4302 Pha courses

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Solutions Architects and Engineers who perform cloud migrations IT Project Managers who are involved in projects related to migrating existing workloads to the AWS Cloud Overview This course is designed to teach you how to: Explain the various cloud migration strategies Assess cloud migration readiness Discover your portfolio and plan for migration Plan and design your application migration strategy Perform and validate application migration to the cloud Optimize your applications and operations after migrating to the cloud Migrating to AWS focuses on planning and migrating existing workloads to the AWS Cloud. The course covers various cloud migration strategies with a detailed discussion on each phase of the migration process, including portfolio discovery, application migration planning and design, migration execution, and post-migration validation and application optimization. This course is designed for Solutions Architects and Engineers who perform cloud migrations, have an understanding of core AWS services and design patterns covered in Architecting on AWS. This course is also available to IT project managers involved in the planning of those migrations who have completed AWS Technical Essentials Module 1: Migrating to AWS ? Overview Migration process 'Mental Model' Cloud Migration Strategies Comparing Cloud Migration Strategies Cloud Center of Excellence (CoE) Cloud Migration Readiness Assessment AWS Cloud Migration Process Group activity: Creating a high-level migration plan Module 2: Discovery and analysis Migration Process Roadmap AWS Migration Methodology AWS Application Discovery Service Portfolio Analysis Hands-on lab 1: Performing discovery Module 3: Migration planning and design (part I) AWS Migration Hub Pricing and Availability Process Group activity: Creating a detailed migration plan Module 3: Migration planning and design (continued) Application migration ordering Application prioritization criteria Defining success criteria Migration methodology Designing for migration Module 4: Migration, integration, and validation Migration considerations Data migration AWS Snow Services AWS Data Migration Service (DMS) Server migration Demonstration: Server migration service Hands-on lab 2 : Migrating databases to AWS EC2 Hands-on lab 3 : Migrating databases to Amazon Aurora Module 5: Operations and optimization On premises vs. cloud IT operations Optimizing in the AWS Cloud Case study: Optimizing an application

Duration 2 Days 12 CPD hours This course is intended for The audience for this course is data professionals and data architects who want to learn about migrating data platform technologies that exist on Microsoft Azure and how existing SQL based workloads can be migrated and modernized. The secondary audience for this course is individuals who manage data platforms or develop applications that deliver content from the existing data platform technologies. Overview Understand Data Platform Modernization Choose the right tools for Data Migration Migrate SQL Workloads to Azure Virtual Machines Migrate SQL Workloads to Azure SQL Databases Migrate SQL Workloads to Azure SQL Database Managed Instance In this course, the students will explore the objectives of data platform modernization and how it is suitable for given business requirements. They will also explore each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances. The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. Introducing Data Platform Modernization Understand Data Platform Modernization Understanding the stages of migration Data Migration Paths Choose the right tools for Data Migration Discover the Database Migration Guide Build your data estate inventory using Map Toolkit Identify Migration candidates using Data Migration Assistant Evaluate a Data workload using Database Experimentation Assistant Data Migration using Azure Database Migration Service Migrate non-SQL Server workloads to Azure using SQL Migration Assistant Migrating SQL Workloads to Azure Virtual Machines Considerations of SQL Server to Azure VM Migrations SQL Workloads to Azure VM Migration Options Implementing High Availability and Disaster Recovery Scenarios Migrate SQL Workloads to Azure SQL Databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL DB offline Migrate SQL Server to Azure SQL DB online Load and Move data to Azure SQL Database Migrate SQL Workloads to Azure SQL Database Managed Instance Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed instance Load and Move data to SQL Database Managed instance Application Configuration and Optimization

Duration 2 Days 12 CPD hours This course is intended for This course is designed for individuals in a variety of job roles whose primary responsibility is not project management, but who manage projects on an informal basis; who contribute as members of a project team; or who wish to incorporate project management practices into their personal work. It is also beneficial for anyone who is considering a career path in project management and desiring a complete overview of the field and its generally accepted practices. Overview In this course, you will identify the elements of sound project management and apply the generally recognized project management practices to successfully manage or participate in projects. You will: Identify the key processes and requirements of project management. Initiate a project. Use a Predictive approach to plan for time and cost. Use an Adaptive approach to plan a project. Plan for project risks, communication, and change control. Manage the execution of a project. Close a project. This course teaches the fundamentals of project management and its underlying structure and elements, including project phases, project life cycles, stakeholders, and areas of expertise. These, coupled with the ability to identify the project management processes that are recognized industry wide as good practice, will help you to apply effective project management techniques to improve the efficiency of your projects and ensure their success. This course is designed to cover various project management approaches and is not intended to focus on a single methodology or framework. Lesson 1: Getting Started with Project Management Topic A: Identify the Characteristics of a Project Topic B: Identify the Project Approach Topic C: Identify the Leadership Roles in a Project Lesson 2: Initiating a Project Topic A: Create a Project Scope/Vision Statement Topic B: Identify the Essential Skills for a Project Team Topic C: Identify the Risks to a Project Lesson 3: Planning for Time and Cost in Predictive Projects Topic A: Create a WBS Topic B: Create a Project Schedule Topic C: Determine Project Costs Lesson 4: Planning for Adaptive Projects Topic A: Create Epics and User Stories Topic B: Build a Product Backlog Topic C: Create an Initial Release Plan Topic D: Conduct a Sprint Planning Meeting Topic E: Replan the Project Lesson 5: Planning for Project Risks, Communication, and Change Control Topic A: Analyze the Risks to a Project Topic B: Create a Communication Plan Topic C: Develop a Change Control Plan Lesson 6: Managing a Project Topic A: Begin Project Work Topic B: Execute the Project Plan Topic C: Track the Progress of an Adaptive Project Topic D: Report Project Performance Topic E: Implement Change Control Lesson 7: Closing a Project Topic A: Close a Sprint, a Release, or an Adaptive Project Topic B: Close a Predictive Project Topic C: Create a Final Report

Duration 2 Days 12 CPD hours This course is intended for This is highly recommended for everyone in a company who works in a Scrum Team or anyone who interacts with any Scrum Team. This will also be very useful for those who are interested in understanding the basics of Scrum and how this method could be used effectively. Overview To ensure that students understand the basics of Scrum To enable Scrum Team members to effectively contribute to a Scrum project. To enable Scrum Team members to apply Scrum effectively in Scrum/Agile projects. In this course, students learn to understand the basics of Scrum, effectively contribute to a Scrum project, and learn how to enable Scrum Team members to apply Scrum effectively in Scrum/Agile projects.Successful candidates will be awarded the Scrum Developer Certified (SDC?) certification by SCRUMstudy after passing the included certification exam. Introduction Agile Overview Scrum Overview Principles The Six Scrum Principles Organization Core Roles and Non-core Roles Business Justification Value-driven Delivery Factors used to Determine Business Justification Confirm Benefits Realization Quality Quality Defined Quality, Scope and Business Value Quality Management in Scrum Change Unapproved and Approved Changes Change in Scrum Risk Risks and Issues Risk Management Procedure Introduction to Scrum Project PhasesInitiate Create Project Vision Process Identify Scrum Master and Stakeholders Process Form Scrum Team and Develop Epics processes Create Prioritized Product Backlog and Conduct Release Planning Processes Plan and Estimate Create User Stories Process Estimate User Stories and Commit User Stories Processes Identify Tasks and Estimate Tasks Processes Create Sprint Backlog Process Implement Create Deliverables and Conduct Daily Stand-up processes Groom Prioritized Product Backlog Process Review and Retrospect Demonstrate and Validate Sprint Process Retrospect Sprint Process Additional course details: Nexus Humans Scrum Developer Certified (SDC) 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 Scrum Developer Certified (SDC) 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 certification is appropriate for anyone who is interested in working as a Scrum Master or for someone who is already a Scrum master in his organization. Scrum Master is an important role in any Scrum team and need not be a technology expert to be effective. Moreover, although Scrum is popular in the IT industry, it can be used effectively across different industries. The SBOK Guide, on which the SMC course is based on, can be used as an effective guide for implementation. Overview The participants will be prepared to take SMC™ certification exam and pass. Also they will be able to apply the concepts in their day to day job. This course guides & teaches Scrum practices to everyone involved in the project; clears impediments for the team; and, ensures that Scrum processes are being followed. Successful candidates will be awarded the Scrum Master Certified (SMC?) certification by SCRUMstudy after passing the included certification exam. The certification exam voucher is included in this course so you can take the exam at your convenience. Introduction Course Objectives Course Methodology Certification Schema Exam Format Overview of Agile Agile Manifesto Agile Principles What has Changed Agile Methods Overview of Scrum Definition and brief history of Scrum Why Scrum Scrum vs. Traditional Project Management Benefits of Scrum Overview of A Guide to the Scrum Body of Knowledge (SBOK? Guide) Framework of the SBOK? Guide Who uses the SBOK? Guide How to use the SBOK? Guide Scrum Flow Principles Empirical Process Control Self-organization Collaboration Value-based Prioritization Time-boxing Iterative Development Scrum Aspects Organization Business Justification Quality Change Risk Scrum Phases and Processes Initiate Plan and Estimate Implement Review and Retrospect Release Scaling Scrum Scaling Scrum for Large Projects Scaling Scrum for the Enterprise Transition to Scrum Mapping Traditional Roles To Scrum Maintaining Stakeholder Involvement Importance Of Executive Support Additional course details: Nexus Humans Scrum Master Certified (SMC) 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 Scrum Master Certified (SMC) 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 This course is for wireless engineers who work in the following roles: Consulting systems engineer Network administrator Network engineer Network manager Sales engineer Systems engineer Technical solutions architect Wireless design engineer Wireless engineer Overview After taking this course, you should be able to: Describe and implement a Cisco-recommended structured design methodology Describe and implement industry standards, amendments, certifications, and Requests For Comments (RFCs) Describe and implement Cisco enhanced wireless features Describe and implement the wireless design process Describe and implement specific vertical designs Describe and implement site survey processes Describe and implement network validation processes The Designing Cisco Enterprise Wireless Networks (ENWLSD) v1.1 course gives you the knowledge you need to design Cisco© wireless networks. The course covers design specifics from scenario design concepts through the installation phase and into post-deployment validation.This course, including the self-paced material, helps prepare you to take the exam, Designing Cisco Enterprise Wireless Networks (300-425 ENWLSD), which leads to to the new CCNP© Enterprise and Cisco Certified Specialist ? Enterprise Wireless Design certifications. Describing and Implementing a Structured Wireless Design Methodology Importance of Planning Wireless Design with a Structured Methodology Cisco Structured Design Model Cisco Design Guides and Cisco Validated Designs for Wireless Networks Role of the Project Manager When Designing Wireless Networks Describing and Implementing Industry Protocols and Standards Wireless Standards Bodies Institute of Electrical and Electronics Engineers (IEEE) 802.11 Standard and Amendments Wi-Fi Alliance (WFA) Certifications Relevant Internet Engineering Task Force (IETF) Wireless RFCs Practice Activity Describing and Implementing Cisco Enhanced Wireless Features Hardware and Software Choices for a Wireless Network Design Cisco Infrastructure Settings for Wireless Network Design Cisco Enhanced Wireless Features Examining Cisco Mobility and Roaming Mobility and Intercontroller Mobility in a Wireless Network Optimize Client Roaming in a Wireless Network Cisco Workgroup Bridge (WGB) and WGB Roaming in a Wireless Network Describing and Implementing the Wireless Design Process Overview of Wireless Design Process Meet with the Customer to Discuss the Wireless Network Design Customer Information Gathering for a Wireless Network Design Design the Wireless Network Deployment of the Wireless Network Validation and Final Adjustments of the Wireless Network Wireless Network Design Project Documents and Deliverables Describing and Implementing Specific Vertical Designs Designs for Wireless Applications Wireless Network Design Within the Campus Extend Wireless Networks to the Branch Sites Examining Special Considerations in Advanced Wireless Designs High-Density Designs in Wireless Networks Introducing Location and Cisco Connected Mobile Experiences (CMX) Concepts Design for Location FastLocate and HyperLocation Bridges and Mesh in a Wireless Network Design Redundancy and High Availability in a Wireless Network Describing and Implementing the Site Survey Processes Site Survey Types Special Arrangements Needed for Site Surveys Safety Aspects to be Considered During Site Surveys Site Survey Tools in Cisco Prime Infrastructure Third-Party Site Survey Software and Hardware Tools Describing and Implementing Wireless Network Validation Processes Post-installation Wireless Network Validation Making Post-installation Changes to a Wireless Network Wireless Network Handoff to the Customer Installation Report

Duration 2 Days 12 CPD hours This course is intended for Participants who have actual experience in the data centre and/or IT infrastructures are best suited. Attendance of the CDCP© course is recommended but not a requirement. Overview After completion of the course the participant will be able to: 1. Develop and review their data centre strategy 2. Use different risk assessment methodologies together with practical tips specifically for data centre migrations to reduce the risk during a data centre migration 3. Understand different migration strategies 4. Understand the legal aspects when migrating a data centre 5. Understand the importance of Business Service Reviews and Service Level Objectives 6. Size and design the target data centre 7. Understand the importance of detailed discovery and how dependencies influence migration waves 8. Understand the safety requirements during migration 19. Get lots of practical tips when moving to another data centre This course is designed to expose participants to a step-by-step methodology which will enable them to reduce the risks involved when undertaking a data centre migration. It will also give participants a lot of valuable practical hints and tips by trainers having extensive experience in moving and consolidating mission critical data centre. Data Centre Strategy Data centre lifecycle Reasons to migrate a data centre Alternatives to data centre migration Consolidation Outsourcing Cloud computing Upgrade existing data centre or build new Project Management Project management and methods Scope statement Statement Of Work (SOW) Work Breakdown Structure (WBS) Allocate time to the project Cost and estimation methodology Project communication Risk Management Risk management and methods Risk identification Risk assessment methodologies Qualitative approach Semi-quantitative approach Quantitative approach Risk evaluation Risk treatment Risk in data centre migrations Migration Strategies Different data centre migration strategies Heterogeneous migration Homogeneous migration Physical migration Different IT transformations Pre-migration transformation Migration transformation Post-migration transformation Legal Aspects Regulatory requirements Contractual considerations Legal aspects when decommissioning High Level Discovery & Planning The importance of Business Service Reviews The concept of Availability The concept of Recoverability The importance of Service Level Objectives Requirements on designing the target IT architecture Information needed for high level planning Design Target Data Centre Requirements for the target data centre Sizing the data centre Architectural requirements Cooling requirements Power requirements Security Detailed Discovery and Planning The importance of discovery Automated discovery tools Asset management Network and system dependencies Detailed migration planning Migration waves Staffing Warranties and insurance Safety Safety precautions Technical safety review Electrical safety Lifting Personal safety during migration Fire safety during migration Security Controversy between access and security Access control Managing security during migration Security during migration Key management Practical hints and tips Continuous improvement Implementation Rehearsal Route investigation Resourcing Logistics team Packing Transport Installing the equipment Post migration support End of Project Why project closure Lessons learned Phased completion of project Criteria for project closure The outcome of the project End of project Exam: Certified Data Centre Migration Specialist Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Duration 5 Days 30 CPD hours This course is intended for For those seeing to prepare for CCIE Enterprise Infrastructure certification Overview This course will help prepare for CCIE Enterprise Infrastructure certification The new CCIE Enterprise Infrastructure certification program prepares you for today?s expert-level job roles in enterprise infrastructure technologies. CCIE Enterprise Infrastructure now includes automation and programmability to help you scale your enterprise infrastructure. VTP VTP and different versions Pruning EtherChannel LACP Layer 2 and Layer 3 Spanning Protocol 1d, 802.1w, and 802.1s SPAN, RSPAN, and ERSPAN DMVPN All Phases Redundancy: Two Clouds One Hub Two Hubs one Cloud Two hubs two Clouds Running Routing Protocols DMVPN over MPLS EIGRP RD, CD, S, FC, FS, and FD Configuration, and hidden debugging Authentications: MD5, and SHA, Summarization Load Balancing:Equal Cost, Unequal Cost, Add-Path, Filtering, Default Route Injection Optimization: Query Propagation Boundary, IP FRR, STUB routing (All Options) Metric: Classic, Wide Metric Route Tags: Decimal and Dotted-Decimal Notations, OTP OSPFv2 Overview and special cases GRE or Virtual-Links LSAs, FA, and RFCs (1583, 1587, 2328, 3101, 5185 and many more) Best Path Selection Network Types Area Types Optimization: GTSM, LFA, Default Route Injection Authentication: RFC 2328, RFC 5709, Summarization, Filtering BGP States Establishing a Peer Session: Regular method,Peer-Groups,Templates,Best Path Selection Attributes: Weight, AS-Path, Origin, Next-Hop, Local-Preference, Atomic-Aggregate Communities, Aggregator, and MED Load Balancing: Equal Cost,Unequal Cost,Conditional Advertisement,Out/In Bound Route Filtering and the order,ORF,Multihoming Scenarios AS-Path Manipulation: Regexp,Local-as,Allow-as,Remove-Private-as Convergence and Scalability: Route Reflectors,Confederation,Aggregation (All Options) Other BGP Features: MultiPath,Add-Path,Route-Refresh,Soft Reconfiguration IPv6 Acquiring an IPv6 Address: IPv6 General Prefix SLAAC DHCPv6 Rapid-Commit Relay Prefix Delegation IPv6 and DMVPN EIGRPv6 OSPFv3: Both flavors, LSAs, RFCs BGP for IPv6: IPv6 transport, and IPv4 route exchange Transitional Solutions: NAT-PT,6VPE,Multicast,MLD,Static RP,BSR,Embedded RP,IPv6 Traffic Filters,RA Guard,ND Inspection MPLS LDP, VRFs, RD, and RT L3VPNs Route Leaking PE to CE Routing Security Control Plane Policing VACLs Storm Control DHCP Snooping IP Source Guard DAI Private VLANs Port Security Access-lists uRPF Device Tracking IPsec Identity Use Case For FlexVPN: Site-to-Site, IKEv1, and IKEv2 Using Preshared Keys 1x Port Base Authentication : Device Roles,Port States,Authentication Process,Host Modes Network Services FHRP: HSRP, VRRP, and GLBP NAT: Static NAT, and PAT,Dynamic NAT,Policy-Base NAT,VRF-Aware NAT,VASI NAT Software Defined Infrastructure Cisco SD Access: Design a Cisco SD Access solution Underlay network (IS-IS, manual/PnP) Overlay fabric design (LISP, VXLAN, Cisco TrustSec) Fabric domains (single-site and multi-site using SD-WAN transit) Cisco SD Access deployment: Cisco DNA Center device discovery and device management Add fabric node devices to an existing fabric Host onboarding (wired endpoints only) Fabric border handoff Segmentation Macro-level segmentation using VNs Micro-level segmentation using SGTs (using Cisco ISE) Assurance Network and client health (360) Monitoring and troubleshooting Cisco SD-WAN: Design a Cisco SD-WAN solution Orchestration plane (vBond, NAT) Management Plane (vManage) Control Plane (vSmart, OMP) Data Plane (vEdge/cEdge) WAN edge deployment Onboarding new edge routers Orchestration with zero-touch provisioning/PnP OMP TLOC Configuration templates Localized policies (only QoS) Centralized policies Application aware Routing Topologies

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline 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 The Machine Learning Pipeline 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 course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.