3108 Microsoft courses

Duration 5 Days 30 CPD hours This course is intended for This course provides an immersive learning experience for business and technical professionals who need a thorough understanding of the CMMC program. It does this by taking the point of view of a CMMC Certified Professional. Students might consider taking this course to learn more about the overall CMMC program, how DoD contractors are assessed, and how to help their organizations prepare for a CMMC Assessment. Overview In this course, you will learn about the CMMC Model, framework, context, and application within the DoD, as well as the expectations and requirements imposed upon organizations that do business with the DoD. You will: Identify the threats to the Defense Supply Chain and the established regulations and standards for managing the risk. Identify the sensitive information that needs to be protected within the Defense Supply Chain and how to manage it. Describe how the CMMC Model ensures compliance with federal acquisitions regulations. Identify responsibilities of the Certified CMMC Professional, including appropriate ethical behavior. Establish the Certification and Assessment scope boundaries for evaluating the systems that protect regulated information. Prepare the OSC for an Assessment by evaluating readiness. Use the CMMC Assessment Guides to determine and assess the Evidence for practices. Implement and evaluate practices required to meet CMMC Level 1. Identify the practices required to meet CMMC Level 2. Work through the CMMC Assessment process. The Cybersecurity Maturity Model Certification (CMMC), managed by The Cyber AB (formerly known as the CMMC Accreditation Body or the CMMC-AB), is a program through which an organization's cybersecurity program maturity is measured by their initial and ongoing compliance with applicable cybersecurity practices, as well as their integration of corresponding policies and plans into their overall business operations. Once rule-making has concluded and CMMC 2.0 has been implemented, all organizations providing products or services to the United States Department of Defense (DoD) must comply with the requirements of their applicable CMMC Level. This course provides a complete review of the key elements of this important program. Lesson 1: Managing Risk within the Defense Supply Chain Topic A: Identify Threats to the Defense Supply Chain Topic B: Identify Regulatory Responses against Threats Lesson 2: Handling Sensitive Information Topic A: Identify Sensitive Information Topic B: Manage the Sensitive Information Lesson 3: Ensuring Compliance through CMMC Topic A: Describe the CMMC Model Architecture Topic B: Define the CMMC Program and Its Ecosystem Topic C: Define Self-Assessments Lesson 4: Performing CCP Responsibilities Topic A: Identify Responsibilities of the CCP Topic B: Demonstrate Appropriate Ethics and Behavior Lesson 5: Scoping Certification and Assessment Boundaries Topic A: Use the CMMC Assessment Scope Documentation Topic B: Get Oriented to the OSC Environment Topic C: Determine How Sensitive Information Moves Topic D: Identify Systems in Scope Topic E: Limit Scope Lesson 6: Preparing the OSC Topic A: Foster a Mature Cybersecurity Culture Topic B: Evaluate Readiness Lesson 7: Determining and Assessing Evidence Topic A: Determine Evidence Topic B: Assess the Practices Using the CMMC Assessment Guides Lesson 8: Implementing and Evaluating Level 1 Topic A: Identify CMMC Level 1 Domains and Practices Topic B: Perform a CMMC Level 1 Gap Analysis Topic C: Assess CMMC Level 1 Practices Lesson 9: Identifying Level 2 Practices Topic A: Identify CMMC Level 2 Practices Lesson 10: Working through an Assessment Topic A: Identify Assessment Roles and Responsibilities Topic B: Plan and Prepare the Assessment Topic C: Conduct the Assessment Topic D: Report the Assessment Results Topic E: Conduct the CMMC POA&M Close-Out Assessment

Duration 4.375 Days 26.25 CPD hours This course is intended for This course provides a jump start on learning material that relates to the CMMC program, and to the planned Certified Professional (CP) certification in particular. It discusses the CMMC program, the current CMMC Model, and other CMMC materials as they exist today. The course may be of interest to individuals who wish to pursue the CMMC-CP certification when it is released. It may also be useful to stakeholders in organizations who will be involved in CMMC assessments, and who wish to gain a general understanding of the program and its requirements for their business planning purposes Overview In this course, you will examine the current CMMC model (Version 1.02), framework, context, and application within the DoD, as well as the expectations and requirements that will be imposed upon organizations that do business with the DoD. It will also help you to identify threats to cybersecurity and privacy within an IoT ecosystem and implement appropriate countermeasures. You will gain the skills to: · Identify risks within the defense supply chain and the established standards for managing them. · Describe how the CMMC model ensures compliance with federal acquisition regulations. · Identify responsibilities of the CMMC Certified Professional, including appropriate ethics and behavior. · Identify regulated information and establish the Certification and Assessment scope boundaries for evaluating the systems that protect that regulated information. · Evaluate OSC readiness and determine the objective evidence you intend to present to the assessor. · Use the NIST 800-171A and CMMC Assessment Guide to assess objective evidence for processes and practices. · Implement and evaluate practices required to meet CMMC maturity level 1. · Implement and evaluate processes and practices required to meet CMMC maturity level 2. · Implement and evaluate processes and practices required to meet CMMC maturity level 3. · Identify processes and practices required to meet CMMC maturity levels 4 and 5. · Work through the logistics of a CMMC assessment, including planning for and conducting the assessment, as well as any follow-up processes, such as remediation and adjudication. The Cybersecurity Maturity Model Certification (CMMC), managed by the CMMC Accreditation Body (CMMC-AB), is a program through which an organization's cybersecurity program is measured by their initial and ongoing compliance with applicable cybersecurity practices as well as their integration of corresponding policies and plans into their overall business operations. By Fiscal Year 2026, all organizations providing products or services to the United States Department of Defense (DoD) must obtain at least a Maturity Level 1 certification under this program. Managing Risk within the Defense Supply Chain Topic A: Identify Threats to the Defense Supply Chain Topic B: Identify Regulatory Responses Against Threats Ensuring Compliance through CMMC Topic A: Identify Limitations of Self-Certification Topic B: Identify Benefits of CMMC Topic C: Describe the CMMC Model Architecture Performing the General Responsibilities of a CMMC CP Topic A: Identify Responsibilities of the CMMC CP Topic B: Demonstrate Appropriate Ethics and Behavior Identifying and Scoping Regulated Information Topic A: Identify Regulated Information Topic B: Establish the Certification and Assessment Scope Boundaries Initiating the Assessment Process Topic A: Evaluate Readiness Topic B: Determine Objective Evidence Assessing Objective Evidence Topic A: Assess the Practices Using the CMMC Assessment Guides Topic B: Assess the Processes Using the CMMC Assessment Guide Level 3 Implementing and Evaluating CMMC Level 1 TTopic A: Maturity Level 1 Domains and Practices Topic B: Determine Scope Boundaries at Maturity Level 1 Topic C: Perform a Maturity Level 1 Gap Analysis Topic D: Perform a Maturity Level 1 Evidence Validation Implementing and Evaluating CMMC Levels 2 and 3 Topic A: Process Maturity Requirements for CMMC Levels 2 and 3 Topic B: Maturity Level 2 Practices Topic C: Maturity Level 3 Practices Identifying CMMC Levels 4 and 5 Topic A: Maturity Level 4 Processes and Practices Topic B: Maturity Level 5 Processes and Practices Working Through a CMMC Assessment Topic A: Define the Assessment Logistics Topic B: Resolve Assessment Related Issues Appendix A: Additional Documentation the CP Should Study

Duration 4 Days 24 CPD hours This course is intended for This course is designed for technical professionals who require the skills to administer IBM© MQ queue managers on distributed operating systems, in the Cloud, or on the IBM© MQ Appliance. Overview After completing this course, you should be able to:Describe the IBM© MQ deployment optionsPlan for the implementation of IBM© MQ on-premises or in the CloudUse IBM© MQ commands and the IBM© MQ Explorer to create and manage queue managers, queues, and channelsUse the IBM© MQ sample programs and utilities to test the IBM© MQ networkEnable a queue manager to exchange messages with another queue managerConfigure client connections to a queue managerUse a trigger message and a trigger monitor to start an application to process messagesImplement basic queue manager restart and recovery proceduresUse IBM© MQ troubleshooting tools to identify the cause of a problem in the IBM© MQ networkPlan for and implement basic IBM© MQ security featuresUse accounting and statistics messages to monitor the activities of an IBM© MQ systemDefine and administer a simple queue manager cluster This course provides technical professionals with the skills that are needed to administer IBM© MQ queue managers on distributed operating systems and in the Cloud. In addition to the instructor-led lectures, you participate in hands-on lab exercises that are designed to reinforce lecture content. The lab exercises use IBM© MQ V9.0, giving you practical experience with tasks such as handling queue recovery, implementing security, and problem determination. Note: This course does not cover any of the features of MQ for z/OS or MQ for IBM© i. Course introductionIBM© MQ reviewIBM© MQ installation and deployment optionsCreating a queue manager and queuesExercise: Using commands to create a queue manager and queuesIntroduction to IBM© MQ ExplorerExercise: Using IBM© MQ Explorer to create queue managers and queuesTesting the IBM© MQ implementationExercise: Using IBM© MQ sample programs to test the configurationImplementing distributed queuingExercise: Connecting queue managersIBM© MQ clientsExercise: Connecting an IBM© MQ clientImplementing trigger messages and monitorsExercise: Implementing a trigger monitorDiagnosing problemsExercise: Running an IBM© MQ traceImplementing basic security in IBM© MQExercise: Controlling access to IBM© MQBacking up and restoring IBM© MQ messages and object definitionsExercise: Using a media image to restore a queueExercise: Backing up and restoring IBM© MQ object definitionsIntroduction to queue manager clustersExercise: Implementing a basic clusterMonitoring and configuring IBM© MQ for performanceExercise: Monitoring IBM© MQ for performanceCourse summary

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Duration 1 Days 6 CPD hours This course is intended for IT professionals interested in understanding the capabilities of the MDS 9000 Series, including: Data center architects Data center engineers IT directors IT managers Network architects Network engineers Solutions architects Systems engineers Overview After taking this course, you should be able to: Describe Cisco MDS SAN features and advantages Define fixed and modular platforms Understand Cisco MDS architecture and high-availability mechanisms Identify technologies used in modern SANs Describe SAN management with Cisco Data Center Network Manager (DCNM) Explain key value-add features that distinguish Cisco MDS switches The Cisco MDS 9000 Series Switches Overview (DCMDSO) v1.5 course gives you a technical overview of how Cisco Multilayer Director Switch (MDS) 9000 Series, can be used to build highly available and scalable storage networks with advanced security and unified management. The course is for technical decision makers and IT professionals who architect, implement, and manage data center Storage Area Network (SAN) environments. In this course, you?ll learn about key capabilities of the MDS 9000 Series, including platforms, architecture, software, management, and key features that contribute to performance, high availability, flexibility, and operational simplicity of storage environments. Define Cisco MDS Platform Overview Introduction and Advantages of Cisco MDS Fixed Platforms Modular Platforms Describe Cisco MDS Architecture Store-and-Forward Architecture High Availability Redundancy Explore Cisco MDS Key Features Virtual Storage Area Networks Port Channels Slow Drain Device and Path Analysis Using Congestion Control Mechanisms Cisco DCNM SAN Insights for SAN Analytics Zoning Smart Zoning Other Differentiating Features Examine Cisco MDS Management Cisco Data Center Network Manager Additional course details: Nexus Humans Cisco MDS 9000 Series Switches Overview v1.5 (DCMDSO) 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 Cisco MDS 9000 Series Switches Overview v1.5 (DCMDSO) 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.

Duration 2.5 Days 15 CPD hours This course is intended for This course is designed for administrators who configure and manage web-based applications on WebSphere Application Server. Web administrators, application developers and deployers, security specialists, and application architects can also benefit from this course.Prerequisite(s) Overview After completing this course, you should be able to:Relate WebSphere Application Server to the WebSphere family of productsDescribe the features and standards in WebSphere Application Server V9Describe the use of WebSphere Application Server in cloud, hybrid cloud, and on-premises environmentsDescribe the architectural concepts that are related to WebSphere Application ServerAssemble and install server-side Java enterprise applicationsUse WebSphere administrative tools to configure and manage enterprise applicationsUse wsadmin scriptingConfigure WebSphere Application Server securityView performance information about server and application componentsTroubleshoot problems by using problem determination tools and log files In this course, you learn how to configure and maintain IBM WebSphere Application Server V9 in a single-server environment. Course Outline Course introduction WebSphere product family overview WebSphere Application Server architecture - stand-alone Exercise: Profile creation WebSphere Application Server administrative console Exercise: Exploring the administrative console Introduction to the PlantsByWebSphere application Application assembly Exercise: Assembling an application Application installation Exercise: Installing an application Problem determination Exercise: Problem determination Introduction to wsadmin and scripting Exercise: Using wsadmin WebSphere security Exercise: Configuring WebSphere Application Server security Exercise: Configuring application security Performance monitoring Exercise: Using the performance monitoring tools Course summary Additional course details: Nexus Humans WA590 IBM WebSphere Application Server V9 Administration 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 WA590 IBM WebSphere Application Server V9 Administration 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.

Duration 3 Days 18 CPD hours This course is intended for Individuals preparing for the Cisco Customer Success ManagerSpecialist certification Individuals who have experience working with customers to determine, measure, and deliver business outcomes through the implementation of technology Overview After taking this course, you should be able to: Describe the role of the Customer Success Manager Describe the tools that the Customer Success Manager uses to ensure customer experience Describe the lifecycle approach to customer experience The Cisco Customer Success Manager (DTCSM) v2.2 course gives you the confidence and competence to fulfill the Customer Success Manager (CSM) role successfully, helping your customers realize value from their solutions and achieve their business outcomes. The course offers experiential learning through practical exercises using situations based on real-life use cases and case studies. In this highly interactive course, you can practice and gain confidence in fulfilling core tasks using best-practice tools and methodologies while receiving feedback from the facilitator and your peers.This course is based on understanding the customer lifecycle and how to optimize that journey, increasing the value realized by the customer, and maximizing your likelihood to maintain their loyalty and renew or expand their business opportunities. The course helps you prepare for the 820-605 Cisco Customer Success Manager (CSM) exam. By passing this exam, you earn the Cisco Customer Success Manager Specialist certification. Course Outline Transition to Subscription Economy Customer and Industry Trends Defining Customer Success and the CSM Role Engaging the Customer for Success Engaging the Customer for Success Addressing Barriers Customer Success Management Activities Success Plan Elements Customer Success Management Activities Additional course details: Nexus Humans Cisco Customer Success Manager v2.2 (DTCSM) 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 Cisco Customer Success Manager v2.2 (DTCSM) 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.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Platform Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing,storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This 1-day instructor led course introduces Azure professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Identify the purpose of projects on Google Cloud. Understand how Azure's resource hierarchy differs from Google Cloud's Understand the purpose of and use cases for Identity and Access Management. Understand how Azure AD differs from Google Cloud IAM. List the methods of interacting with Google Cloud. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine Understand the basics of networking in Google Cloud. Understand how Azure VPC differs from Google VPC. Understand the similarities and differences between Azure VM and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure. Deploy applications using Google Compute Engine Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Azure Blob compares to Cloud Storage. Compare Google Cloud?s managed database services with Azure SQL. Learn how to choose among the various storage options on Google Cloud. Load data from Cloud Storage into BigQuery Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Azure Kubernetes Service differs from from Google Kubernetes Engine. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Azure App Service. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Google Cloud Deployment Manager differs from Azure Resource Manager. Understand the purpose of integrated monitoring, alerting, and debugging Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from Azure Data Lake. Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from Azure's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from Azure to Google Cloud.

Duration 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies