Duration 2 Days 12 CPD hours This course is intended for Anyone with the need to understand how business analysis is performed to support agile projects or who must transition their existing business analysis skills and practices from waterfall to agile. Overview In this course, students will: Understand the fundamentals of agile delivery and agile business analysis Compare and contrast business analysis on waterfall and agile projects Explain the value proposition for agile product development Define the 4 main types of project life cycles Complete an in-depth walkthrough of the agile delivery life cycle Explain the major flavors of agile Understand the major standards available to assist in transition of skills Define business analysis tailoring and understand how to apply it Learn over 20 business analysis techniques commonly used on agile projects In this course, students will gain an understanding about agile business analysis. Students will learn how business analysis on an agile project is ?the same? and ?different? than business analysis performed on waterfall projects. Students will understand how the business analysis role changes on an agile team. A number of business analysis techniques suited for supporting agile teams will be introduced as will the various standards available to the community to help teams and organizations transition. Since few organizations are pure agile, students will also learn about delivery approaches that use a combination of practices from waterfall and agile and will also be introduced to the important concept of business analysis tailoring ? the key skill used to adapt business analysis skills to all environments ? regardless of the delivery life cycle selected. Introduction What is agile The Agile Manifesto Agile principles Agile benefits Hands-on activity Learning and course objectives The current state of agile Agile trends Agile skills Value proposition The business case for agile The BA role changes on an agile project Hands-on activity Understanding project life cycles Project life cycle Product life cycle Incremental versus Iterative Hybrid approaches to delivery Choosing a project life cycle An in-depth look at Agile The agile development life cycle A sequence of iterations Essential concepts Inside each iteration Iteration goal Iteration planning Sequence of tasks Work period Testing End of iteration activities Evaluation and feedback Structured walkthroughs Evaluation guidelines The BA role in structured walkthroughs Scripting scenarios Defect list Retrospectives Hands-on exercise Type of Agile Delivery Approaches The flavors of agile Scrum Scrum roles Extreme Programming (XP) Dynamic System Development Method (DSDM) Feature Driven Development (FDD) Testing Best practices used by FDD Kanban Kanban Boards Agile Unified Process Scaling Frameworks Introduction to Agile Business Analysis What is business analysis? What is agile business analysis? Framework for agile business analysis Business analysis components International Institute of Business Analysis (IIBA©) Project Management Institute (PMI©) Context to business analysis Our industry BA standards Our industry Agile BA standards Product Owners What stays the same What is expected to change Agile requirements deliverables Lightweight documentation Requirements repository Where business analysis fits in The BA workload Hands-on exercise Business Analysis Tailoring Business analysis tailoring (defined) Tailoring considerations What tailoring looks like The PMI Guide to Business Analysis Determining the ?best? BA approach Methodology vs Standard Why use methodologies Determining your methodology Business analysis impacts Tools and techniques for agile business analysis Agile BA techniques Backlog refinements Behavior Driven Development (BDD) Burndown chart Collaborative games Definition of done Definition of ready INVEST Iteration planning Kanban board Minimum marketable features (MMF) Minimum viable product (MVP) MoSCoW Narrative writing Persona analysis Product roadmap Progressive Elaboration Prototyping Purpose alignment model Retrospectives Story slicing Hands-on Exercise Prioritization Techniques Requirements prioritization Prioritizing on agile projects Prioritization criteria Business benefit MoSCoW Pair-choice comparison Setting priorities with multi-voting Cost to acquire and operate Determining business value Story point estimating Planning poker Project velocity Hands-on activity Course wrap-up Making the transition to agile How my role will be different Course summary Retrospective Questions Additional course details: Nexus Humans BA08 - Agile for Business Analysts 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 BA08 - Agile for Business Analysts 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.
Have you ever felt that you are living life on autopilot? Going through the motions and being buffeted by life’s storms? If so, during this workshop, you will discover how to disengage your autopilot, to understand why we do what we do, gain clarity and a new perspective on what is happening in your life, plus explore the wonderful opportunities for positive change using NLP in order to take back the controls of your life.
Following on from the Macros course look at how you can write your own Visual Basic code within Excel to fully automate tasks and save time. Course overview Duration: 2 days (13 hours) Our VBA in Excel course is an introduction to using the Visual Basic for Applications language for programming in Excel. It looks at structures, syntax and coding standards. This course is designed for existing experienced users of Excel who can record and run macros and those who have dabbled in VBA but would like some formal training and help to put some structure to their code. Objectives By the end of the course you will be able to: Write visual basic procedures Create event and general procedures Use commands from the Excel data model Use statements and functions Use a selection of debugging tools Create and use variables and constants Use different types of loops Create an Excel user form Content The VBA environment Project explorer Excel objects Modules Properties window Code window Code structure Code structure Navigating within your code Adding comments Using WITH Steps to creating a VBA procedure Procedures Sub procedures Event procedures Calling procedures The Excel data model Workbook commands Worksheet commands Excel selection methods Data manipulation commands Debugging Using breakpoints Stepping through code The immediate window The watch window The locals window points Variables and Constants Declaring variables Declaring multiple variables Variable data types Concatenation Scope of variables Constants Declaring constants Using constants Scope of constants Looping Do while loops Do until loops For next loops Conditional Statements IF statement SELECT CASE statement Comparison statements Logical operators Creating a User Form Form layout The control toolbox Naming conventions Adding objects Naming objects Captions Displaying the form Object properties Object properties Setting properties at design time Setting properties at run time Interconnectivity between the user form and Excel Comparing values Transferring information Running code
Duration 5 Days 30 CPD hours This course is intended for This course will help you: Prepare for entry-level job roles in the high-demand area of data center environments Prepare for courses that support the Cisco Certified Network Professional Data Center certification exams Gain knowledge and hands-on skills through Cisco's unique combination of lessons and hands-on practice using enterprise-grade Cisco learning technologies, data center equipment, and software Overview After taking this course, you should be able to: Describe the foundations of data center networking Describe Cisco Nexus products and explain the basic Cisco NX-OS functionalities and tools Describe Layer 3 first-hop redundancy Describe Cisco Fabric Extender (FEX) connectivity Describe Ethernet port channels and virtual port channel (VPCs) Introduce switch virtualization, machine virtualization, and network virtualization Compare storage connectivity options in the data center Describe Fibre Channel communication between the initiator server and the target storage Describe Fibre Channel zone types and their uses Describe N-Port Virtualization (NPV) and N-Port Identifier Virtualization (NPIV) Describe data center Ethernet enhancements that provide a lossless fabric Describe Fibre Channel over Ethernet FCoE Describe data center server connectivity Describe Cisco UCS Manager Describe the purpose and advantages of APIs Describe Cisco ACI Describe the basic concepts of cloud computing The Understanding Cisco Data Center Foundations (DCFNDU) v1.0 course helps you prepare for entry-level data center roles. In this course, you will learn the foundational knowledge and skills you need to configure Cisco© data center technologies including: networking, virtualization, storage area networking, and unified computing. You will get an introduction to Cisco Application Centric Infrastructure (Cisco ACI), automation and cloud computing. You will get hands-on experience with configuring features on Cisco Nexus Operating System (Cisco NX-OS) and Cisco Unified Computing System (Cisco UCS). This course also earns you 30 Continuing Education (CE) credits towards recertification. Describing the Data Center Network Architectures Cisco Data Center Architecture Overview Three-Tier Network: Core, Aggregation, and Access Spine-and-Leaf Network Two-Tier Storage Network Describing the Cisco Nexus Family and Cisco NX-OS Software Cisco Nexus Data Center Product Overview Cisco NX-OS Software Architecture Cisco NX-OS Software CLI Tools Cisco NX-OS Virtual Routing and Forwarding Describing Layer 3 First-Hop Redundancy Default Gateway Redundancy Hot Standby Router Protocol Virtual Router Redundancy Protocol Gateway Load Balancing Protocol Describing Cisco FEX Server Deployment Models Cisco FEX Technology Cisco FEX Traffic Forwarding Cisco Adapter FEX Describing Port Channels and VPCs Ethernet Port Channels Virtual Port Channels Supported VPC Topologies Describing Switch Virtualization Cisco Nexus Switch Basic Components Virtual Routing and Forwarding Cisco Nexus 7000 Virtual Device Contexts (VDCs) VDC Types VDC Resource Allocation VDC Management Describing Machine Virtualization Virtual Machines Hypervisor VM Manager Describing Network Virtualization Overlay Network Protocols Virtual Extensible LAN (VXLAN) Overlay VXLAN Border Gateway Protocol (BGP) Ethernet VPN (EVPN) Control Plane VXLAN Data Plane Cisco Nexus 1000VE Series Virtual Switch VMware vSphere Virtual Switches Introducing Basic Data Center Storage Concepts Storage Connectivity Options in the Data Center Fibre Channel Storage Networking Virtual Storage Area Network (VSAN) Configuration and Verification Describing Fibre Channel Communication Between the Initiator Server and the Target Storage Fibre Channel Layered Model Fabric Login (FLOGI) Process Fibre Channel Flow Control Describing Fibre Channel Zone Types and Their Uses Fibre Channel Zoning Zoning Configuration Zoning Management Describing Cisco NPV Mode and NPIV Cisco NPV Mode NPIV Mode Describing Data Center Ethernet Enhancements Institute of Electrical and Electronic Engineers (IEEE) Data Center Bridging Priority Flow Control Enhanced Transmission Selection Data Center Bridging Exchange (DCBX) Protocol Congestion Notification Describing FCoE Cisco Unified Fabric FCoE Architecture FCoE Initialization Protocol FCoE Adapters Describing Cisco UCS Components Physical Cisco UCS Components Cisco Fabric Interconnect Product Overview Cisco I/O Module (IOM) Product Overview Cisco UCS Mini Cisco Integrated Management Controller (IMC) Supervisor Cisco Intersight? Describing Cisco UCS Manager Cisco UCS Manager Overview Identity and Resource Pools for Hardware Abstraction Service Profiles and Service Profile Templates Cisco UCS Central Overview Cisco HyperFlex? Overview Using APIs Common Programmability Protocols and Methods How to Choose Models and Processes Describing Cisco ACI Cisco ACI Overview Multitier Applications in Cisco ACI Cisco ACI Features VXLAN in Cisco ACI Unicast Traffic in Cisco ACI Multicast Traffic in Cisco ACI Cisco ACI Programmability Common Programming Tools and Orchestration Options Describing Cloud Computing Cloud Computing Overview Cloud Deployment Models Cloud Computing Services Additional course details: Nexus Humans Cisco Understanding Cisco Data Center Foundations v1.1 (DCFNDU) 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 Understanding Cisco Data Center Foundations v1.1 (DCFNDU) 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 5 Days 30 CPD hours This course is intended for Cloud Solutions Architects DevOps Engineers Individuals using Google Cloud Platform who deploy applications, monitor operations, and manage enterprise solutions Overview At course completion, you will have attained knowledge of: Fundamentals of Google Cloud Platform (GCP) Google Cloud Storage Google Compute Engine Google Cloud SQL Load Balancing (LB) Google Cloud Monitoring Auto-Scaling Virtual Private Cloud (VPC) Network Cloud Identity and Access Management (IAM) Cloud CDN and DNS Cloud VPN Google Cloud Deployment Manager Google Container Engine Cloud Run Cloud Bigtable Cloud Datastore Cloud BigQuery Cloud DataFlow Cloud DataProc Cloud Pub/Sub In this course you will attain a deep knowledge of Google Cloud Platform infrastructure and design patterns on developing applications on GCP. This course will prepare you for the Google Cloud Architect Associate Certification Exam. Fundamentals of Google Cloud Platform (GCP) Overview Regions and Zones Review of major GCP services Google Cloud Storage Fundamental APIs Consistency Cloud Storage Namespace Buckets and Objects Bucket and Object Naming Guidelines Encryption Object Versioning Object Lifecycle Management Access Control Access Control Lists Signed URL Multipart upload Resumable upload Understanding Pricing for Cloud Storage Offline Media Import/Export Architecture case study of common Use Cases of Google Cloud Storage Hands-on: Cloud Storage Lab; Creating Buckets, objects, and managing access control Google Compute Engine Compute Engine Architecture VM Instances types Persistence Disks Images Generating Custom Images IP Addresses Static IPs Ephemeral Access Control Options IAM Service Account Monitoring Instances with Google Cloud Monitoring Compute Engine Networks and Firewalls Hands-on: Hosting an Application on Compute Engine Google Cloud SQL Core advantages of Cloud SQL Cloud SQL database instance types Access Control High availability options Failover Read replica Backup options On Demand Automated Understanding Pricing of Cloud SQL Load Balancing (LB) Fundamentals of a Load Balancer Network Load balancing HTTPS Load balancing Cross region Load balancing Content Load balancing Target proxies SSL Load Balancing Internal Load Balancing Network Load Balancing Understanding Pricing for Load Balancer Google Cloud Monitoring Architecture of Cloud Monitoring Supported metrics Stackdriver Monitoring APIs Auto-Scaling Overview of Autoscaling Auto-scaling Fundamentals Instance groups Templates Policies Decisions Hands-on: Deploying a scale application on GCP using Autoscaling, Compute Engine, Cloud SQL, Load Balancers. Virtual Private Cloud (VPC) Network Salient features of Virtual Private Cloud (VPC) Network Infrastructure Virtual Private Cloud (VPC) Networking Fundamentals Subnetworks Firewall Internal DNS Network Routes Hands-on: Hosting Secure Applications in Google Cloud VPC Networks Cloud Identity and Access Management (IAM) Introduction User and Service Accounts IAM Roles Policy Hands-on: Managing Users, Policies and Granting Roles using Service Accounts Cloud CDN and DNS What is CDN Google Cloud CDN Cloud CDN Concepts Some of the Cloud CDN Edge locations Cloud DNS Cloud DNS Terminologies Supported Record Types Hands-on: Moving an Existing Domain Name to Cloud DNS Cloud VPN Cloud VPN overview Types of Cloud VPN Specifications Maintenance and Availability Google Cloud Deployment Manager Deployment Manager Deployment Manager Fundamentals Runtime Configurator Quotas Hands-on: Generating and Creating Cloud Deployment Manager Template Google Container Engine Google Container Engine Overview Docker Overview Kubernetes Terminologies Replication Controller Deployment Price and Quotas Hands-on: Deploying WordPress Cluster using Container Engine Cloud Run Overview of Cloud Run Deploy a Prebuilt Sample container Cloud Bigtable Overview of Cloud Bigtable Access Control Performance Locations Cloud Datastore Overview of Cloud Datastore Limits Storage Size Multitenancy Benefits of Multitenancy Encryption Locations Cloud BigQuery BigQuery Overview Interacting with BigQuery Datasets, Tables, and Views Partitioned Tables Query Plan Explanation Hands-on: Getting Started with BigQuery Cloud DataFlow Overview Programming Model DataFlow SDK 1.x for java Cloud Dataflow SDK 2.x Security and Permissions Advanced Access Control Cloud DataProc Overview Clusters Versioning Cloud Pub/Sub Overview of Cloud Pub/Sub Pub/Sub Concepts and Message Flow Data Model Cleanup of All Services Hands-on: Cloud Pub/Sub Lab with Background Cloud Function Additional course details: Nexus Humans Google Cloud Engineer Associate Certification Bootcamp 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 Google Cloud Engineer Associate Certification Bootcamp 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 Developers who have some familiarity with serverless and experience with development in the AWS Cloud Overview In this course, you will learn to: Apply event-driven best practices to a serverless application design using appropriate AWS services Identify the challenges and trade-offs of transitioning to serverless development, and make recommendations that suit your development organization and environment Build serverless applications using patterns that connect AWS managed services together, and account for service characteristics, including service quotas, available integrations, invocation model, error handling, and event source payload Compare and contrast available options for writing infrastructure as code, including AWS CloudFormation, AWS Amplify, AWS Serverless Application Model (AWS SAM), and AWS Cloud Development Kit (AWS CDK) Apply best practices to writing Lambda functions inclusive of error handling, logging, environment re-use, using layers, statelessness, idempotency, and configuring concurrency and memory Apply best practices for building observability and monitoring into your serverless application Apply security best practices to serverless applications Identify key scaling considerations in a serverless application, and match each consideration to the methods, tools, or best practices to manage it Use AWS SAM, AWS CDK, and AWS developer tools to configure a CI/CD workflow, and automate deployment of a serverless application Create and actively maintain a list of serverless resources that will assist in your ongoing serverless development and engagement with the serverless community This course gives developers exposure to and practice with best practices for building serverless applications using AWS Lambda and other services in the AWS serverless platform. You will use AWS frameworks to deploy a serverless application in hands-on labs that progress from simpler to more complex topics. You will use AWS documentation throughout the course to develop authentic methods for learning and problem-solving beyond the classroom. Introduction Introduction to the application you will build Access to course resources (Student Guide, Lab Guide, and Online Course Supplement) Thinking Serverless Best practices for building modern serverless applications Event-driven design AWS services that support event-driven serverless applications API-Driven Development and Synchronous Event Sources Characteristics of standard request/response API-based web applications How Amazon API Gateway fits into serverless applications Try-it-out exercise: Set up an HTTP API endpoint integrated with a Lambda function High-level comparison of API types (REST/HTTP, WebSocket, GraphQL) Introduction to Authentication, Authorization, and Access Control Authentication vs. Authorization Options for authenticating to APIs using API Gateway Amazon Cognito in serverless applications Amazon Cognito user pools vs. federated identities Serverless Deployment Frameworks Overview of imperative vs. declarative programming for infrastructure as code Comparison of CloudFormation, AWS CDK, Amplify, and AWS SAM frameworks Features of AWS SAM and the AWS SAM CLI for local emulation and testing Using Amazon EventBridge and Amazon SNS to Decouple Components Development considerations when using asynchronous event sources Features and use cases of Amazon EventBridge Try-it-out exercise: Build a custom EventBridge bus and rule Comparison of use cases for Amazon Simple Notification Service (Amazon SNS) vs. EventBridge Try-it-out exercise: Configure an Amazon SNS topic with filtering Event-Driven Development Using Queues and Streams Development considerations when using polling event sources to trigger Lambda functions Distinctions between queues and streams as event sources for Lambda Selecting appropriate configurations when using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis Data Streams as an event source for Lambda Try-it-out exercise: Configure an Amazon SQS queue with a dead-letter queue as a Lambda event source Writing Good Lambda Functions How the Lambda lifecycle influences your function code Best practices for your Lambda functions Configuring a function Function code, versions and aliases Try-it-out exercise: Configure and test a Lambda function Lambda error handling Handling partial failures with queues and streams Step Functions for Orchestration AWS Step Functions in serverless architectures Try-it-out exercise: Step Functions states The callback pattern Standard vs. Express Workflows Step Functions direct integrations Try-it-out exercise: Troubleshooting a Standard Step Functions workflow Observability and Monitoring The three pillars of observability Amazon CloudWatch Logs and Logs Insights Writing effective log files Try-it-out exercise: Interpreting logs Using AWS X-Ray for observability Try-it-out exercise: Enable X-Ray and interpret X-Ray traces CloudWatch metrics and embedded metrics format Try-it-out exercise: Metrics and alarms Try-it-out exercise: ServiceLens Serverless Application Security Security best practices for serverless applications Applying security at all layers API Gateway and application security Lambda and application security Protecting data in your serverless data stores Auditing and traceability Handling Scale in Serverless Applications Scaling considerations for serverless applications Using API Gateway to manage scale Lambda concurrency scaling How different event sources scale with Lambda Automating the Deployment Pipeline The importance of CI/CD in serverless applications Tools in a serverless pipeline AWS SAM features for serverless deployments Best practices for automation Course wrap-up Additional course details: Nexus Humans AWS Developing Serverless Solutions on AWS 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 AWS Developing Serverless Solutions on AWS 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 This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. 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: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.