4679 Courses

Duration 5 Days 30 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Consulting systems engineer IoT Designer Network administrator Network engineer Network manager Sales engineer Systems engineer Technical solutions architect Overview After taking this course, you should be able to: Explain the fundamentals of Cisco IoT and list common devices involved List the common protocols, standards, and data flows of IoT Explain the Cisco IoT, common needs, and the corresponding solutions Explain how programmability can be used to automate and make operations, deployment, and support of Cisco IoT more effective Describe common Cisco IoT applications and how they apply to Cisco IoT use cases Explain the functions and use cases for Cisco security applications and Cisco IoT This course prepares you to develop Internet of Things (IoT) applications for Cisco© IoT edge compute and network architecture. Through a combination of lessons and hands-on experience, you will learn to implement and deploy Cisco IOx applications using Cisco Field Network Director and Cisco Kinetic. This course covers designing, deploying, and troubleshooting edge applications, and understanding the use of management tools, so you can control your industrial network and connected devices at scale. This course will prepare you for the certification exam 300-915 Developing Solutions Using Cisco IoT and Edge Platforms (DEVIOT), a concentration in the CCNP DevNet track. Course Outlines DEFINING CISCO IOT IOT NETWORKING AND OTHER DEVICES EXAMINING IOT PROTOCOLS EXAMINING IOT STANDARDS RECOGNIZING CISCO IOT NEEDS AND SOLUTIONS USING PROGRAMMABILITY WITH CISCO IOT DESCRIBING CISCO IOT APPLICATIONS: CISCO IOX DESCRIBING CISCO IOT APPLICATIONS: CISCO KINETIC AND CISCO FIELD NETWORK DIRECTOR DEFINING CISCO SECURITY APPLICATIONS Lab outline Use an MQTT Consumer to Subscribe to Sensor Data Use Cisco IOx Applications to Receive and Process Sensor Data Troubleshoot a Sensor Connection Use and Interpret Freeboard Data Use and Interpret Grafana Data Use and Interpret Kibana Data Cisco IOx Familiarity Lab Develop and Deploy a Cisco IOx Application Troubleshoot Cisco IOx Navigate Cisco Field Network Director Explore Cisco Field Network Director API Additional course details: Nexus Humans Cisco Developing Solutions Using Cisco IoT and Edge Platforms v1.0 (DEVIOT) 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 Developing Solutions Using Cisco IoT and Edge Platforms v1.0 (DEVIOT) 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 Days 12 CPD hours This course is intended for This training is ideally suited for data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities. It will also benefit system administrators and data engineers who wish to harness Elastic Stack's functionalities for efficient system logging, monitoring, and robust data visualization. With a focus on practical application, this course is perfect for those aspiring to solve complex data challenges in real-time environments across diverse industry verticals. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll explore: New features and updates introduced in Elastic Stack 7.0 Fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana Useful tips for using Elastic Cloud and deploying Elastic Stack in production environments How to install and configure an Elasticsearch architecture How to solve the full-text search problem with Elasticsearch Powerful analytics capabilities through aggregations using Elasticsearch How to build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis How to create interactive dashboards for effective storytelling with your data using Kibana How to secure, monitor and use Elastic Stack's alerting and reporting capabilities The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. Geared for experienced data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities, Working with Elasticsearch will explore how to use Elastic Stack and Elasticsearch efficiently to build powerful real-time data processing applications. Throughout the two-day hands-on course, you?ll explore the power of this robust toolset that enables advanced distributed search, analytics, logging, and visualization of data, enabled by new features in Elastic Stack 7.0. You?ll delve into the core functionalities of Elastic Stack, understanding the role of each component in constructing potent real-time data processing applications. You?ll gain proficiency in Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for compelling data visualization. You?ll also explore the art of crafting custom plugins using Kibana and Beats, and familiarize yourself with Elastic X-Pack, a vital extension for effective security and monitoring. The course also covers essentials like Elasticsearch architecture, solving full-text search problems, data pipeline building, and creating interactive Kibana dashboards. Learn how to deploy Elastic Stack in production environments and explore the powerful analytics capabilities offered through Elasticsearch aggregations. The course will also touch upon securing, monitoring, and utilizing Elastic Stack's alerting and reporting capabilities. Hands-on labs, captivating demonstrations, and interactive group activities enrich your learning journey throughout the course. Introducing Elastic Stack What is Elasticsearch, and why use it? Exploring the components of the Elastic Stack Use cases of Elastic Stack Downloading and installing Getting Started with Elasticsearch Using the Kibana Console UI Core concepts of Elasticsearch CRUD operations Creating indexes and taking control of mapping REST API overview Searching - What is Relevant The basics of text analysis Searching from structured data Searching from the full text Writing compound queries Modeling relationships Analytics with Elasticsearch The basics of aggregations Preparing data for analysis Metric aggregations Bucket aggregations Pipeline aggregations Substantial Lab and Case Study Analyzing Log Data Log analysis challenges Using Logstash The Logstash architecture Overview of Logstash plugins Ingest node Visualizing Data with Kibana Downloading and installing Kibana Preparing data Kibana UI Timelion Using plugins

Duration 3 Days 18 CPD hours This course is intended for Typical candidates for this course are IT Professionals who deploy small-to-medium scale enterprise network solutions based on Aruba products and technologies. Overview After you successfully complete this course, expect to be able to: Explain how Aruba's wireless networking solutions meet customers' requirements Explain fundamental WLAN technologies, RF concepts, and 802.11 Standards Learn to configure the Mobility Conductor and Mobility Controller to control access to the Employee and Guest WLAN Control secure access to the WLAN using Aruba Firewall Policies and Roles Recognize and explain Radio Frequency Bands and channels, and the standards used to regulate them Describe the concept of radio frequency coverage and interference and successful implementation and diagnosis of WLAN systems Identify and differentiate antenna technology options to ensure optimal coverage in various deployment scenarios Describe RF power technology including, signal strength, how it is measured and why it is critical in designing wireless networks Learn to configure and optimize Aruba ARM and Client Match and Client Insight features Learn how to perform network monitoring functions and troubleshooting This course teaches the knowledge, skills and practical experience required to set up and configure a basic Aruba WLAN utilizing the AOS 8.X architecture and features. Using lecture and labs, this course provides the technical understanding and hands-on experience of configuring a single Mobility Conductor with one controller and AP Aruba WLAN. Participants will learn how to use Aruba hardware and AOS8 to install and build a complete, secure controller network with multiple SSIDs. WLAN Fundamentals Describes the fundamentals of 802.11, RF frequencies and channels Explain RF Patterns and coverage including SNR Roaming Standards and QOS requirements Mobile First Architecture An introduction to Aruba Products including controller types and modes OS 8.X Architecture and features License types and distribution Mobility Conductor Mobility Controller Configuration Understanding Groups and Subgroups Different methods to join Mobility Controller with Mobility Conductor Understanding Hierarchical Configuration Secure WLAN configuration Identifying WLAN requirements such as SSID name, encryption, authentication Explain AP groups structure and profiles Configuration of WLAN using the Mobility Conductor GUI AP Provisioning Describes the communication between AP and Mobility controller Explain the AP booting sequence and requirements Explores the APs controller discovery mechanisms Explains how to secure AP to controller communication using CPSec Describes AP provisioning and operations WLAN Security Describes the 802.11 discovery, authentication and association Explores the various authentication methods, 802.1x with WPA/WPA2, Mac auth Describes the authentication server communication Explains symmetric vs asymmetric Keys, encryption methods WIPS is described along with rogue discovery and protection Firewall Roles and Policies An introduction into Firewall Roles and policies Explains Aruba?s Identity based Firewall Configuration of Policies and Rules including aliases Explains how to assign Roles to users Dynamic RF Management Explain how ARM calibrates the network selecting channels and power settings Explores OS 8.X Airmatch to calibrate the network How Client Match and Client Insight match steers clients to better APs Guest Access Introduces Aruba?s solutions for Guest Access and the Captive portal process Configuration of secure guest access using the internal Captive portal The configuration of Captive portal using Clearpass and its benefits Creating a guest provisioning account Troubleshooting guest access Network Monitoring and Troubleshooting Using the Mobility Conductor dashboard to monitor and diagnose client, WLAN and AP issues Traffic analysis using APPrf with filtering capabilities A view of AirWave's capabilities for monitoring and diagnosing client, WLAN and AP issues

Duration 2 Days 12 CPD hours This course is intended for This course is relevant to anyone who needs to work with and understand data including: Business Analysts, Data Analysts, Reporting and BI professionals Marketing and Digital Marketing professionals Digital, Web, e-Commerce, Social media and Mobile channel professionals Business managers who need to interpret analytical output to inform managerial decisions Overview This course will cover the basic theory of data visualization along with practical skills for creating compelling visualizations, reports and dashboards from data using Tableau. Outcome: After attending this course delegates will understand - How to move from business questions to great data visualizations and beyond How to apply the fundamentals of data visualization to create informative charts How to choose the right visualization type for the job at hand How to design and develop basic dashboards in Tableau that people will love to use by doing the following: Reading data sources into Tableau Setting up the roles and data types for your analysis Creating new data fields using a range of calculation types Creating the following types of charts - cross tabs, pie and bar charts, geographic maps, dual axis and combo charts, heat maps, highlight tables, tree maps and scatter plots Creating Dashboards that delight using the all of the features available in Tableau. The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to tourism. From Business Questions to Data Visualisation and Beyond The first step in any data analysis project is to move from a business question to data analysis and then on to a complete solution. This section will examine this conversion emphasizing: The use of data visualization to address a business need The data analytics process ? from business questions to developed dashboards Introduction to Tableau ? Part 1 In this section, the main functionality of Tableau will be explained including: Selecting and loading your data Defining data item properties Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations Creating basic visualizations Creating a basic dashboard Introduction to Tableau ? Part 2 In this section, the main functionality of Tableau will be explained including: Selecting and loading your data Defining data item properties Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations Creating basic visualizations Creating a basic dashboard Key Components of Good Data Visualisation and The Visualisation Zoo In this section the following topics will be covered: Colour theory Graphical perception & communication Choosing the right chart for the right job Data Exploration with Tableau Exploring data to answer business questions is one of the key uses of applying good data visualization techniques within Tableau. In this section we will apply the data visualization theory from the previous section within Tableau to uncover trends within the data to answer specific business questions. The types of charts that will be covered are: Cross Tabs Pie and bar charts Geographic maps Dual axis and combo charts with different mark types Heat maps Highlight tables Tree maps Scatter plots Introduction to Building Dashboards with Tableau In this section, we will implement the full process from business question to final basic dashboard in Tableau: Introduction to good dashboard design Building dashboards in Tableau

Duration 2 Days 12 CPD hours This course is intended for The ProxySG 6.6 Basic Administration course is intended for students who wish to master the fundamentals of the ProxySG. It is designed for students who have not taken any previous training courses about the ProxySG. Overview Describe the major Secure Web Gateway functions of the ProxySG.License and configure a ProxySG.Deploy a ProxySG in either explicit or transparent mode.Use the Visual Policy Manager to write policies to manage web filtering, authentication, and SSL traffic management.Use ProxySG access logs to generate reports. The ProxySG 6.6 Basic Administration course is an introduction to deployment options and management of the individual key features offered using the ProxySG 6.6 solution. Introduction to the Symantec ProxySG Secure Web Gateway Describe the functions of a proxy server Differentiate proxy servers from firewalls Describe the key features and benefits of the ProxySG List the various ProxySG models Access online Symantec community resources ProxySG Security Deployment Options Describe the three network deployment methods Describe the three possible roles of the ProxySG ProxySG Management Console Describe the relationship between the Management Console and the ProxySG CLI Describe the primary function of the major areas of the Management Console Use the Management Console to access on-box help and Symantec product documentation Traffic Interception Using Proxy Services Understand the functions of proxy services, listeners, and proxy types Describe the three most common proxy services Explain how the intercept and bypass settings affect what happens to network traffic passing through the ProxySG Explain the function of common global proxy service settings Hypertext Transfer Protocol Understand how a connection is initiated over the transport layer Identify the components of an HTTP URL Explain the two types of HTTP messages: request and response Identify common response codes Introduction to the Visual Policy Manager Describe the relationship among the VPM, CPL, and the Management Console Describe the default processing order for policy layers and rules Describe triggers and actions that can be used in writing policy Identify the types of objects that the VPM supports Describe some of the best practices to be followed when using the VPM to create policy Filtering Web Content Describe the main concepts of web filtering Describe the primary category databases Describe the category types available to policy Describe how WebFilter and WebPulse work together Using Threat Intelligence to Defend the Network Understand Intelligence Services as provided by the Global Intelligence Network Understand Geolocation and Threat Risk Levels and how they can be used in policy Ensuring Safe Downloads Describe how malware can be transmitted via HTTP Explain the methods, advantages, and disadvantages of file type detection Describe some of the considerations in deciding what content to block as possible malware sources Notifying User of Internet Usage Policies Explain the function and various components of built-in and custom exception pages Describe the function of Notify User objects Identify the types of pages that can be sent to users by using Notify User objects Describe splash pages and coaching pages using Notify User objects in the VPM Access Logging on the ProxySG Describe, at a high level, how the ProxySG performs access logging Describe the components of a ProxySG access log facility Identify default log facilities and log formats Describe common use cases for periodic and continuous uploading of access logs

Duration 2 Days 12 CPD hours This course is intended for Workspace ONE administrators, account managers, solutions architects, solutions engineers, sales engineers, technical support engineers, and consultants Overview By the end of the course, you should be able to meet the following objectives: Summarize the basic troubleshooting methodologies Outline common troubleshooting techniques in the Workspace ONE UEM console Outline common troubleshooting techniques when integrating enterprise solutions in the Workspace ONE UEM console Summarize common troubleshooting strategies for Workspace ONE UEM managed devices Outline common application management troubleshooting techniques in the Workspace ONE UEM console Summarize common troubleshooting techniques for email management in the Workspace ONE UEM console Explain common troubleshooting approaches for the VMware Unified Access Gateway™ platform and individual edge services Outline useful troubleshooting tools, such as the Self-Service Portal and VMware Workspace ONE Assist™ In this two-day course, you learn to investigate, analyze, and determine issues that might occur with all the different components of VMware Workspace ONE© UEM. Troubleshooting is the backbone of service maintenance and management. To effectively troubleshoot product issues, administrators must understand how product services communicate and function. This in turn helps optimize service and software health management. Course Introduction Introductions and course logistics Course objectives Fundamentals of Troubleshooting Workspace ONE UEM Outline software troubleshooting logic and support methods Summarize the main process flows for the Workspace ONE UEM components Explain the importance of Workspace ONE UEM process flows for troubleshooting Identify different Workspace ONE UEM log files Workspace ONE UEM Console Troubleshooting Outline the best practices for troubleshooting Workspace ONE UEM console issues Identify common group management and assignment-related issues Outline common issues for Workspace ONE UEM console roles and system settings Understand how analytic events can be used to identity platform errors Summarize the steps for collecting and analyzing Workspace ONE UEM console logs Integration Troubleshooting Outline the common enterprise integrations in Workspace ONE UEM Outline common troubleshooting techniques for the VMware AirWatch© Cloud Connector? Troubleshoot issues related to Directory Services integration Identify directory user and groups synchronization issues Troubleshoot issues related to certificate authority integration Explain VMware Workspace ONE© Access? integration and VMware Workspace ONE© Intelligent Hub troubleshooting techniques Endpoint Troubleshooting Compare the endpoint connection topologies in Workspace ONE UEM Outline useful tools and resources for endpoint troubleshooting Summarize the best practices for device enrollment troubleshooting Explain device connectivity troubleshooting techniques Understand how to identify and resolve profile-related issues Identify common compliance policy issues and potential root causes Applications Troubleshooting Explain the different scoping questions for troubleshooting applications Review application management configurations Summarize the general tools and resources for application troubleshooting Describe the general logic of troubleshooting public applications Understand internal application issues and potential causes Explain purchased application troubleshooting techniques Unified Access Gateway And Edge Services Troubleshooting Review Unified Access Gateway architecture and edge service workflows Understand Unified Access Gateway general configurations Explain how to utilize Unified Access Gateway related troubleshooting tools and resources Identify and resolve common issues for Content Gateway on Unified Access Gateway Summarize troubleshooting techniques for VMware Workspace ONE© Tunnel? on Unified Access Gateway Email Troubleshooting Review different email architecture and workflows Summarize common errors associated with email profiles Identify tools and resources for email troubleshooting Discuss troubleshooting techniques for VMware AirWatch© Secure Email Gateway? on Unified Access Gateway Outline PowerShell integration issues and techniques to address them Additional Troubleshooting Tools Describe how the Self-Service Portal helps administrators and empowers end-users to resolve issues Understand how Workspace ONE Assist can help endpoint troubleshooting

Duration 5 Days 30 CPD hours This course is intended for Typical candidates for this course are IT Professionals who deploy small-to-medium scale enterprise network solutions based on Aruba products and technologies Overview After you successfully complete this course, expect to be able to: Explain how Aruba's wireless networking solutions meet customers' requirements Explain fundamental WLAN technologies, RF concepts, and 802.11 Standards Learn to configure the Mobility Master and Mobility Controller to control access to the Employee and Guest WLAN Control secure access to the WLAN using Aruba Firewall Policies and Roles Recognize and explain Radio Frequency Bands and channels, and the standards used to regulate them Describe the concept of radio frequency coverage and interference and successful implementation and diagnosis of WLAN systems Identify and differentiate antenna technology options to ensure optimal coverage in various deployment scenarios Describe RF power technology including, signal strength, how it is measured and why it is critical in designing wireless networks Learn to configure and optimize Aruba ARM and Client Match features Learn how to perform network monitoring functions and troubleshooting AR-AMF teaches knowledge, skills & practical exp. to set up & config a basic AR WLAN utilizing OS 8.X architecture & features.using lecture & labs,AR-AMF provides tech. & hands-on exp. of config. a single Mobility Master with 1 controller & AP WLAN WLAN Fundamentals Describes the fundamentals of 802.11, RF frequencies and channels Explain RF Patterns and coverage including SNR Roaming Standards and QOS requirements Mobile First Architecture An introduction to Aruba Products including controller types and modes OS 8.X Architecture and features License types and distribution Mobility Master Mobility Controller Configuration Understanding Groups and Subgroups Different methods to join MC with MM Understanding Hierarchical Configuration Secure WLAN configuration Identifying WLAN requirements such as SSID name, encryption, authentication Explain AP groups structure and profiles Configuration of WLAN using the Mobility Master GUI AP Provisioning Describes the communication between AP and Mobility controller Explain the AP booting sequence and requirements Explores the APs controller discovery mechanisms Explains how to secure AP to controller communication using CPSec Describes AP provisioning and operations WLAN Security Describes the 802.11 discovery, authentication and association Explores the various authentication methods, 802.1x with WPA/WPA2, Mac auth Describes the authentication server communication Explains symmetric vs asymmetric Keys, encryption methods WIPS is described along with rogue discovery and protection Firewall Roles and Policies An introduction into Firewall Roles and policies Explains Aruba?s Identity based Firewall Configuration of Policies and Rules including aliases Explains how to assign Roles to users Dynamic RF Management Explain how ARM calibrates the network selecting channels and power settings Explores the new OS 8.X Airmatch to calibrate the network How Client Match and Client Insight match steers clients to better Aps Dynamic RF Management Explain how ARM calibrates the network selecting channels and power settings Explores the new OS 8.X Airmatch to calibrate the network How Client Match and Client Insight match steers clients to better Aps Guest Access Introduces Aruba?s solutions for Guest Access and the Captive portal process Configuration of secure guest access using the internal Captive portal The configuration of Captive portal using Clearpass and its benefits Creating a guest provisioning account Troubleshooting guest access Network Monitoring and Troubleshooting Using the MM dashboard to monitor and diagnose client, WLAN and AP issues Traffic analysis using APPrf with filtering capabilities A view of Airwaves capabilities for monitoring and diagnosing client, WLAN and AP issues

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions