2981 Software Development courses in Sheffield delivered Online

Duration 2 Days 12 CPD hours This course is intended for This class is primarily intended for the following participants: Technical employees using GCP, including customer companies, partners and system integrators deployment engineers, cloud architects, cloud administrators, system engineers , and SysOps/DevOps engineers. Individuals using GCP to create, integrate, or modernize solutions using secure, scalable microservices architectures in hybrid environments. Overview Connect and manage Anthos GKE clusters from GCP Console whether clusters are part of Anthos on Google Cloud or Anthos deployed on VMware. Understand how service mesh proxies are installed, configured and managed. Configure centralized logging, monitoring, tracing, and service visualizations wherever the Anthos GKE clusters are hosted. Understand and configure fine-grained traffic management. Use service mesh security features for service-service authentication, user authentication, and policy-based service authorization. Install a multi-service application spanning multiple clusters in a hybrid environment. Understand how services communicate across clusters. Migrate services between clusters. Install Anthos Config Management, use it to enforce policies, and explain how it can be used across multiple clusters. This two-day instructor-led course prepares students to modernize, manage, and observe their applications using Kubernetes whether the application is deployed on-premises or on Google Cloud Platform (GCP). Through presentations, and hands-on labs, participants explore and deploy using Kubernetes Engine (GKE), GKE Connect, Istio service mesh and Anthos Config Management capabilities that enable operators to work with modern applications even when split among multiple clusters hosted by multiple providers, or on-premises. Anthos Overview Describe challenges of hybrid cloud Discuss modern solutions Describe the Anthos Technology Stack Managing Hybrid Clusters using Kubernetes Engine Understand Anthos GKE hybrid environments, with Admin and User clusters Register and authenticate remote Anthos GKE clusters in GKE Hub View and manage registered clusters, in cloud and on-premises, using GKE Hub View workloads in all clusters from GKE Hub Lab: Managing Hybrid Clusters using Kubernetes Engine Introduction to Service Mesh Understand service mesh, and problems it solves Understand Istio architecture and components Explain Istio on GKE add on and it's lifecycle, vs OSS Istio Understand request network traffic flow in a service mesh Create a GKE cluster, with a service mesh Configure a multi-service application with service mesh Enable external access using an ingress gateway Explain the multi-service example applications: Hipster Shop, and Bookinfo Lab: Installing Open Source Istio on Kubernetes Engine Lab: Installing the Istio on GKE Add-On with Kubernetes Engine Observing Services using Service Mesh Adapters Understand service mesh flexible adapter model Understand service mesh telemetry processing Explain Stackdriver configurations for logging and monitoring Compare telemetry defaults for cloud and on-premises environments Configure and view custom metrics using service mesh View cluster and service metrics with pre-configured dashboards Trace microservice calls with timing data using service mesh adapters Visualize and discover service attributes with service mesh Lab: Telemetry and Observability with Istio Managing Traffic Routing with Service Mesh Understand the service mesh abstract model for traffic management Understand service mesh service discovery and load balancing Review and compare traffic management use cases and configurations Understand ingress configuration using service mesh Visualize traffic routing with live generated requests Configure a service mesh gateway to allow access to services from outside the mesh Apply virtual services and destination rules for version-specific routing Route traffic based on application-layer configuration Shift traffic from one service version to another, with fine-grained control, like a canary deployment Lab: Managing Traffic Routing with Istio and Envoy Managing Policies and Security with Service Mesh Understand authentication and authorization in service mesh Explain mTLS flow for service to service communication Adopt mutual TLS authentication across the service mesh incrementally Enable end-user authentication for the frontend service Use service mesh access control policies to secure access to the frontend service Lab: Managing Policies and Security with Service Mesh Managing Policies using Anthos Config Management Understand the challenge of managing resources across multiple clusters Understand how a Git repository is as a configuration source of truth Explain the Anthos Config Management components, and object lifecycle Install and configure Anthos Config Management, operators, tools, and related Git repository Verify cluster configuration compliance and drift management Update workload configuration using repo changes Lab: Managing Policies in Kubernetes Engine using Anthos Config Configuring Anthos GKE for Multi-Cluster Operation Understand how multiple clusters work together using DNS, root CA, and service discovery Explain service mesh control-plane architectures for multi-cluster Configure a multi-service application using service mesh across multiple clusters with multiple control-planes Configure a multi-service application using service mesh across multiple clusters with a shared control-plane Configure service naming/discovery between clusters Review ServiceEntries for cross-cluster service discovery Migrate workload from a remote cluster to an Anthos GKE cluster Lab: Configuring GKE for Multi-Cluster Operation with Istio Lab: Configuring GKE for Shared Control Plane Multi-Cluster Operation

Duration 5 Days 30 CPD hours This course is intended for Audience for this course This course is designed for system administrators responsible for creating OpenShift Enterprise instances, deploying applications, creating process customizations, managing instances and projects. Prerequisites for this course Have taken Red Hat Enterprise Linux Administration I and II (RH124 and RH134), or equivalent Red Hat Enterprise Linux© system administration experience Be certified as a Red Hat Certified System Administrator (RHCSA), or equivalent Red Hat Enterprise Linux system administration experience Be certified as a Red Hat Certified Engineer (RHCE©) Overview Learn to install, configure, and manage OpenShift Enterprise by Red Hat instances - OpenShift Enterprise Administration (DO280) prepares the system administrator to install, configure, and manage OpenShift Enterprise by Red Hat© instances. OpenShift Enterprise, Red Hat's platform-as-a-service (PaaS) offering, provides pre-defined deployment environments for applications of all types through its use of container technology. This creates an environment that supports DevOps principles such as reduced time to market and continuous delivery. - In this course, students will learn how to install and configure an instance of OpenShift Enterprise, test the instance by deploying a real world application, and manage projects/applications through hands-on labs. - Course content summary - Container concepts - Configuring resources with the command line interface - Building a pod - Enabling services for a pod - Creating routes - Downloading and configuring images - Rolling back and activating deployments - Creating custom S2I images This course will empower you to install and administer the Red Hat© OpenShift© Container Platform, with hands-on, lab-based materials that show you how to install, configure, and manage OpenShift clusters and deploy sample applications to further understand how developers will use the platform. This course is based on Red Hat© Enterprise Linux© 7.5 and Openshift Container Platform 3.9. OpenShift is a containerized application platform that allows your enterprise to manage container deployments and scale your applications using Kubernetes. OpenShift provides predefined application environments and builds upon Kubernetes to provide support for DevOps principles such as reduced time to market, infrastructure-as-code, continuous integration (CI), and continuous delivery (CD). 1 - INTRODUCTION TO RED HAT OPENSHIFT ENTERPRISE Review features and architecture of OpenShift Enterprise. 2 - INSTALL OPENSHIFT ENTERPRISE Install OpenShift Enterprise and configure a master and node. 3 - EXECUTE COMMANDS Execute commands using the command line interface. 4 - BUILD APPLICATIONS Create, build, and deploy applications to an OpenShift Enterprise instance. 5 - PERSISTENT STORAGE Provision persistent storage and use it for the internal registry. 6 - BUILD APPLICATIONS WITH SOURCE-TO-IMAGE (S2I) Create and build applications with S2I and templates. 7 - MANAGE THE SYSTEM Use OpenShift Enterprise components to manage deployed applications. 8 - CUSTOMIZE OPENSHIFT ENTERPRISE Customize resources and processes used by OpenShift Enterprise. 9 - COMPREHENSIVE REVIEW Practice and demonstrate knowledge and skills learned in the course. 10 - NOTE: Course outline is subject to change with technology advances and as the nature of the underlying job evolves. For questions or confirmation on a specific objective or topic, please contact us. Additional course details: Nexus Humans Red Hat OpenShift Administration II: Operating a Production Kubernetes Cluster (DO280) 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 Red Hat OpenShift Administration II: Operating a Production Kubernetes Cluster (DO280) 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.

Overview With the ever-increasing demand for Go Lang in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Go Lang may be. Learning about Go Lang or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Go Lang . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Go Lang is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Go Lang course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Go Lang course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Go Lang course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Go Lang , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Go Lang , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Go Lang , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Go Lang course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.  Course Curriculum Module 1_ Introduction Module 1_ Introduction 00:00 Module 2_ Data Types and Variables Module 2_ Data Types and Variables 00:00 Module 3_ Conditional Statements Module 3_ Conditional Statements 00:00 Module 4_ Iteration Module 4_ Iteration 00:00 Module 5_ Functions Module 5_ Functions 00:00

Overview   With the ever-increasing demand for Android Games Development in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Android Games Development may be.   Learning about Android Games Development or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Android Games Development. That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Android Games Development is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates.   The self-paced online learning methodology by Compete High in this Introduction to Android Games Development course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course!   Instead of searching for hours, enrol right away on this Introduction to Android Games Development course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run.   Who is this course for?   While we refrain from discouraging anyone wanting to do this Introduction to Android Games Development course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Android Games Development, Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Android Games Development, Anyone looking for a certificate of completion on doing an online training on this topic, Students of Android Games Development, or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity   Career Path   This Introduction to Android Games Development course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.    Course Curriculum Module-1 First Steps with the Android SDK First Steps with the Android SDK 00:00 Module-2 Game Development 101 Game Development 101 00:00 Module-3 Android for Game Developers Android for Game Developers 00:00 Module-4 An Android Game Development Framework An Android Game Development Framework 00:00

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Dive into the transformative world of Artificial Intelligence through the course titled 'Foundations of Artificial Intelligence: Building Intelligent Systems.' This comprehensive curriculum sweeps across an array of subjects, from the rudimentary introduction to AI to the intricate nuances of building AI applications. Embrace a holistic understanding of core modules like Machine Learning, Natural Language Processing, and Robotics. The content, framed meticulously, beckons those inquisitive minds eager to craft, innovate, and change the world with AI's limitless possibilities. Deepen your conceptual clarity with two-part modules that delve into Knowledge Representation and Machine Learning, ensuring that learners grasp intricate details without feeling overwhelmed. With sections dedicated to Computer Vision and Deep Learning, individuals will find themselves proficiently navigating the vibrant ecosystems these technologies encompass. Finally, a spotlight on AI applications ensures that learners not only acquire theoretical wisdom but also grasp how AI integrates into real-world scenarios. By the culmination of this course, participants will stand at the forefront of AI innovations, armed with the acumen to shape a future where intelligent systems intertwine seamlessly with our daily lives. This foundation lays the groundwork for boundless exploration in the Artificial Intelligence realm Learning Outcomes Upon completion of this course, participants will be able to: Gain comprehensive insights into the fundamental principles of Artificial Intelligence. Understand the critical mathematical concepts underpinning AI technologies. Develop proficiency in various AI knowledge representation methods. Acquire a solid foundation in Machine Learning, Deep Learning, and Natural Language Processing techniques. Familiarise with the applications and integrations of AI in Robotics and Computer Vision. Why buy this Foundations of Artificial Intelligence: Building Intelligent Systems? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Foundations of Artificial Intelligence: Building Intelligent Systems there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Foundations of Artificial Intelligence: Building Intelligent Systems course for? This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning. Aspiring AI enthusiasts keen on building a robust foundation in the subject. Technologists aiming to pivot into AI-centric roles. Researchers eager to enhance their knowledge spectrum in intelligent systems. University students studying computer science or related disciplines, looking to supplement their academic pursuits. Entrepreneurs eyeing opportunities in AI-driven ventures. Prerequisites This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Foundations of Artificial Intelligence: Building Intelligent Systems was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path AI Research Scientist - Average Salary Range: £60,000 - £85,000 per annum Machine Learning Engineer - Average Salary Range: £55,000 - £80,000 per annum NLP Specialist - Average Salary Range: £50,000 - £75,000 per annum Computer Vision Engineer - Average Salary Range: £52,000 - £77,000 per annum Robotics Engineer - Average Salary Range: £48,000 - £73,000 per annum AI Application Developer - Average Salary Range: £54,000 - £79,000 per annum Course Curriculum Module 01: Introduction to Artificial Intelligence Introduction to Artificial Intelligence 00:21:00 Module 02: Mathematics for AI Mathematics for AI 00:17:00 Module 03: Knowledge Representation in AI - Part 1 Knowledge Representation in AI - Part 1 00:18:00 Module 04: Knowledge Representation in AI - Part 2 Knowledge Representation in AI - Part 2 00:16:00 Module 05: Machine Learning - Part 1 Machine Learning - Part 1 00:16:00 Module 06: Machine Learning - Part 2 Machine Learning - Part 2 00:15:00 Module 07: Deep Learning Deep Learning 00:16:00 Module 08: Natural Language Processing Natural Language Processing 00:22:00 Module 09: Computer Vision Computer Vision 00:14:00 Module 10: Robotics Robotics 00:18:00 Module 11: Building AI Applications Building AI Applications 00:24:00

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.