427 Algorithm courses delivered Online

Embark on a journey into the world of technology with Spark Generation! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.

This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!

Definitive Segment Routing course description This Segment Routing (SR) training course is a comprehensive program designed to equip network professionals with the knowledge and skills needed to implement and manage SR in modern networking environments. Segment Routing is a cutting-edge network architecture that enhances network flexibility, scalability, and efficiency. This course offers in-depth coverage of SR principles, protocols, and practical implementation techniques. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Explain packet paths when implementing SLB. Explain how Segment Routing works. Explain the relationship between SR and MPLS. Use SR for Traffic Engineering. Troubleshoot Segment Routing. Implement TI-LFA using Segment Routing Definitive Segment Routing course details Who will benefit: This course is ideal for network engineers, architects, and administrators who want to stay up-to-date with the latest networking technologies and enhance their expertise in Segment Routing. Prerequisites: Concise MPLS for engineers Duration 3 days Definitive Segment Routing course contents Introduction to Segment Routing (SR) What is SR? Source based routing, SPRING, history, segments, why SR? SR benefits.SR usage: Traffic Engineering, Shortest path, local protection. Relationship between SR and MPLS, SRv6. Hands on Investigating the base network. Segment Routing architecture SR domains, SR paths, SR segments. Segment types. Segment IDs, combining segments, IGP extensions, control plane components. Hands on Configuring SR, exploring how SR works, Segment Routing protocols SR-MPLS. MPLS label stack operations. Segment Routing Global Block (SRGB). SRLB. IS-IS and OSPF extensions for SR. Prefix segments, adjacency segments. SRGB/IGP interactions. Multidomain SR policies. SPF, Strict SPF. Hands on Analysing IGP SR extension operation. Investigating the SRGB. Segment Routing Traffic Engineering RSVP-TE versus SR-TE. SR policies. Anycast and binding SIDs. SR flexible algorithm flex-algo, Performance measurement delay. Hands on Optimising network paths for various applications. SR integration with 'older' technologies MPLS and LDP integration with SR. Hands on Integration. Topology Independent Loop Free Alternative Classic LFA and IP/MPLS protection mechanisms. TI-LFA protection options. Hands on TI-LFA operation with SR and LDP traffic. Scenarios SDN. Managing SR with SR controllers. Analyse, optimise, automate. Network slicing. BGP peering segments Path Computation Elements, BGP Link State. BGP prefix segments, BGP peer segments. Egress peer engineering. SR enabled VPNs. Hands onBGP segment routing. Troubleshooting Segment Routing IP toolkit: ping and traceroute. MPLS toolkit: MPLS ping, MPLS echo request/reply, MPLS ping, MPLS traceroute and path discovery. Router show commands. Hands on Used throughout the course during exercises. SRv6 Note this is an optional extra day. See our one day SRv6 course for details. IPv6 headers review, routing headers, IPv6 segment, SRv6 segment Identifiers. IPv6 Segment Routing Header. SRH procedures. Hands on Configuring SRv6, Analysing SRv6 operation.

Duration 2 Days 12 CPD hours This course is intended for This course benefits individuals responsible for configuring and monitoring devices running the Junos OS. Overview Describe the history and rationale for MPLS, as well as its basic terminology. Explain the MPLS label operations (push, pop, swap) and the concept of label-switched path (LSP). Describe the configuration and verification of MPLS forwarding. Describe the functionalities and operation of RSVP and LDP. Configure and verify RSVP-signaled and LDP-signaled LSPs. Select and configure the appropriate label distribution protocol for a given set of requirements. Describe the default Junos OS MPLS traffic engineering behavior. Explain the Interior Gateway Protocol (IGP) extensions used to build the Traffic Engineering Database (TED). Describe the Constrained Shortest Path First (CSPF) algorithm, its uses, and its path selection process. Describe administrative groups and how they can be used to influence path selection. Describe the default traffic protection behavior of RSVP-signaled LSPs. Explain the use of primary and secondary LSPs. Describe the operation and configuration of fast reroute. Describe the operation and configuration of link and node protection. Describe the operation and configuration of LDP loop-free alternate. Describe the LSP optimization options. Explain LSP priority and preemption. Describe the behavior of fate sharing. Describe how SRLG changes the CSPF algorithm when computing the path of a secondary LSP. Explain how extended admin groups can be used to influence path selection. Explain the purpose of several miscellaneous MPLS features. This two-day course is designed to provide students with a solid foundation on Multiprotocol Label Switching (MPLS). Course Outline Course Introduction MPLS Fundamentals MPLS Foundation Terminology MPLS Configuration MPLS Packet Forwarding Label Distribution Protocols Label Distribution Protocols RSVP LDP Routing Table Integration Mapping Next-Hops to LSPs Route Resolution Example Route Resolution Summary IGP Passive Versus Next-Hop Self for BGP Destinations Constrained Shortest Path First RSVP Behavior Without CSPF CSPF Algorithm CSPF Tie Breaking Administrative Groups Inter-area Traffic Engineered LSPs Traffic Protection and LSP Optimization Default Traffic Protection Behavior Primary and Secondary LSPs Fast Reroute RSVP Link Protection LDP LFA and Link Protection LSP Optimization Fate Sharing Junos OS Fate Sharing SRLG Extended Admin Groups Miscellaneous MPLS Features Forwarding Adjacencies Policy Control over LSP Selection LSP Metrics Automatic Bandwidth Container LSPs TTL Handling Explicit Null Configuration MPLS Pings

In this course, you will learn how to author machine learning models in Python without the aid of frameworks or libraries from scratch. Discover the process of loading data, evaluating models, and implementing machine learning algorithms.

Overview This comprehensive course on Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning with Python comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 21 lectures • 01:34:00 total length •Introduction to types of ML algorithm: 00:02:00 •SVM - Python Implementation: 00:06:00 •Introduction to types of ML algorithm: 00:02:00 •Importing a dataset in python: 00:02:00 •Resolving Missing Values: 00:06:00 •Managing Category Variables: 00:04:00 •Training and Testing Datasets: 00:07:00 •Normalizing Variables: 00:02:00 •Normalizing Variables - Python Code: 00:03:00 •Summary: 00:01:00 •Simple Linear Regression - How it works?: 00:04:00 •Simple Linear Regreesion - Python Implementation: 00:07:00 •Multiple Linear Regression - How it works?: 00:01:00 •Multiple Linear Regression - Python Implementation: 00:09:00 •Decision Trees - How it works?: 00:05:00 •Random Forest - How it works?: 00:03:00 •Decision Trees and Random Forest - Python Implementation: 00:04:00 •kNN - How it works?: 00:02:00 •kNN - Python Implementation: 00:10:00 •Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00 •SVM - How it works?: 00:04:00

The purpose of this course is to teach you how to use Python for machine learning to create real-world algorithms. You will gain an in-depth understanding of the fundamentals of deep learning. This course will help you explore different frameworks in Python to solve real-world problems using the core concepts of deep learning and artificial intelligence.

Covering ARM systems design and architecture and practical assembly programming, this is a comprehensive ARM assembly video course to get you up and running. You'll develop the skills necessary for starting your career as an ARM embedded developer, such as developing algorithms and creating state machines in assembly.

Computer vision (CV), a subfield of computer science, focuses on replicating the complex functionalities of the human visual system. This course provides a comprehensive understanding of Computer Vision from the beginning using Python and helps you in becoming an expert.