234 Data Structures & Algorithms (DSA) courses in Leicester delivered Online

Objective-C programming training course description A hands on introduction that will allow you to master Objective-C and start using it to write powerful native applications for even the newest Macs and iOS devices! Using The step-by-step approach, will let you get comfortable with Objective-C's unique capabilities and Apple's Xcode 5 development environment. Make the most of Objective-C objects and messaging. Work effectively with design patterns, collections, blocks, foundation classes, threading, Git and a whole lot more. Every session builds on what you've already learned, giving a rock-solid foundation for real-world success! What will you learn Use Xcode 5. Declare classes, instance variables, properties, methods, and actions. Use arrays, dictionaries, and sets. Expand and extend classes with protocols, delegates, categories, and extensions. Use Apple's powerful classes and frameworks. Objective-C programming training course details Who will benefit: Developers wanting to learn Objective-C. Prerequisites: Software development fundamentals. Duration 5 days Objective-C programming training course contents PART 1: GETTING STARTED WITH OBJECTIVE-C The Developer Program: Objective-C, enrolling as an Apple Developer, setting up the development environment, Xcode. Your first project. OO programming with Objective-C: OO projects, Frameworks, classes and instances, encapsulation, accessors, Inheritance. OO features in Objective-C: Messages, methods, working with id, nesting messages, method signatures and parameters. allocating and initializing objects. Using Xcode: Xcode, source code control, git and Xcode, Using a Remote Repository. Compiler Directives: Projects, Compiler Directives, Prefix headers, main.m, .h files. PART 2: OBJECTIVE-C BASICS Messaging in a Testbed App: Setting Up the Testbed Apps, Adding a Text Field and Connecting It to Your Code, Sending a Message to the Text Field, Reviewing the Message Syntax. Declaring a Class in an Interface File: Context, Creating an Instance Variable with id, What Happens When Execution Stops, dynamic binding, Creating an Instance Variable for with the Class Name and with a Superclass Name, instance variable visibility. Properties in an Interface File: Interface Variables vs Properties, Declared Properties, Using Attributes. Implementing Properties. @synthesize, @dynamic. Methods in an Interface File: Methods in a Class, class and instance methods, Method declaration, returning complex data structures from Methods. Actions in an Interface File: Actions, Actions in OS X and iOS, disconnecting actions. Routing messages with selectors: Receiver and selector objects in messages, Objective-C Runtime, SEL and @selector (), performSelector, NSInvocation, testing whether an Instance can respond to a selector. Building on the Foundation: The Foundation Framework, Foundation Classes, Foundation Paradigms and Policies; Mutability, class clusters, notifications. Defining a Class in Implementation Files: Projects, dynamic typing, creating a new App, implementing a method, expanding Classses with init Methods. Organizing Data with Collections: Collecting Objects, Property Lists, Runtime, comparing the Collection Classes, Creating a Collection, Objective-C Literal Syntax, Enumerating collections, Testing Membership in a Collection, Accessing an Object in a Collection. Managing Memory and Runtime Objects: Managing objects in memory, managing reference counts manually and with ARC, variable qualifiers, variable autorelease. PART 3: EXPANDING AND EXTENDING CLASSES Protocols and Delegates: Subclassing, Protocols, Delegates, Looking Deeper Inside Protocols. Categories and Extensions: Comparing categories and protocols, categories vs subclasses, working with categories, class extensions, informal protocols. Associative References and Fast Enumeration: Objective-C 2.0 Time-Saving Features, Extending Classes by Adding Instance Variables (Sort of), Using Fast Enumeration. Blocks: Revisiting Blocks, Callbacks, Blocks, Exploring Blocks in Cocoa, Cocoa Blocks and Memory. PART 4: BEYOND THE BASICS Handling Exceptions and Errors: Exception and Error classes: NSException, NSError, Identifying exceptions, throwing exceptions, catching exceptions. Queues and Threading: Getting Started with Concurrency, Introducing Queues, Dispatch Sources, Using Dispatch Queues. Working with the Debugger: Logging Information, Console Logs, NSLog, Smart Breakpoints, enhancing breakpoints with messages. Using Xcode Debug Gauges for Analysis: Debug Gauges, Monitoing CPU and memory utilization, monitoring energy, Using Instruments. PART 5: OPTIONAL TOPICS C Syntax Summary: Data Types, Control Structures. Apps, Packages, and Bundles: Project Bundles, lproj Files, Asset Catalogs, plist Files, Precompiled Header Files (.pch). Archiving and Packaging Apps for Development and Testing: Archiving.

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OOAD training course description A workshop course providing thorough practical knowledge of object oriented analysis and design methods. What will you learn Perform Systems Analysis with Object Oriented methods. Identify key classes and objects. Expand and refine OO problem domain models. Design Class hierarchies using inheritance and polymorphism. Design programs with Object Oriented methods. OOAD training course details Who will benefit: System analysts, designers, programmers and project managers. Prerequisites: It is desirable that delegates have experience of programming in C++/Java or some other OOP language. Duration 5 days OOAD training course contents What is OO? Classes, objects, messages, encapsulation, associations, inheritance, polymorphism, reusability. What is Systems Analysis and design? Data flow diagrams, structure diagrams. The OO approach. OOA The problem domain and object modelling. Identifying classes and objects. Generalisation and inheritance. Defining attributes and methods. OOD Refining the OOA results. Designing the User Interface. Designing the algorithms and data structures using objects. Designing the methods. OOP Prototyping. Implementing OOD with OOPs and OOPLs.

Java training course description A comprehensive introduction of the Java language and environment. It is important to note that the course will assume that the delegates are already familiar with the C language as this enables more advanced features of the Java language to be covered in the course. The course will also give an overview of areas related to programming in Java. What will you learn Describe the Java architecture. Write Java applets and applications. Debug Java programs. Examine existing code and determine its function. Use multimedia extensions, the awt, multithreading, exceptions within Java Java training course details Who will benefit: Those wishing to program in Java. Prerequisites: Complete C programming Duration 5 days Java training course contents Review of UNIX fundamentals What is Java? What Java is, history of Java, reasons for success. The Java Virtual Machine, Bytecodes, getting up and running with Java, Java resources. Simple Java applications. C features in Java Java data structures, Java flow control, differences from C, arrays, strings and packages. OO features in Java Java classes and objects, inheritance, overloading, packages. Differences from C++. Java applets Applications vs. applets, HTML, the applet tag, applet methods, life cycle, testing and debugging. Multimedia applets Images, sounds, fonts, colours and animation. Java products The JDK in detail, other development environments. Javabeans and JDBC overviews. Abstract Window Toolkit JFC and Swing versus AWT. Event handling (JDK 1.1), GUIs, panels, buttons, lists, scrollbars, text areas, frames… Exception handling and multithreading Handling exceptions. Starting, pausing, stopping threads, producers, consumers, monitoring. More standard classes Java file I/O, Streams, The system class. The networking model, java.net classes. Security and Java Types of attack, the security manager, craplets, securing the network. Integrating legacy code with Java

Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of programming fundamentals and object-oriented programming concepts. They will typically be high school students, post-secondary school students, or career changers, with no prior programming experience. They might want to gain an understanding of the core programming fundamentals before moving on to more advanced courses such as Programming in C#. Overview Explain core programming fundamentals such as computer storage and processing. Explain computer number systems such as binary. Create and use variables and constants in programs. Explain how to create and use functions in a program. Create and use decisions structures in a computer program. Create and use repetition (loops) in a computer program. Explain pseudocode and its role in programming. Explain the basic computer data structures such as arrays, lists, stacks, and queues. Implement object-oriented programming concepts. Create and use classes in a computer program. Implement encapsulation, inheritance, and polymorphism. Describe the base class library (BCL) in the .NET Framework. Explain the application security concepts. Implement simple I/O in a computer program. Identify application errors and explain how to debug an application and handle errors. Identify the performance considerations for applications. In this 5-day course, students will learn the basics of computer programming through the use of Microsoft Visual Studio 2022 and the Visual C# and Visual Basic programming languages. The course assumes no prior programming experience and introduces the concepts needed to progress to the intermediate courses on programming, Programming in C#. The focus will be on core programming concepts such as computer storage, data types, decision structures, and repetition by using loops. The course also covers an introduction to object-oriented programming covering classes, encapsulation, inheritance, and polymorphism. Coverage is also included around exception handling, application security, performance, and memory management. 1 - Introduction to Core Programming Concepts Computer Data Storage and Processing Application Types Application Lifecycle Code Compilation 2 - Core Programming Language Concepts Syntax Data Types Variables and Constants 3 - Program Flow Introduction to Structured Programming Concepts Introduction to Branching Using Functions Using Decision Structures Introducing Repetition 4 - Algorithms and Data Structures Understand How to Write Pseudocode Algorithm Examples Introduction to Data Structures 5 - Error Handling and Debugging Introduction to Program Errors Introduction to Structured Error Handling Introduction to Debugging 6 - Introduction to Object-Oriented Programming Introduction to Complex Structures Introduction to Structs Introduction to Classes Introducing Encapsulation 7 - More Object-Oriented Programming Introduction to Inheritance Introduction to Polymorphism Introduction to .NET and the Base Class Library 8 - Introduction to Application Security Authentication and Authorization Code Permissions on Computers Introducing Code Signing 9 - Core I/O Programming Using Console I/O Using File I/O 10 - Application Performance and Memory Management Value Types vs Reference Types Converting Types The Garbage Collector Additional course details: Nexus Humans 55337 Introduction to Programming 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 55337 Introduction to Programming 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.

CWISA training course description This CWISA course covers wireless technologies with reference to IoT. It examines from an IoT perspective how wireless works, and is an excellent introduction to IoT for the wireless engineer. Topics range from wireless technologies, RF, to mobile networks, IoT, and security. What will you learn Describe wireless networking and IoT technologies. Explain basic RF communications. Plan wireless solutions. Describe how to implement wireless solutions. Use best practices in implementing wireless solutions. CWISA training course details Who will benefit: Anyone working with IoT technologies. Prerequisites: RF fundamentals. Duration 4 days CWISA training course contents Introduction to wireless technologies History of wireless, radio waves and frequencies, wireless technologies and related components, common components of wireless solutions, LAN networking requirements, Network security, Implementing wireless solutions, staging, documentation, security updates, Industry organizations, IEEE, compatibility and certification groups. Wireless network use cases Wireless BANs, Wireless PANs, Wireless LANs, Wireless MANs, Wireless WANs, Wireless sensor networks, New network driver-Internet of Things, IoT for industry (IIoT), IoT for connected vehicles, Residential environments, Retail, Education (K12), Higher education, Agriculture, Smart cities / Public access, Health care, Office buildings, Hospitality, Industry, Stadiums, arenas, and large public venues. Planning wireless solutions Identifying use cases and applications, common wireless requirements and constraints, performing a wireless system design, selecting and evaluating design parameters. RF communications RF wave characteristics, RF propagation behaviours, RF signal metrics, fundamentals of wireless modulation. other wireless carriers, common frequency bands. Radio frequency hardware Hardware levels, basic RF hardware components (circuit board level), RF link types (use category). RF device types. Mobile communications networks Mobile networks, LTE, 5G, Use cases. Short-range, low-rate, and low-power networks RF and speed, RF and range, RF and power, 802.11, 802.15.4, Bluetooth, LoRa (Long range) / LoRaWAN, ZigBee, 6LoWPAN, NB-IoT and LTE-M. Wireless sensor networks What is a Wireless Sensor Network (WSN)? WSN applications, Sensors and actuators, WSN architectures, Planning a WSN. Internet of Things (IoT) Internet of Things (IoT) defined, IoT history and its definition revisited, one more comment on the definition of IoT, IoT verticals, Oil & Gas, IoT structure/ architecture basics, IoT connected objects. Securing wireless networks Confidentiality, integrity and availability, Privacy, non-repudiation, authenticity & safety, Importance of authentication in wireless networks, Key cryptographic technologies & concepts, Authentication methods, Authorisation, OAuth 2.0 authorisation framework, monitoring. Troubleshooting wireless solutions Proper solutions design, designing and implementing wireless solutions, basic installation procedures, general configuration considerations, troubleshooting and remediation, troubleshoot common problems in wireless solutions. Programming, scripting and automation What is an API? categories of APIs, common API communication methods, choosing a language, why are we integrating systems? Application & integration architectures. Data structures & types, XML, YAML, API types.

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.

Recent developments in data analytics and statistics underscore the critical importance of understanding both data structure and analytics methodologies in today's data-driven world. With the exponential growth of data, businesses are increasingly relying on skilled professionals who can harness the power of data to drive informed decision-making. Our comprehensive Data Structure, Data Analytics with Statistics & Data Science QLS Endorsed Diploma bundle, endorsed by the Quality Licence Scheme (QLS) and accredited by the CPD Quality Standards (QS), offers a holistic approach to mastering data structure, data analytics, and statistical techniques. In an era where data reigns supreme, organisations seek individuals who can navigate complex datasets with confidence and precision. This Data Structure, Data Analytics bundle equips learners with the essential skills and knowledge needed to excel in the field of data science and analytics. By delving into topics such as data manipulation, statistical analysis, and database management, participants gain a deep understanding of how to extract valuable insights from raw data. Moreover, our guided courses in career development and communication empower learners to effectively communicate their findings and advance their professional journey. Bundle Include includes: QLS Endorsed Courses: Course 01: Certificate in Data Analytics with Tableau at QLS Level 3 Course 02: Diploma in Data Structure at QLS Level 5 Course 03: Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 CPD QS Accredited Courses: Course 04: Business and Data Analytics for Beginners Course 05: Learn Financial Analytics and Statistical Tools Course 06: SQL For Data Analytics & Database Development Course 07: Big Data Analytics with PySpark Power BI and MongoDB Course 08: Google Data Studio: Data Analytics Course 09: Business Intelligence Analyst Course 10: Spatial Data Visualization and Machine Learning in Python Course 11: Data Analysis In Excel Take your career to the next level with our Data Structure, Data Analytics bundle that includes technical courses and five guided courses focused on personal development and career growth. Course 12: Career Development Plan Fundamentals Course 13: CV Writing and Job Searching Course 14: Networking Skills for Personal Success Course 15: Ace Your Presentations: Public Speaking Masterclass Course 16: Decision Making and Critical Thinking Seize this opportunity to elevate your career with our comprehensive Data Structure, Data Analytics bundle, endorsed by the prestigious QLS and accredited by CPD.Data Structure, Data Analytics with Statistics & Data Science QLS Endorsed Diploma. Learning Outcomes: Upon completion of this Data Structure, Data Analytics bundle, participants will be able to: Demonstrate proficiency in data analytics tools such as Tableau, SQL, and Google Data Studio through Data Structure, Data Analytics courses. Apply statistical techniques to analyse and interpret data for informed decision-making. Design and implement data structures to efficiently store and retrieve information. Utilise machine learning algorithms for predictive analysis and pattern recognition. Develop effective communication and presentation skills to convey insights to stakeholders. Navigate career development pathways in the field of data science and analytics. This Data Structure, Data Analytics course bundle provides a deep dive into the foundational principles of data structure, data analytics, and statistical methodologies. Participants will explore the fundamental concepts of data manipulation, including sorting, searching, and storing data efficiently. Through hands-on exercises and theoretical discussions, learners will gain a solid understanding of various data structures such as arrays, linked lists, trees, and graphs, along with their applications in real-world scenarios. Moreover, the Data Structure, Data Analytics bundle encompasses a comprehensive exploration of data analytics techniques, equipping participants with the skills to extract actionable insights from complex datasets. From descriptive and inferential statistics to predictive modelling and machine learning algorithms, learners will discover how to uncover patterns, trends, and correlations within data, enabling informed decision-making and strategic planning. Throughout the Data Structure, Data Analytics course, emphasis is placed on practical applications and case studies, allowing participants to apply their knowledge to solve real-world problems in diverse domains. CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Structure, Data Analytics course is perfect for: Aspiring data analysts seeking to enhance their analytical skills acrod Data Structure, Data Analytics courses. Professionals transitioning into roles requiring proficiency in data analytics. Students pursuing careers in data science, statistics, or related fields. Business professionals looking to leverage data for strategic decision-making. Individuals interested in advancing their career prospects in the field of data analytics. Anyone seeking to gain a comprehensive understanding of data structure, analytics, and statistics. Requirements You are warmly invited to register for this bundle. Please be aware that there are no formal entry requirements or qualifications necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Upon completion of the Data Structure, Data Analytics courses, you will be able to: Data Analyst Business Intelligence Analyst Data Scientist Statistician Database Administrator Machine Learning Engineer Data Engineer Certificates 13 CPD Quality Standard Certificates Digital certificate - Included 3 QLS Endorsed Certificates Hard copy certificate - Included

Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects

Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) 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 CompTIA Data Plus (DA0-001) 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.