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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.
Duration 2 Days 12 CPD hours This course is intended for Experienced VMware vSphere administrators Overview By the end of the course, you should be able to meet the following objectives: Explain the key features and use cases for vSAN Detail the underlying vSAN architecture and components Describe the different vSAN deployment options Detail vSAN cluster requirements and considerations Apply recommended vSAN design considerations and capacity sizing practices Determine and plan for storage consumption by data growth and failure tolerance Design vSAN hosts for operational needs Explain Maintenance Mode use and its impacts on vSAN Apply best practices for vSAN network configurations Manually configure a vSAN cluster using VMware vSphere Client⢠Explain and configure vSAN fault domains Understand and apply vSAN storage policies Define encryption in the vSAN cluster Describe the architecture and use cases for stretched clusters Describe the architecture and use cases for two-node clusters Understand the steps involved in creating the vSAN iSCSI target services This two-day, hands-on training course provides you with the knowledge, skills, and tools to plan and deploy a VMware vSAN? cluster. In this course, you are taught the many considerations that the end vSAN configuration has on the initial planning of the vSAN datastore. You also perform a fully manual configuration of a vSAN cluster. Course Introduction Introductions and course logistics Course objectives Introduction to vSAN Describe vSAN architecture Identify vSAN objects and components Describe the advantages of object-based storage Describe the difference between All-Flash and Hybrid vSAN architecture Explain the key features and use cases for vSAN Discuss the vSAN integration and compatibility with other VMware technologies Planning a vSAN Cluster Identify requirements and planning considerations for vSAN clusters Apply vSAN cluster planning and deployment best practices Determine and plan for storage consumption by data growth and failure tolerance Design vSAN hosts for operational needs Identify vSAN networking features and requirements Describe ways of controlling traffic in a vSAN environment Recognize best practices for vSAN network configurations Deploying a vSAN Cluster Deploy and configure a vSAN cluster using the Cluster Quickstart wizard Manually configure a vSAN cluster using vSphere Client Explain and configure vSAN fault domains Using VMware vSphere© High Availability with vSAN Understand vSAN cluster maintenance capabilities Describe the difference between implicit and explicit fault domains Create explicit fault domains vSAN Storage Policies Describe a vSAN object Describe how objects are split into components Explain the purpose of witness components Explain how vSAN stores large objects View object and component placement on the vSAN datastore Explain how storage policies work with vSAN Define and create a virtual machine storage policy Apply and modify virtual machine storage policies Change virtual machine storage policies dynamically Identify virtual machine storage policy compliance status Introduction to Advanced vSAN Configurations Define and configure compression and deduplication in the vSAN cluster Define and configure encryption in the vSAN cluster Understand the remote vSAN datastore topology Identify the operations involved in managing the remote vSAN datastore Understand the steps involved in creating the vSAN iSCSI target service vSAN Stretched and Two-Node Clusters Describe the architecture and use cases for stretched clusters Detail the deployment and replacement of a vSAN witness node Describe the architecture and uses case for two-node clusters Explain the benefits of vSphere HA and vSphere Site Recovery Manager in a vSAN stretched cluster Explain storage policies for vSAN stretched cluster Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSAN: Plan and Deploy [v7] 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 vSAN: Plan and Deploy [v7] 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.