31 Algorithms courses in London

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds

UMTS training course description An in-depth study of the UMTS technologies and network structure. What will you learn Explain what 3G and UMTS are. Describe the migration path to UMTS. Describe the UMTS architecture. UMTS training course details Who will benefit: Anyone who needs to know more about UMTS. Prerequisites: Total GSM Duration 3 days UMTS training course contents Introduction 3G WCDMA 2G WCDMA comparison. European and international spectrum allocations. UMTS Services UMTS QoS classes, Conversational, Streaming, Interactive and Background. UMTS bearer services. Radio Access Network (RAN) Architecture System architecture. The Radio Network Controller (RNC) and Node B functionality. Protocol model. The Iu interface for Circuit and Packet switching. The Iur interface and RNSAP. RNC node B interface and NBAP. The Physical layer Spread spectrum coding and modulation. Logical and physical channels. User data rates and transmission. Power control. Signalling, synchronisation, common control, access and indicator channels. Procedures for transmit diversity, measurement, power control and handover. Radio Resource Management Fast and outer loop power control. Transmit power and power rise. Handover algorithms. Intra frequency and inter system handovers. Load, measurement on the air interface. Admission and load control. Packet Access Packet data traffic. Packet data transport channels. Packet scheduling algorithms. Handover, load and administration control. Packet data performance. UTRA TDD Mode Time Division Duplex (TDD). UTRA TDD modulation and spreading, transport channels, physical channels and their structure. Noise and interference limited network. Interference, FDD and TDD co-existence.

IPsec training course description This hands on course focuses on IPsec VPNs. Rather than focusing on one implementation this course concentrates on the technologies and protocols of IPsec. Starting with an overview of the complete IPsec architecture the course then moves onto ESP packet analysis along with encryption and authentication provided. IKEv1 and IKEv2 are both covered in detail. Having covered IPsec with pre shared keys the course then moves onto IPsec with certificates followed by IPsec issues. The course is vendor neutral with hands on with both Cisco and Microsoft implementations. What will you learn Explain how IPsec works. Explain the role of AH, ESP and IKE. Configure IPsec. Troubleshoot IPsec. IPsec training course details Who will benefit: Technical staff working with IPsec. Prerequisites: Definitive IP VPNs for engineers. Duration 3 days IPsec training course contents What is IPsec? How to spell IPsec, IPsec is IP security, confidentiality, integrity, authenticity, replay protection, what is a VPN? Network layer security, IPsec and IPv4, IPsec and IPv6, the suite of protocols, the standard, IPsec RFCs, IPsec history. Hands on Analysis of 'normal' IP packets. IPsec architecture The IPsec protocols, AH vs ESP, Why two headers? transport mode, tunnel mode, Remote access VPNs, site to site VPNs, security associations, SA database, Security Parameters Index, implementations: Host tack, Bump in the Stack, Bump in the Wire. Hands on Configuring IPsec. AH What AH does, the stack, The AH header, What is authenticated? Device authentication. AH in transport mode, AH in tunnel mode. Hands on AH packet analysis. ESP What ESP does, the ESP header, ESP in transport mode, ESP in tunnel mode, ESP and SA, ESP and SPI. Hands on ESP packet analysis, policy configuration. IPsec encryption IPsec is a framework, standard algorithms, ESP keys, the role of IKE, key lifetimes, how IKE generates the keys, DES, 3DES, AES, cipher block chaining, counter mode, other encryption. Hands on Encryption configuration. IPsec authentication Authentication types, IPsec authentication, Authentication algorithms: MD5, keyed SHA-1, HMAC-MD5, HMAC-SHA-1, HMAC-RIPEMD, other authentication algorithms. Hands on Authentication configuration. IKE Internet Key Exchange, IKE and the SAD, the two phase negotiation, ISAKMP, ISAKMP header, pre shared keys, digital signatures, public key encryption, Diffie Hellman, proposals, counter proposals, nonces, identities, phase 1 negotiation: main mode, aggressive mode, base mode. Phase 2 negotiation: quick mode, new group mode. Hands on IKE packet analysis. More IKE PFS, IKE and dynamic addresses, XAUTH, hybrid authentication, CRACK, ULA, PIC. User level authentication. IKE renegotiation, heartbeats. Hands on Troubleshooting IPsec. IKEv2 The IKEv2 exchange, IKE_SA_INIT, IKE_AUTH, CREATE_CHILD_SA, IKEv2 packets, the informational exchange. Comparing IKev1 vs IKE v2. Hands on IKEv2 configuration and analysis. PKI What is PKI?, Digital certificates, Certificate authorities, CA servers, RA, VA, certificates, CA hierarchy, CRLs, certificate formats. Hands on installing and configuring certificate servers. IPsec issues NAT, IPsec overhead and fragmentation. Summary IPsec strengths and weaknesses. Where to get further information.

Cyber security training course description This cyber security course focusses on the network side of security. Technologies rather than specific products are studied focussing around the protection of networks using firewalls and VPNs. What will you learn Describe: - Basic security attacks - RADIUS - SSL - VPNs Deploy firewalls and secure networks Explain how the various technologies involved in an IP VPN work. Describe and implement: - L2TP - IPsec - SSL - MPLS, L3, VPNs. Cyber security training course details Who will benefit: Anyone working in the security field. Prerequisites: TCP/IP foundation for engineers Duration 5 days Cyber security training course contents Security review Denial of service, DDOS, data manipulation, data theft, data destruction, security checklists, incident response. Security exploits IP spoofing, SYN attacks, hijacking, reflectors and amplification, keeping up to date with new threats. Hands on port scanning, use a 'hacking' tool. Client and Server security Windows, Linux, Log files, syslogd, accounts, data security. Hands on Server hardening. Firewall introduction What is a firewall? Firewall benefits, concepts. HAnds on launching various attacks on a target. Firewall types Packet filtering, SPI, Proxy, Personal. Software firewalls, hardware firewalls. Firewall products. Hands on Simple personal firewall configuration. Packet filtering firewalls Things to filter in the IP header, stateless vs. stateful filtering. ACLs. Advantages of packet filtering. Hands on Configuring packet filtering firewalls. Stateful packet filtering Stateful algorithms, packet-by-packet inspection, application content filtering, tracks, special handling (fragments, IP options), sessions with TCP and UDP. Firewall hacking detection: SYN attacks, SSL, SSH interception. Hands on SPI firewalls. Proxy firewalls Circuit level, application level, SOCKS. Proxy firewall plusses and minuses. Hands on Proxy firewalls. Firewall architectures Small office, enterprise, service provider, what is a DMZ? DMZ architectures, bastion hosts, multi DMZ. Virtual firewalls, transparent firewalls. Dual firewall design, high availability, load balancing, VRRP. Hands on Resilient firewall architecture. Testing firewalls Configuration checklist, testing procedure, monitoring firewalls, logging, syslog. Hands on Testing firewalls. Encryption Encryption keys, Encryption strengths, Secret key vs Public key, algorithms, systems, SSL, SSH, Public Key Infrastructures. Hands on Password cracking. Authentication Types of authentication, Securid, Biometrics, PGP, Digital certificates, X.509 v3, Certificate authorities, CRLs, RADIUS. Hands on Using certificates. VPN overview What is a VPN? What is an IP VPN? VPNs vs. Private Data Networks, Internet VPNs, Intranet VPNs, Remote access VPNs, Site to site VPNs, VPN benefits and disadvantages. VPN Tunnelling VPN components, VPN tunnels, tunnel sources, tunnel end points, tunnelling topologies, tunnelling protocols, which tunnelling protocol? Requirements of tunnels. L2TP Overview, components, how it works, security, packet authentication, L2TP/IPsec, L2TP/PPP, L2 vs L3 tunnelling. Hands on Implementing a L2TP tunnel. IPsec AH, HMAC, ESP, transport and tunnel modes, Security Association, encryption and authentication algorithms, manual vs automated key exchange, NAT and other issues. Hands on Implementing an IPsec VPN. SSL VPNs Layer 4 VPNs, advantages, disadvantages. SSL. TLS. TLS negotiation, TLS authentication. TLS and certificates. Hands on Implementing a SSL VPN. MPLS VPNs Introduction to MPLS, why use MPLS, Headers, architecture, label switching, LDP, MPLS VPNs, L2 versus L3 VPNs. Point to point versus multipoint MPLS VPNs. MBGP and VRFs and their use in MPLS VPNs. Hands on Implementing a MPLS L3 VPN. Penetration testing Hacking webservers, web applications, Wireless networks and mobile platforms. Concepts, threats, methodology. Hands on Hacking tools and countermeasures.

Advanced C++ training course description The course will give a broad overview of the C++ Programming language, focusing on modern C++, up to C++17. This course will cover the use of the Standard Library, including containers, iterator, function objects and algorithms. From the perspective of application development, a number of design patterns will be considered. What will you learn Write C++ programs using the more esoteric language features. Utilise OO techniques to design C++ programs. Use the standard C++ library. Exploit advanced C++ techniques Advanced C++ training course details Who will benefit: Programmers needing to write C++ code. Programmers needing to maintain C++ code. Prerequisites: C++ programming foundation. Duration 5 days Advanced C++ training course contents Study of a string class Create a string class as a means to investigate many issues, involving the use of operator overloading and including overloading new and delete. Creation of the class will also require consideration of 'const correctness'. Exception handling Consider the issues involved in exception handling including the concept of exception safety. Templates Review definition of template functions, including template parameter type deduction. Introduction to template metaprogramming. Newer features including template template parameters and variadic templates. Creation of template classes. Design patterns Introduction to Design Patterns and consideration of a number of patterns, such as, factory method, builder, singleton and adapter. The standard C++ library (STL) Standard Library features, such as, Containers, Iterator, Function Objects and Algorithms. Introduction to Lambda expressions. C++ and performance The writing of code throughout the course will be oriented towards performant code, including use of R Value references and 'move' semantics. Pointers The use of pointers will be considered throughout the course. Smart pointers will be considered to improve program safety and help avoid the use of 'raw' pointers. Threading This section will consider the creation of threads and synchronisation issues. A number of synchronisation primitives will be considered. Async and the use of Atomic will also be considered. New ANSI C++ features Summarising some of the newer features to be considered are: Auto, Lambdas expression, smart pointers, variadic templates and folds, R Value references and tuple together with structured binding.

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Software development training course description This three-day MTA Training course helps you prepare for Microsoft Technology Associate Exam 98-361, and build an understanding of these topics: Core programming, Object-Oriented programming, general software development, web applications, desktop applications, and databases. This course leverages the same content as found in the Microsoft Official Academic Course (MOAC) for this exam. What will you learn Describe core programming. Explain Object Oriented programming. Describe general software development. Describe Web applications. Describe desktop applications. Explain how databases work. Software development training course details Who will benefit: Anyone looking to learn the fundamentals of software. Prerequisites: None. Duration 3 days Software development training course contents Core programming Computer storage and data types How a computer stores programs and the instructions in computer memory, memory stacks and heaps, memory size requirements for the various data storage types, numeric data and textual data. Computer decision structures Various decision structures used in all computer programming languages; If decision structures; multiple decision structures, such as If…Else and switch/Select Case; reading flowcharts; decision tables; evaluating expressions. Handling repetition For loops, While loops, Do...While loops and recursion. Understand error handling Structured exception handling. Object-oriented programming Classes Properties, methods, events and constructors; how to create a class; how to use classes in code. Inheritance Inheriting the functionality of a base class into a derived class. Polymorphism Extending the functionality in a class after inheriting from a base class, overriding methods in the derived class. Encapsulation Creating classes that hide their implementation details while still allowing access to the required functionality through the interface, access modifiers. General software development Application life cycle management Phases of application life cycle management, software testing. Interpret application specifications Application specifications, translating them into prototypes, code, select appropriate application type and components. Algorithms and data structures Arrays, stacks, queues, linked lists and sorting algorithms; performance implications of various data structures; choosing the right data structure. Web applications Web page development HTML, CSS, JavaScript. ASP.NET web application development Page life cycle, event model, state management, client-side versus server-side programming. Web hosting Creating virtual directories and websites, deploying web applications, understanding the role of Internet Information Services. Web services Web services that will be consumed by client applications, accessing web services from a client application, SOAP, WSDL. Desktop applications Windows apps UI design guideline categories, characteristics and capabilities of Store Apps, identify gestures. Console-based applications Characteristics and capabilities of console- based applications. Windows Services Characteristics and capabilities of Windows Services. Databases Relational database management systems Characteristics and capabilities of database products, database design, ERDs, normalisation concepts. Database query methods SQL, creating and accessing stored procedures, updating and selecting data. Database connection methods Connecting to various types of data stores, such as flat file; XML file; in-memory object; resource optimisation.

Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.