3044 Software Development courses

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 0.5 Days 3 CPD hours This course is intended for This course is intended for: Line of Business (LoB) owners, IT leaders, and executives Overview In this course, you will learn to: Explain the role of information technology (IT) in an organization for business transformation Explain the customer value proposition for using the cloud across industries Define key characteristics of cloud computing Explain the cloud business model Identify key security practices of cloud computing Frame the cloud business value using the Cloud Value Framework In this course, you will learn the fundamental concepts of cloud computing and how a cloud strategy can help companies meet business objectives. It explores the advantages and possibilities of cloud computing. It also introduces addresses concepts such as security and compliance to help facilitate better discussions with line of business (LOB) professionals, information technology (IT) LoB, IT leaders, and executives. Module 1: Course Introduction Course Introduction Module 2: Information Technology for Business Transformation Role of IT in an organization for business transformation Brief history of IT Legacy approach to IT What drives customers to move from traditional infrastructure to the cloud Module 3: Cloud Computing Define cloud computing Key characteristics of cloud technology The cloud business model Key security practices within the cloud Module 4: Business Value of the Cloud The customer value proposition Identify who is using cloud computing Industry trends Customer examples Module 5: The Cloud Value Framework Introduction to the Cloud Value Framework Cost Savings Staff Productivity Operational Resilience Business Agility Module 6: Business Value Activity Business Value Activity Additional course details: Nexus Humans AWS Cloud Essentials for Business Leaders 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 Cloud Essentials for Business Leaders 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 geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts 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. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This day-long workshop gives participants a thorough understanding of the iPad iOS operating system. This course is designed for both those who want to learn more about their iPads, those who work in business environments and who want to integrate the iPad into their existing company?s infrastructure, as well as personnel who are responsible for supporting other iPad users. Setting Up The iPad iPad Essentials The Home Screen Launching and Running Apps Changing Screen Orientation Locking the Rotation The Control Center Creating Folders Accessibility and Voice Over Settings General Settings Parameters Passcode Setting Up Notifications Location Services iCloud and Synching your iPad Other Application Settings Multi-Touch Gestures Tap, Touch and Hold Drag, Flick and Swipe Pinch, Rotate and Shake Switching Between Applications Using the Apple Applications Showing and Hiding Applications Closing Documents vs. Quitting Applications Working With Documents Type, Select, Cut, Copy, Paste and Replace Understanding the iPad Keyboard Opening Pages, Numbers and Keynote Accessing Files and Documents Copying files between the iPad and Computer Working with Microsoft Office Connecting To The Internet WI-FI and Bluetooth Devices Through Servers Browsing and Searching The Web Enterprise Network The iPad In Business iOS Security Deployment Seamless Integration Mobile Device Management Printing with AirPrint Creating Passcodes Working with Photos and Camera Photos and Video Recording Video Integrating Photos or Video Into Documents or Presentations Mirroring Video Finding and Installing Apps The App Store Apps for Enterprise Installing and Deleting Apps Resetting the iPad Connecting and Mirroring with the iPhone Battery Issues Tips for Improving Battery Use Rebooting the iPad Hidden Keystrokes Troubleshooting Connectivity Issues ReInstalling Apps Preserving Batter Power Accessibility Functions Additional course details: Nexus Humans iPad For Business 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 iPad For Business 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 is an intermediate course for POWER i administrators, IBM Business Partners, and anyone else who would like practical knowledge of the features and functions supported by BRMS. Overview Describe the major features and functions of BRMS List the steps to install BRMS on a single system or in a BRMS Network environment Implement a previously defined backup and recovery strategy using BRMS Implement a previously defined archival and retrieval plan, including dynamic retrieval, using BRMS Explain how to utilize a tape drive, tape library system, virtual tape, and optical drive with BRMS Implement and use BRMS using the green screen, System i Navigator, and IBM Navigator for i This course covers the features & functions supported by Backup Recovery & Media Services (BRMS). Learn how to perform the supported functions when using a 5250 emulation session, when using System i Navigator, & when using IBM Navigator for i. Overview of BRMS . Installing BRMS . BRMS policies overview . Media devices and encryption using software and hardware . Overview and implementation of virtual tape, DVD, and optical device support . Creating a simple backup control group . BRMS log . Saving IFS data . Working with backup lists . Parallel save, user exits, and save-while-active . Performing a backup and full system backup . Other backup topics i . Storage locations . Containers . Move management . Media class . Media policies . Media topics . BRMS networking . Scheduling BRMS jobs . Daily maintenance . BRMS reports . Recovery . Tape duplication and label print . Functional usage . Archive . Retrievaltion . TSM Client and BRMS on IBM i . BRMS Enterprise . Summary .

Duration 1 Days 6 CPD hours Apple?s Keynote is the equivalent of Microsoft?s PowerPoint. With it?s powerful set of tools and effects, Keynote makes it easy to create stunning presentations. In this one-day class you will learn how to design and customize slides, add media and music, animate text and images, record voice over narration and the best tips and tricks for presenting the final presentation. Course covers working with a Mac, iPhone and/or iPad and demonstrates how to collaborate in real time with other users Creating a Presentation Opening Keynote Choosing a Theme and Slide Size Selecting a Master Slide Outlining a Presentation Using the Inspector Working with the Format Bar Pasting Text into an Outline Formatting Text Customizing a Slide Layout Copying Styles Between Slides Fixing Spelling Errors Working in Outline View Reordering Slides Creating Object Effects Dragging Files to Create New Slides Using the Light Table Creating a Custom Theme Creating an Empty Theme Creating Backgrounds and Formatting Text Creating a Title Slide Creating a Master Slide Saving and Sharing Themes Applying a Custom Theme Dragging Files to Create New Slides Using the Light Table Working with Tables and Charts Tables and Charts Working with Tables and Charts Chart and Table options Understanding Axis and Series 2D and 3D Charts Animating Tables and Charts Adding content from Microsoft Office or PDF Files Adding Media to Your Presentation Adding Photos and Graphics Enhancing Photos in Keynote Customizing Photo or Graphic Layouts Making Part of a Photo or Graphic Transparent Masking Photos and Shapes Instant Alpha Adding Hyperlinks and Navigation Adding a Chart or Table Adding Audio or Soundtrack Adding a Global Transition Adding Video and Animation Creating Builds to Reveal Text Creating a Sequence Build to Reveal a Table Creating a Smart Build Creating Custom Animation Animating Charts Animating Your Presentation Previewing the Presentation 2D and 3D Transitions Between Slides Creating Object Effects Running and Pausing your Presentation Animating a Title Slide Adding HyperLinks to your Presentation Using Magic Move Recording a Narrated, Self Playing Presentation Rehearsing and Delivering Your Presentation Reviewing your Presentation Adding Comments to your Presentation Adding and Printing Presenter Notes Rehearsing your Presentation Creating a Self-running Slideshow Troubleshooting your Presentation Indexing with Spotlight Importing from PowerPoint Animating a Title Slide Cleaning Up a Presentation Enhancing a Presentation Using an iOS Device as a Remote Control - Sharing Your Presentation Printing handouts Export for Email Exporting to PDFs Exporting to PowerPoint Exporting to Quicktime Sending to YouTube or the web Exporting Export For Email, PDFs Uploading to iCloud or Moving between Computer and iCloud Exporting to PowerPoint Exporting to QuickTime Sending to YouTube Troubleshooting & Cleaning Up Your PresentationTips and Tricks Working with Keynote on an iOS mobile device Additional course details: Nexus Humans Apple Keynote 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 Apple Keynote 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 Project Team Members Consultants Overview This course will prepare you to: Configure selected application areas of Compliance Management, Customs Management and Risk Management. This course covers selected application areas of Compliance Management, Customs Management and Risk Management. Course Outline Communication between SAP ERP and SAP Global Trade Services Basic mapping settings Definition and activation of legal regulations Configuration of legal control Configuration of customs processing Configuration of preference determination and vendor declaration management Additional course details: Nexus Humans GTS200 Configuring SAP Global Trade Services 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 GTS200 Configuring SAP Global Trade Services 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 Operators, administrators, and architects responsible for the creation, maintenance, or delivery of remote and virtual desktop services. Overview By the end of the course, you should be able to meet the following objectives: Recognize the features and benefits of Horizon Use VMware vSphere to create VMs to be used as desktops for Horizon Create and optimize Windows VMs to create Horizon desktops Install and configure Horizon Agent on Horizon desktop Configure and manage the VMware Horizon Client™ systems and connect the client to a VMware Horizon desktop Configure, manage, and entitle desktop pools of full VMs Configure, manage, and entitle pools of instant-clone desktops Create and use Remote Desktop Services (RDS) desktops and application pools Monitor the Horizon environment using Horizon Console Dashboard and Horizon Help Desk Tool Implement a structured approach to troubleshooting Resolve common issues that occur in a Horizon environment Troubleshoot issues with linked and instant clones Configure the Windows client Identify the correct log level for gathering logs Optimize protocols for the best end-user experience VMware Horizon© 8: Virtual Desktop Bootcamp is a five-day combination course of VMware Horizon 8: Skills for Virtual Desktop Management and VMware Horizon 8: Virtual Desktop Troubleshooting. This training combination gives you the skills to deliver virtual desktops and applications through a single virtual desktop infrastructure platform. You build skills in configuring and managing VMware Horizon 8 through a combination of lecture and hands-on labs. You learn how to configure and deploy pools of virtual machines and how to provide a customized desktop environment to end-users. Additionally, you learn how to resolve common issues that occur in a VMware Horizon environment. You engage in a series of lab exercises to bring existing environment issues to resolution. The exercises mirror real-world troubleshooting use cases. These exercises equip learners with the knowledge and practical skills to manage typical challenges faced by virtual desktop administrators and operators. Course Introduction Introductions and course logistics Course objectives Introduction to VMware Horizon Recognize the features and benefits of VMware Horizon Describe the conceptual and logical architecture of VMware Horizon Introduction to Use Case Define a use case for your virtual desktop and application infrastructure Convert customer requirements to use-case attributes vSphere for Horizon 8 Explain basic virtualization concepts Use VMware vSphere© Client? to access your vCenter Server system and VMware ESXi? hosts Create, provision, and remove a virtual machine VMware Horizon Desktops Create a Windows and a Linux virtual machine using vSphere Optimize and prepare Windows and Linux virtual machines to set up VMware Horizon desktop VMs VMware Horizon Agents Outline the configuration choices when installing Horizon Agent on Windows and Linux virtual machines Create a gold master for Windows Horizon desktops VMware Horizon Pools Identify the steps to set up a template for desktop pool deployment List the steps to add desktops to the VMware Horizon© Connection Server? inventory Compare dedicated-assignment and floatingassignment pools Outline the steps to create an automated pool Define user entitlement Explain the hierarchy of global, pool-level, and userlevel policies VMware Horizon Client Options Describe the different clients and their benefits Access Horizon desktop using various Horizon clients and HTML Configure integrated printing, USB redirection, and the shared folders option Configure session collaboration and media optimization for Microsoft Teams Creating and Managing Instant-Clone Desktop Pools List the advantages of instant clones Explain the provisioning technology used for instant-clone desktop pools Set up an automated pool of instant clones Push updated images to instant-clone desktop pools Creating RDS Desktop and Application Pools Explain the difference between an RDS desktop pool and an automated pool Compare and contrast an RDS session host pool, a farm, and an application pool Create an RDS desktop pool and an application ool Access RDS desktops and application from Horizon Client Use the instant clone technology to automate the build-out of RDSH farms Configure load-balancing for RDSHs on a farm Monitoring VMware Horizon Monitor the status of the VMware Horizon components using the Horizon Administrator console dashboard Monitor desktop sessions using the HelpDesk tool Overview of Virtual Desktop Troubleshooting Structured approach to troubleshooting configuration and operational problems Applying troubleshooting methods

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) 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 Hands-on Predicitive Analytics with Python (TTPS4879) 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.