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This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

Learn how create and structure enterprise projects and programmes. Course overview Duration: 2 days (13 hours) Our P6 Project Planning and Controls Fundamentals course is an intensive two day course aimed at experienced planners and project controllers who need to use Primavera to create and manage detailed plans. It includes creating EPS levels, projects, WBS levels and detailed activity and resource planning. Experience of project planning and scheduling techniques is essential. Objectives  By the end of the course you will be able to: Create a programme structure Create projects and set project properties Create programme milestones Create a Work Breakdown Structure (WBS) Create detailed plans including activities, links and resources Progress the schedule Manage actuals Customise layouts Use the reporting tools in Primavera Content Programme Management Creating EPS elements Defining the programme structure Navigating the EPS structure Finding programmes Project Management and WBS Creating projects Setting project properties Validating projects Assigning project codes Building a work breakdown structure Creating a WBS structure Creating WBS elements Work package management Top Down budgets Allocating top down budgets Budget change Programming milestones and activity planning Creating programme milestones Setting constraints Linking milestones Scheduling Using the schedule function Detailed activity planning Creating activities Relationship types Creating relationships Adding milestones Assigning activity codes Resourcing, workloads and baselining Resource types Creating resources Resource attributes Assigning resources Switching resources Split load resource assignment Reduced hours resource assignment Checking workload Reviewing workload Dealing with resource conflicts Assignments view Baselining Creating baselines Assigning baselines Working with layouts Creating layouts Customising columns Setting filters Sorting and grouping Changing the timescale Customising the Gantt Creating activity code breakdown structures Progressing the schedules Updating task status and remaining duration Setting the data date Monitoring and reporting Exporting and importing information Primavera standard reports Creating custom reports Creating portfolios Printing Printing your schedule Printing to other packages

4-Hour Discovery Day - NLP Training Near Me | Ely Wellbeing Neuro Linguistic Programming (NLP) is a collection of models and techniques that provide insights into human psychological processes. Through its various models, strategies and tools, NLP helps people to change their lives by taking control of their thoughts, feelings and behaviours. Our 4 Hour Discovery Day gives you an opportunity to learn the basics of Neuro Linguistic Programming; how it

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Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Duration 5 Days 30 CPD hours This course is intended for Data center administrators Data center engineers Systems engineers Server administrators Network managers Cisco integrators and partners Data center designers Technical solutions architects Network architects Overview After taking this course, you should be able to: Describe the foundations of data center networking Describe Cisco Nexus products and explain the basic Cisco NX-OS functionalities and tools Describe Layer 3 first-hop redundancy Describe Cisco FEX connectivity Describe Ethernet port channels and vPCs Introduce switch virtualization, machine virtualization, and describe network virtualization Compare storage connectivity options in the data center Describe Fibre Channel communication between the initiator server and the target storage Describe Fibre Channel zone types and their uses Describe NPV and NPIV Describe data center Ethernet enhancements that provide a lossless fabric Describe FCoE Describe data center server connectivity Describe Cisco UCS Manager Describe the purpose and advantages of APIs Describe Cisco ACI Describe the basic concepts of cloud computing The Understanding Cisco Data Center Foundations (DCFNDU) v1.1 course helps you prepare for entry-level data center roles. In this course, you will learn the foundational knowledge and skills you need to configure Cisco© data center technologies including networking, virtualization, storage area networking, and unified computing. You will get an introduction to Cisco Application Centric Infrastructure (Cisco ACI), automation and cloud computing. You will get hands-on experience with configuring features on Cisco Nexus Operating System (Cisco NX-OS) and Cisco Unified Computing System (Cisco UCS). This course does not lead directly to a certification exam, but it does cover foundational knowledge that can help you prepare for several CCNP and other professional-level data center courses and exams. Describing the Data Center Network Architectures Cisco Data Center Architecture Overview Three-Tier Network: Core, Aggregation, and Access Spine-and-Leaf Network Two-Tier Storage Network Describing the Cisco Nexus Family and Cisco NX-OS Software Cisco Nexus Data Center Product Overview Cisco NX-OS Software Architecture Cisco NX-OS Software CLI Tools Cisco NX-OS Virtual Routing and Forwarding Describing Layer 3 First-Hop Redundancy Default Gateway Redundancy Hot Standby Router Protocol Virtual Router Redundancy Protocol Gateway Load Balancing Protocol Describing Cisco FEX Server Deployment Models Cisco FEX Technology Cisco FEX Traffic Forwarding Cisco Adapter FEX Describing Port Channels and vPCs Ethernet Port Channels Virtual Port Channels Supported vPC Topologies Describing Switch Virtualization Cisco Nexus Switch Basic Components Virtual Routing and Forwarding Cisco Nexus 7000 VDCs VDC Types VDC Resource Allocation VDC Management Describing Machine Virtualization Virtual Machines Hypervisor VM Manager Describing Network Virtualization Overlay Network Protocols VXLAN Overlay VXLAN BGP EVPN Control Plane VXLAN Data Plane Cisco Nexus 1000VE Series Virtual Switch VMware vSphere Virtual Switches Introducing Basic Data Center Storage Concepts Storage Connectivity Options in the Data Center Fibre Channel Storage Networking VSAN Configuration and Verification Describing Fibre Channel Communication Between the Initiator Server and the Target Storage Fibre Channel Layered Model FLOGI Process Fibre Channel Flow Control Describing Fibre Channel Zone Types and Their Uses Fibre Channel Zoning Zoning Configuration Zoning Management Describing Cisco NPV Mode and NPIV Cisco NPV Mode NPIV Mode Describing Data Center Ethernet Enhancements IEEE Data Center Bridging Priority Flow Control Enhanced Transmission Selection DCBX Protocol Congestion Notification Describing FCoE Cisco Unified Fabric FCoE Architecture FCoE Initialization Protocol FCoE Adapters Describing Cisco UCS Components Physical Cisco UCS Components Cisco Fabric Interconnect Product Overview Cisco IOM Product Overview Cisco UCS Mini Cisco IMC Supervisor Cisco Intersight Describing Cisco UCS Manager Cisco UCS Manager Overview Identity and Resource Pools for Hardware Abstraction Service Profiles and Service Profile Templates Cisco UCS Central Overview Cisco HyperFlex Overview Using APIs Common Programmability Protocols and Methods How to Choose Models and Processes Describing Cisco ACI Cisco ACI Overview Multitier Applications in Cisco ACI Cisco ACI Features VXLAN in Cisco ACI Unicast Traffic in Cisco ACI Multicast Traffic in Cisco ACI Cisco ACI Programmability Common Programming Tools and Orchestration Options Describing Cloud Computing Cloud Computing Overview Cloud Deployment Models Cloud Computing Services Lab outline Explore the Cisco NX-OS CLI Explore Topology Discovery Configure HSRP Configure vPCs Configure VRF Explore the VDC Elements Install ESXi and vCenter Configure VSANs Validate FLOGI and FCNS Configure Zoning Configure Unified Ports on a Cisco Nexus Switch and Implement FCoE Explore the Cisco UCS Server Environment Configure a Cisco UCS Service Profile Configure Cisco NX-OS with APIs Explore the Cisco UCS Manager XML API Management Information Tree Explore Cisco ACI

Become a vulnerability assessment professional with the Nessus scanner for networks and learn to analyze and rank vulnerabilities, both manually and through automation. Explore vulnerability scanning with Metasploit and write custom professional reports. Learn to import results of Nmap in Nessus and create VA Project Worksheets to analyze vulnerability assessments.

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Basic Arduino Crash Course Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Basic Arduino Crash Course Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Basic Arduino Crash Course Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Basic Arduino Crash Course Course, like every one of Study Hub's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Basic Arduino Crash Course? Lifetime access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD QS-accredited qualifications after course completion Receive one-to-one assistance 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 Basic Arduino Crash Course 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 free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Basic Arduino Crash Course course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skills. Prerequisites This Basic Arduino Crash Course does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Basic Arduino Crash Course was made by professionals and it is compatible with all PCs, Macs, 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 As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Basic Arduino Crash Course is a great way for you to gain multiple skills from the comfort of your home. Section 1: Introduction & Requirements Unit 1: Introduction 00:01:00 Unit 2: Instructor's Introduction 00:05:00 Unit 3: What is Arduino 00:02:00 Section 2: Objective to Remember Unit 1: The Holes in Board 00:01:00 Unit 2: Working Procedure 00:01:00 Unit 3: The Breadboard 00:05:00 Section 3: Thinking Process of Arduino Unit 1: Thinking Process of Arduino 00:06:00 Section 4: Making a Circuit Unit 1: Putting Together a Circuit 00:04:00 Section 5: Coding Arduino Unit 1: Cut and Paste Coding 00:12:00 Section 6: More About Circuit Diagram Unit 1: Circuit Diagram 00:03:00 Section 7: Practical Work Unit 1: Inputs: Buttons 00:04:00 Unit 2: Analog Input: IR sensor 00:04:00 Unit 3: Analog Input: Potentiometer 00:09:00 Assignment Assignment - Basic Arduino Crash Course

Register on the Javascript for Data Structures today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Javascript for Data Structures is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Javascript for Data Structures Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Javascript for Data Structures, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Introduction Welcome to the Course 00:03:00 Essential Concepts Essential Concepts 00:02:00 Constructor Function 00:09:00 Protoype 00:04:00 Class 00:04:00 List Data Structure List Data Structure 00:01:00 Creating Class For List Data Structure 00:03:00 Implementing Add Feature 00:06:00 Working On Find And Remove Feature 00:08:00 Creating InsertAfter Feature 00:05:00 Implementing Contains And Clear Feature 00:04:00 Challenge - Work On Traverse List Features 00:03:00 Solution - Implementing List Traverse Features 00:08:00 Challenge - Work On DisplayElementNameOnPostion Features 00:01:00 Solution - Implementing DisplayElementNameOnPostion Features 00:06:00 Stack Data Structure Stack Data Structure 00:03:00 Using Object To Create Stack Class 00:04:00 Implementing Push and Pop Feature 00:09:00 Working with Peek and Clear Feature 00:04:00 Challenge - Extend Stack Class Feature 00:01:00 Solution - Extending Stack Class Feature 00:03:00 Challenge - Convert Stack Class From Object To Array Class 00:01:00 Solution - Converting Stack Class From Object To Array Class 00:05:00 Queue Data Structure Queue Data Structure 00:03:00 Using Object To Create Queue Class 00:04:00 Implementing Enqueue Feature 00:03:00 Implementing Tricky Dequeue Feature 00:09:00 Working On PeeK Size and Clear Features 00:03:00 Extending Features With Two Extra Methods 00:06:00 Challenge Convert Queue Class From Object To Array Class 00:01:00 Solution Converting Queue Class From Object To Array Class 00:04:00 Set Data Structure Set Data Structure 00:02:00 Creating Set Class 00:03:00 Implementing Add And Remove Feature 00:09:00 Working On Contains, Show And Size Method 00:05:00 Creating Unique Set 00:09:00 Adding Mutual Members Feature 00:04:00 Challenge Implement Difference Set Feature 00:02:00 Solution Implementing Difference Set Feature 00:03:00 Final Thought Final Thought 00:01:00 Resources Resources - Javascript for Data Structures 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.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this