2997 Design courses delivered Live Online

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 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 3 Days 18 CPD hours This course is intended for This intermediate course is for application programmers who need to write embedded SQL COBOL or PL/I programs in either a DB2 9 or DB2 10 for z/OS environment. Overview Incorporate static SQL statements in an application program Prepare the program for execution Validate execution results are correct Produce code to support multiple rows being returned from the database manager using cursors Identify considerations regarding units of work, concurrency, and restart of programs Identify differences between static and dynamic SQL Provide test data for applications Discuss program and DB2 options relative to performance of static SQL This course enables you to acquire the skills necessary to produce application programs that manipulate DB2 databases. Emphasis is on embedding Structured Query Language (SQL) statements and preparing programs for execution. CV720G;CF82G;DB2 Concepts Identify DB2 family products Explain DB2 workstation component functions Identify DB2 objects Identify the key differences between static SQL and other application alternatives for accessing DB2 data Program Structure I Embed INSERT, UPDATE, DELETE and single-row SELECT statements in application programs Effectively communicate with DB2 when processing NULL values and determining success of statement execution Demonstrate use of DB2 coding aids Code CONNECT statements within an application program Identify connection types and impacts on a unit of work Program for the Call Attach Facility (CAF) Program Preparation Identify the additional steps necessary to prepare a program that contains embedded SQL for execution Describe the functions of the DB2 PRECOMPILE and BIND processes Describe factors relevant to the BIND process, including RUNSTATS positioning, package status, parameters, and authorization requirements Program Structure II Use DECLARE, OPEN, FETCH, and CLOSE CURSOR statements to handle select criteria that may return multiple rows in application programs Issue positioned UPDATE and DELETE statements Identify how scrollable cursors can be used Recovery and Locking Concepts Define a unit of recovery Identify the basic locking strategies used by DB2 Dynamic SQL Introduction Describe the difference between static and dynamic SQL List the types of dynamic statements Code dynamic SQL in a program Managing Test Data Identify methods to insert data into a table Use the LOAD or IMPORT utility Identify the purpose of the RUNSTATS utility Identify the purpose of the REORG utility Performance Considerations Use programming techniques that enhance DB2 application performance by following general guidelines, using indexable predicates, and avoiding unnecessary sorts Identify the access paths available to DB2 List common causes of deadlocks and avoid such causes when possible Use the EXPLAIN tools as aids to develop applications that emphasize performance Additional course details: Nexus Humans CV722 IBM DB2 11 for z/OS Application Programming Workshop 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 CV722 IBM DB2 11 for z/OS Application Programming Workshop 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 is an intermediate and beyond level SQL course geared for experienced end users, data scientists, business analysts, application developers and database administrators. Students should have recently attended a basic SQL class or have equivalent experience. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment led by our expert practitioner, attendees will learn advanced skills needed to: Advanced Query Techniques Manipulating Table Data Using SQL's Data Manipulation Language (DML) User-Defined Functions Stored Procedures Triggers A company?s success hinges on responsible, accurate database management. Organizations rely on highly available data to complete all sorts of tasks, from creating marketing reports and invoicing customers to setting financial goals. Data professionals like analysts, developers and architects are tasked with creating, optimizing, managing and analyzing data from databases ? with little room for error. When databases aren?t built or maintained correctly, it?s easy to mishandle or lose valuable data. Our SQL Programming and Database Training Series provides students with the skills they require to develop, analyze and maintain data and in correctly structured, modern and secure databases. Next Level SQL explores how to identify and use advanced querying techniques to manipulate and index tables. All hands-on work in this course is ANSI SQL compliant and should work with most SQL databases such as Oracle, SQL Server, MySQL, MS Access, Informix, Sybase, or any other ANSI SQL compliant database. Advanced Query Techniques Join inner outer (Left, Right, Full) Subqueries Simple Correlated Using the Exists Operator Tips for Developing Complex Queries Performing Set Operations Aggregating Results Using Group by Creating Temporary Tables Manipulating Table Data Using SQL's Data Manipulation Language (DML) Inserting Data into Tables Updating Existing Data Deleting Records Truncating Tables Implementing Data Integrity with Transactions Beginning Explicit Transactions Committing Transactions Rolling Back Transactions User-Defined Functions Definition and Benefits of Use CREATE FUNCTION Syntax RETURN Clause and the RETURNS Statement Scalar vs. Table Functions Comparison with Stored Procedures Returning Scalar Values and Tables ALTER and DROP FUNCTION Stored Procedures Definition and Benefits of Use CREATE PROCEDURE Syntax Variables and Parameters Control of Program Flow ALTER and DROP PROCEDURE Implementation Differences Triggers Definition and Benefits of Use Alternatives (e.g., Constraints) CREATE TRIGGER Syntax Trigger Types 'Inserted' (or 'NEW') and 'Deleted' (or 'OLD') Tables Event Handling and Trigger Execution ALTER and DROP TRIGGER Additional course details: Nexus Humans Advanced SQL Programming (TTSQL005) 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 Advanced SQL Programming (TTSQL005) 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 Network Security Operations Workload Application Administrators Security Operations Field Engineers Network Engineers Systems Engineers Technical Solutions Architects Cisco Integrators and Partners Overview After taking this course, you should be able to: Define the Cisco telemetry and analytics approach. Explore common scenarios that Cisco Tetration Analytics can solve. Describe how the Cisco Tetration Analytics platform collects telemetry and other context information. Discuss how relative agents are installed and configured. Explore the operational aspects of the Cisco Tetration Analytics platform. Describe the Cisco Tetration Analytics support for application visibility or application insight based on the Application Dependency Mapping (ADM) feature. List the concepts of the intent-based declarative network management automation model. Describe the Cisco Tetration policy enforcement pipeline, components, functions, and implementation of application policy. Describe how to use Cisco Tetration Analytics for workload protection in order to provide a secure infrastructure for business-critical applications and data. Describe Cisco Tetration Analytics platform use cases in the modern heterogeneous, multicloud data center. List the options for the Cisco Tetration Analytics platform enhancements. Explain how to perform the Cisco Tetration Analytics administration. This course teaches how to deploy, use, and operate Cisco© Tetration Analytics? platform for comprehensive workload-protection and application and network insights across a multicloud infrastructure. You will learn how the Cisco Tetration Analytics platform uses streaming telemetry, behavioral analysis, unsupervised machine learning, analytical intelligence, and big data analytics to deliver pervasive visibility, automated intent-based policy, workload protection, and performance management. Exploring Cisco Tetration Data Center Challenges Define and Position Cisco Tetration Cisco Tetration Features Cisco Tetration Architecture Cisco Tetration Deployment Models Cisco Tetration GUI Overview Implementing and Operating Cisco Tetration Explore Data Collection Install the Software Agent Install the Hardware Agent Import Context Data Describe Cisco Tetration Operational Concepts Examining Cisco Tetration ADM and Application Insight Describe Cisco Tetration Application Insight Perform ADM Interpret ADM Results Application Visibility Examining Cisco Tetration Intent-Based Networking Describe Intent-Based Policy Examine Policy Features Implement Policies Enforcing Tetration Policy Pipeline and Compliance Examine Policy Enforcement Implement Application Policy Examine Policy Compliance Verification and Simulation Examining Tetration Security Use Cases Examine Workload Security Attack Prevention Attack Detection Attack Remediation Examining IT Operations Use Cases Key Features and IT Operations Use Cases Performing Operations in Neighborhood App-based Use Cases Examining Platform Enhancement Use Cases Integrations and Advanced Features Third-party Integration Examples Explore Data Platform Capabilities Exploring Cisco Tetration Analytics Administration Examine User Authentication and Authorization Examine Cluster Management Configure Alerts and Syslog Additional course details: Nexus Humans Cisco Implementing Cisco Tetration Analytics v1.0 (DCITET) 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 Implementing Cisco Tetration Analytics v1.0 (DCITET) 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 4 Days 24 CPD hours This course is intended for The audience for this course is either: a Dynamics 365 consultant who wants to learn Commerce, or a retail analyst with core Dynamics 365 experience who wants to apply their skills to the Dynamics product family. Overview After completing this course, students will be able to: Configure Dynamics 365 Commerce Headquarters Configure products, prices, discounts, loyalty, and affiliations Manage Point of Sale (POS) in Dynamics 365 Commerce Configure and Manage Dynamics 365 Commerce call centers Manage e-commerce Dynamics 365 Commerce functional consultants set up and use the application functionality in Dynamics 365 Commerce, and provide support for the application. The functional consultant typically has a strong understanding of unified commerce business operations, and experience configuring, deploying, maintaining, and using Microsoft Dynamics 365 Commerce. This four-day course covers the essentials for the role Module 1: Get started with Dynamics 365 Commerce Introduction to Unified Commerce platform Dynamics 365 Commerce architecture Deployment of Dynamics 365 Commerce Hardware and peripherals Module 2: Configure Commerce Headquarters Configure prerequisites and Commerce parameters Configure and maintain payment processing Configure Commerce Data Exchange (CDX) Configure delivery modes and charges Configure and work with statements Module 3: Products and Merchandising Product information management Merchandising in Dynamics 365 Commerce Product recommendations and product discovery Module 4: Retail Pricing Manage Pricing Manage discounts and promotions Module 5: Loyalty and customer experience Customer Management Loyalty and affiliations Module 6: Point of sale Introduction to POS Channel Setup Configure Cash and Shift management Worker Setup Point of Sale Setup Customer management at POS Transaction processing Inventory processing End of day processing Reporting Configure and work with Task management Test POS Maintain registers and devices Localization Module 7: Configure and work with call centers in Dynamics 365 Commerce Configure channel Configure Product Catalogs Configure Order Holds Create call center orders Configure call center directed selling Configure Returns and Refunds Configure continuity orders and installment billing Module 8: Work with E-Commerce in Dynamics 365 Commerce Describe e-commerce core capabilities Configure an E-Commerce Channel in Dynamics 365 HQ Configure an E-Commerce site Configure and manage E-Commerce site content Describe & Demonstrate digital asset management Configure business-to-business (B2B) site Configure Ratings and reviews functionality Demonstrate E-Commerce Order Processing Module 9: Manage order fulfillment and inventory in Dynamics 365 Commerce Configure and work with Stock replenishment Configure and work with Order fulfillment Module 10: Work with Dynamics 365 Fraud Protection Overview of Dynamics Fraud Protection Describe Dynamics Fraud Protection Services Configure and work with Dynamics Fraud Protection with Dynamics 365 Commerce Additional course details: Nexus Humans MB-340T00: Microsoft Dynamics 365 Commerce Functional Consultant 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 MB-340T00: Microsoft Dynamics 365 Commerce Functional Consultant 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 Experienced system administrators, system engineers, and system integrators. Overview Configure and manage VMware ESXi? networking and storage for a large and sophisticated enterprise Use VMware vSphere© Client?, VMware vSphere© Web Client, and VMware vSphere© ESXi? Shell to manage vSphere Use VMware vSphere© Auto Deploy? and host profiles to provision ESXi hosts Optimize the performance of all vSphere components Use VMware vRealize© Log Insight? to monitor system logs Deploy VMware vCenter© Server Appliance? to be highly available and optimized for performance Migrate a Windows vCenter Server system to vCenter Server Appliance 6.5 Harden the vSphere environment against security threats Encrypt virtual machines for additional security This advanced course provides students with advanced knowledge of configuring and operating a highly available and scalable virtual infrastructure. Course Introduction Introductions and course logistics Course objectives Identify additional resources for after this course Identify other VMware Education offerings Describe the user interfaces available in vSphere 6.5 Network Scalability Configure and manage vSphere distributed switches Explain distributed switch features such as port mirroring, LACP, QoS tagging, and NetFlow Storage Scalability Explain VMware vSphere© Storage APIs - Array Integration and VMware vSphere© API for Storage Awareness? Configure and assign virtual machine storage policies Configure VMware vSphere© Storage DRS? and VMware vSphere© Storage I/O Control Create and use virtual volumes in vSphere Host and Management Scalability Explain the uses of VMware vCenter© Converter? Define and use content libraries Describe and use host profiles Describe and use VMware vSphere© ESXi? Image Builder CLI and vSphere Auto Deploy CPU Optimization Explain the CPU scheduler operation, NUMA support, and other features that affect CPU performance Use esxtop to monitor key CPU performance metrics Memory Optimization Explain ballooning, memory compression, and host-swapping techniques for memory reclamation when memory is overcommitted Use esxtop to monitor key memory performance metrics Storage Optimization Describe storage queue types and other factors that affect storage performance Use esxtop to monitor key storage performance metrics 8 Network Optimization Network Optimization Explain the performance features of network adapters Explain the performance features of vSphere networking Use esxtop to monitor key network performance metrics Analyzing vSphere Explain how Proactive DRS enhances virtual machine availability Use vRealize Log Insight to identify and troubleshoot issues vCenter Server Availability and Performance Describe the high availability options for vCenter Server and VMware Platform Services Controller? Describe and use VMware vCenter Server© High Availability Identify the factors that influence vCenter Server performance Migrate a Windows vCenter Server 5.5 system to vCenter Server Appliance 6.5 vSphere Security Configure ESXi host access and authorization Secure ESXi, vCenter Server, and virtual machines Use VMware Certificate Authority to configure vSphere certificate management Configure vSphere to encrypt virtual machines, core dumps Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSphere 6.5 Optimize and Upgrade 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 VMware vSphere 6.5 Optimize and Upgrade 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 introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Experienced Programmers and Systems Administrators. Overview Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices. Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to: ? Create working Python scripts following best practices ? Use python data types appropriately ? Read and write files with both text and binary data ? Search and replace text with regular expressions ? Get familiar with the standard library and its work-saving modules ? Use lesser-known but powerful Python data types ? Create 'real-world', professional Python applications ? Work with dates, times, and calendars ? Know when to use collections such as lists, dictionaries, and sets ? Understand Pythonic features such as comprehensions and iterators ? Write robust code using exception handling An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features. An Overview of Python What is python? 1 -- An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Built-in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings The standard library The sys module Launching external programs Math functions Random numbers The string module Reading CSV data Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the file system Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations 17 ? Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network services Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Parsing command-line options Detecting the current platform Trapping signals Implementing logging Python Timeline Advantages/Disadvantages of Python Getting help with pydoc

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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.