergence Overview Cisco HyperFlex HX-Series Servers Describing Cisco UCS Connectivity Cisco UCS Fabric Interconnect Cisco UCS B-Series Connectivity Cisco UCS C-Series Connectivity Cisco UCS S-Series Connectivity Cisco HyperFlex Connectivity Architecture Cisco HyperFlex Edge Connectivity Ethernet End-Host Mode Compared to Switching Mode Cisco UCS Fabric Interconnect Uplink Pinning Cisco UCS C-Series Integration Describing the Cisco HyperFlex HX Data Platform Cisco HyperFlex HX Data Platform Software Writing Data to Cisco HyperFlex HX Data Platform Reading Data from Cisco HyperFlex HX Data Platform Data Optimization in Cisco HyperFlex HX Data Platform Configuring Cisco UCS Service Profiles Portability Issue with Nonabstracted Identities Cisco UCS Service Profile Identity Pools Server Pools IP Pools Configuring Cisco UCS Service Profile Templates Service Profile Templates Implementing iSCSI on Cisco UCS iSCSI Addressing Evolution of SCSI from DAS to SAN iSCSI Multipathing Implementing Cisco UCS Firmware Updates Update Cisco UCS C-Series Server Firmware Download Tasks for the Infrastructure Image Download Tasks for Cisco UCS B-Series Firmware Packages Best Practices for Updating Firmware in Cisco UCS Manager Firmware Upgrades Using Auto Install Capability Catalog Updates Host Firmware Packages Driver Updates for Operating Systems and Hypervisors Implementing Cisco UCS Backups Compare Backup Options in Cisco UCS Manager Compare Two Import Types Policy Backup

Duration 4 Days 24 CPD hours This course is intended for Data center engineers Engineers (design, implementation, pre-sales, post-sales) Product managers and sales Overview After taking this course, you should be able to: Describe hyperconvergence, Cisco HyperFlex, and the components of Cisco HyperFlex Explain the Cisco Unified Computing System™ (Cisco UCS) and what makes it valuable to business Describe how Cisco HyperFlex Data Platform (HXDP) works Describe the physical components of Cisco HyperFlex Describe Cisco Intersight and introduce functionalities relevant to HyperFlex Install standard ESXi-based vSphere Cisco HyperFlex Manage your Cisco HyperFlex VMware ESXi-based cluster Describe how to maintain Cisco HyperFlex Design a Cisco HyperFlex solution Protect the data on your Cisco HyperFlex cluster using replication and data at rest encryption Describe a stretched cluster and how is it different from a standard cluster Describe an Edge cluster and how is it different from a standard cluster Perform basic troubleshooting tasks and explain Cisco Intersight The Implementing Cisco HyperFlex (DCIHX) v1.3 course shows you how to deploy and use the Cisco© HyperFlex? data platform to support multicloud workloads. You will become familiar with HyperFlex components and learn how to install, design, manage, and troubleshoot Cisco HyperFlex to support highly scalable and resilient multicloud implementations. You will also gain hands-on experience focused on installation, management, maintenance, and native replication, and you will explore cluster technologies as well as Cisco Intersight.? Introducing Hyperconvergence and Cisco HyperFlex Traditional Data Center Design What Is Hyperconvergence? Describing Cisco UCS: The Foundation of Cisco HyperFlex Cisco Server Deployment Models: Standalone Versus Managed Cisco UCS Managed Model Benefits Describing Cisco HyperFlex Software Components Virtual Machine Hypervisor Log-Structured File System Describing Cisco HyperFlex Hardware Components Introducing Cisco HyperFlex Servers Storage Technologies in Cisco HyperFlex Introducing Cisco Intersight Introducing Cisco Intersight Installing and Expanding Standard ESXi Cisco HyperFlex Installation Summary Software Prerequisites Managing Cisco HyperFlex in vSphere Environment Management Interfaces Overview Cisco HyperFlex Plugin for vCenter Maintaining Cisco HyperFlex Cisco HyperFlex Upgrade Overview Cisco HyperFlex Online Upgrade Designing Cisco HyperFlex Cluster Resiliency: VM-Level Cluster Resiliency: HXDP-Level Protecting Your Data Disaster Recovery Overview Third-Party Data Restore Solutions Introducing Cisco HyperFlex Stretched Deployment Stretched Cluster Overview Prerequisites Introducing Cisco HyperFlex EDGE Cisco HyperFlex EDGE Cluster Overview Prerequisites and Recommendations Troubleshooting Cisco HyperFlex Troubleshooting Guidelines Generating Tech Support Bundles

Duration 4 Days 24 CPD hours This course is intended for Systems engineers Network engineers Field engineers Technical support personnel Channel partners and resellers Overview After taking this course, you should be able to: Describe the key concepts of segment routing Implement and verify IGP segment routing Migrate an existing Multiprotocol Label Switching (MPLS) LDP-based network to segment routing Implement and verify TI-LFA segment routing Instantiate segment routing policies Instantiate multidomain segment routing policies Configure and verify BGP prefix segments and SR-based services The Implementing Segment Routing on Cisco IOS XR (SEGRTE201) v2.0 course covers the fundamental concepts of Segment Routing (SR), how to configure and verify segment routing within an Interior Gateway Protocol (IGP), and the interworking of Label Distribution Protocol (LDP) with segment routing. You will learn how to implement Topology-Independent Loop-Free Alternate (TI-LFA) using segment routing, and how to instantiate and verify segment routing traffic engineering policies. You will also learn how to implement segment routing within Border Gateway Protocol (BGP). Introduction to Segment Routing Examining Unified Fabric Routing Exploring Segment Routing Concepts Examining Segment Types Examining the Segment Routing Global Block (SRGB) IGP Segment Routing Implementation and Verification Examining the IGP Control Plane Examining SRGB and IGP Interactions Examining Prefix and Adjacency SIDs Intermediate System to Intermediate System (IS-IS) Multilevel and Open Shortest Path First (OSPF) Multi-Area Configuring and Verifying IS-IS SR Operation Configuring and Verifying OSPF SR Operation Segment Routing and LDP Interworking SR and LDP Interworking Data Plane Mapping Server Function and Configuration Interworking Deployment Models Topology Independent ? Loop Free Alternate Examining Classic LFA Examining TI-LFA Fundamentals Implementing and Verifying TI-LFA for SR Traffic Implementing and Verifying SR TI-LFA for LDP Traffic TI-LFA and SR LDP Interworking Segment Routing Policies ? Traffic Engineering (SR-TE) Exploring SR Policies Introducing the Anycast and Binding SIDs Enabling and Verifying SR Policies Instantiating SR Policies Instantiating SR Policies using BGP Dynamic Multidomain SR Policies Configuring and Verifying a Path Computation Element (PCE) Configuring and Verifying BGP Link-State (LS) Configuring Multidomain SR Policies with a PCE Configuring Multidomain SR Policies with On Demand Next-Hop (ODN) Segment Routing?Based Services Examining the BGP Prefix-SID Operation Configuring and Verifying the BGP Prefix SID Examining Egress Peer Engineering Examining the BGP Prefix-SID Operation SR Flexible Algorithm and Performance Measurement (PM) Delay SR-Enabled VPNs

This accredited qualification has been designed for delivery to all learners working or preparing to work in a customer service role or where using the telephone is a part of their role. This qualification covers the principles of customer service, including how to meet customer expectations, the importance of appropriate behaviour and communication techniques, as well as ways to deal with problem customers. How long will it take me to achieve this qualification? This qualification is classroom-based and usually achieved by taking a one-day course. However, it can also be achieved through a variety of other methods including blended and distance learning, as long as the recommended learning hours are completed. How is the qualification assessed? Through a 1-hour 30-question multiple-choice examination. Learners must achieve a score of at least 20 out of 30 in order to pass.

What are the aims of this course? What learning disability is and isn't The facts of learning disabilities What barriers people with learning disabilities face Medical barriers Societal barriers How to support people with learning disabilities

Duration 5 Days 30 CPD hours This course is intended for Developed for experienced IT Professionals working with Citrix Virtual Apps and Desktops 7.1x. Potential students include administrators, engineers, and architects responsible for the end user workspace, provisioning services environment, and overall health and performance of the solution. Overview How to configure Workspace Environment Management to improve the end user environment and virtual resource consumption Understand Zones in Citrix Virtual Apps and Desktops 7.1x and how to account for user and desktop locations and optimal connection and registration How to build and manage App Layers to minimize image sprawl with Citrix Virtual Apps and Desktops 7.1x Understand and configure HDX channels and protocols for improved performance delivering multimedia and data over network connections Get more value out of your Citrix Virtual Apps and Desktops 7.1x investment through the use of Workspace Environment Management, Provisioning Services, Application Layering, and advanced features. Students leave this course with a good understanding of how to manage more complex solutions such as multizone environments spanning multiple locations with configurations around StoreFront, the Delivery Controllers, and HDX. Students will gain the skills to improve logon times, user personalization, and resource performance through Workspace Environment Management. Also, learn to optimize management of your app and desktop images by building and combining App Layers. End the course by learning to install, configure, and manage Provisioning Services in accordance with leading practices.This course includes a voucher to take the related exam (1Y0-311 Citrix XenApp and XenDesktop 7.15 Advanced Administration) and earn your Citrix Certified Professional - Virtualization (CCP-V) certification. Implementing Redundancy and Scalability StoreFront and Citrix Gateway Site Infrastructure Machines Running the Virtual Delivery Agent Managing a Virtual Apps and Desktops Environment with Multiple Locations Zones VDA Registration in a Multi-Zone Environment Zone Preference Optimal Gateway Routing and Zones Managing StoreFront Store Subscriptions in a Multi- Location Environment StoreFront and Citrix ADC Branding Implementing Backups and Disaster Recovery Backups Disaster Recovery Considerations Disaster Recovery Process Implementing Advanced Authentication Methods Multi-factor Authentication - RADIUS & OTP Multi-factor Authentication - Smart Card Authentication Federated Authentication - ADFS, SAML, and FAS Improving App and Data Security Introduction to Application Security Preventing Jailbreak Attacks Minimizing the Impact of Attacks Securing Machines Running the Virtual Delivery Agent TLS to VDA Encryption GPOs and Citrix Policies Image Management Introduction to Troubleshooting Troubleshooting Methodology Process (Standard Slide) Resource Tools and Utilities Introduction to PowerShell Troubleshooting Access Issues Troubleshooting StoreFront Troubleshooting Citrix Gateway Troubleshooting Delivery Controller Issues Validating FMA Services Troubleshooting VDA Registration Issues Troubleshooting VDA Registration Troubleshooting HDX Connection Issues Troubleshooting HDX Connections Introduction to App Layering App Layering Introduction Architecture and How it Works Creating an OS Layer The OS Layer Creating a Platform Layer The Platform Layer Creating App Layers The App Layers Creating Elastic App and User Layers Elastic App Layering User Layers Deploying a Layered Image using Citrix Virtual Apps and Desktops Using Templates in App Layering Using Layered Images in a Citrix Virtual Apps and Desktops Site Exploring Layer Priority Layer Priority Maintaining an App Layering Environment Updating Layers Maintaining and Updating the App Layering Environment Common App Layering Considerations and Additional Resources Introduction to Workspace Environment Management (WEM) Workspace Environment Management (WEM) Introduction WEM Administration Using WEM to Centralize Managing User Resources with WEM Managing Profiles with WEM Managing Endpoints with the WEM Transformer Feature Using WEM for Performance Optimization Optimizing Machine Performance with WEM Optimizing User Experience with WEM Using WEM to Secure Environments WEM Environments Migrating and Upgrading WEM Migrating to WEM Upgrading a WEM Deployment WEM Multi-Location Considerations

Duration 5 Days 30 CPD hours This course is intended for This course is intended for Cisco Unified Communications system channel partners and resellers who are responsible for deployment and application engineering for Cisco Unified Contact Center Express customers, System and technical support engineers, Day 1 and Day 2 support personnel, and Customers deploying and maintaining Cisco Unified CCX Overview Upon successful completion of this course, students will be able to create utilize advanced techniques in scripting and Cisco Unified CCX functionality The student will explore advanced techniques in scripting and Cisco Unified CCX functionality. During this five day class students will use advanced scripting to implement features that extend the functionality of Cisco Unified CCX. Cisco Unified CCX Overview Components of the Cisco Unified CCX Environment. Gateways. Routers. Cisco Unified Communications Manager. Cisco Unified CCX. Script Editor. Cisco Finesse. Cisco Unified Intelligence Center. Cisco Unified CCX Agent. External Servers. Cisco Unified CCX System Cluster Components. Engine. Database Server. Call Flow Terms. The Call Flow. The Debug Process Reactive. Non-Reactive Prompt Recording Utilities Prompt Recorder Emergency Message Recorder Basic ACD Routing Review Script Steps used in a Simple ACD Routing Script. Resource Group Routing. Defining the Contact Service Queue. Create a Simple ACD routing script Common Scripting Concepts Prompt Management. Using the Default Script. Terminating a Call and Ending a Script. Abandon Rates. Exception Handling. Script Interruptions. Check Agent Availability before and after entering queue. Using Java Methods for Holiday and Time of Day routing Accessing an External Database Database architecture and supported databases. Setting up the Database Subsystem. Using Database script steps Skills Based Routing Appling skills to agents. Defining the Contact Service Queue. Specifying the CSQ in the Script Advanced ACD Routing Overflow Routing. When to Overflow. How to get the Data Needed for Making Decisions. Describe Methods of Overflowing Basic ACD Callback Options Setup the Email Subsystem. Script for Email Notification. Script for Leaving a Recorded Message. Script for Callback when Queue Times have Decreased Enterprise Data and Session Management Define Enterprise Data in Cisco Finesse. Define a Call Variable Layout in Cisco Finesse. Define ECC Variables in the script editor. Set Enterprise Data in the script. Define Session Management. Setup Session Management. Use Session Management to Pass Variable Information Between Scripts Advanced ACD Callback Options Leave Queued Message with an Option for Callback. Scheduled Callback

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.