234 Data Structures & Algorithms (DSA) courses delivered Online

About Course Advanced C++: Master the Language of Champions Learn the advanced C++ concepts and techniques you need to build high-performance software applications. In this comprehensive course, you will learn: Generic programming with templates Metaprogramming with constexpr and reflection Advanced object-oriented programming techniques Concurrency and parallelism Performance optimization This course is designed for experienced C++ programmers who want to take their skills to the next level. You will learn from an experienced C++ developer who will teach you the concepts and skills you need to succeed. By the end of this course, you will be able to: Write high-performance, efficient, and maintainable C++ code. Use advanced C++ features to solve complex problems. Design and implement complex software applications. Build a portfolio of real-world C++ applications Throughout the course, you will work on a variety of hands-on projects to build your skills and create a portfolio of real-world C++ applications. Enroll today and start your journey to becoming a C++ expert! Bonus: Get access to the instructor's personal collection of C++ resources. Why learn advanced C++? C++ is a powerful and versatile language that can be used to build a wide variety of software applications. It is also one of the most in-demand languages in the software industry. Learning advanced C++ will give you a significant advantage in the job market and allow you to build more complex and sophisticated software applications. Here are some of the benefits of learning advanced C++: C++ is a high-performance language that can be used to build fast and efficient software applications. C++ is a versatile language that can be used to build a wide variety of software applications, including operating systems, embedded systems, games, and more. C++ is an in-demand language in the software industry, and there are many job opportunities for C++ programmers. Learning advanced C++ will give you a significant advantage in the job market and allow you to build more complex and sophisticated software applications. So what are you waiting for? Enroll in this course today and start your journey to becoming a C++ expert! What Will You Learn? Learn to program with one of the most powerful programming languages that exists today, C++ Master on every advanced C++ programming topics Learn to code C++ from scratch for application development Coding advanced problem statements using the C++ concepts Setting up a local C++ coding environment to create your own coding practices Develop skills on real-world class, object and methods programming techniques Learn how to implement C++ templates, template functions, and classes How to handle error, exception handling and catch real time app errors Apply overloading methods and deep inheritance to how code reusing for your development Polymorphism and abstract classes to implemeting secure code in multiple methods Learn to Apply overloading techniques in C++, Dynamic operators and conversions Course Content Getting Started with C++ Introduction Course Curriculum Getting Started on Windows, Mac or Linux How to Ask Great Questions FAQ's Get and Installing Visual Studio Creating Project C++ Hello World Program Compile and Run a CPP program C++ Object Oriented Programming (theory) Introduction What Are oops Data Structures What Are Access Modifiers C++ Classes Introduction Creating a Class Creating an Objects Class Methods Adding Parameters Constructors Constructor with Parameters The Destructor Get and Set Methods Access Modifiers Static Members C++ Objects and Methods Introduction Constant Objects and Functions Pointers to Class and Object Array of Objects C++ Operator Overloading Introduction Overloading the Equality Operator Overloading the Stream Insertion Operator Overloading the Stream Extraction Operator Overloading the Binary Arithmetic Operators Overloading the Assignment Operators Overloading the Unary Operators Overloading the Subscript Operator Inline Functions C++ Inheritance and Polymorphism Introduction Inheritance Protected Members Constructors and Inheritance Destructors and Inheritance Overriding Methods Polymorphism Abstract Classes Final Classes and Methods Deep Inheritance and Methods Multiple Inheritance C++ Error Handling and Exceptions Introduction What Are Exceptions Throwing an Exception Catching an Exception Catching Multiple Exceptions Create Custom Exceptions C++ Templates Introduction Creating a Function Template Function Template Arguments Overloading a Function Template Creating a Class Template Templates with Multiple Parameters A course by Sekhar Metla IT Industry Expert Xpert Learning RequirementsGood to have C++ basic, intermediate to start hereNo software is required in advance of the course (all software used in the course is free) Audience C++ Advanced level developers curious about programming Anyone interested in learning the Advanced concepts of C++ Anyone who wants to grasp the concept with real-world examples of coding Anyone who wants to become a proficient software developer Anyone who wants to become an independent programmer Audience C++ Advanced level developers curious about programming Anyone interested in learning the Advanced concepts of C++ Anyone who wants to grasp the concept with real-world examples of coding Anyone who wants to become a proficient software developer Anyone who wants to become an independent programmer

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Embark on a journey to master Python with our Diploma in Python Fundamentals course. From basic data types to advanced OOP, learn to code efficiently, handle files, and manage errors in Python. Ideal for beginners and those looking to solidify their programming skills.

Duration 3 Days 18 CPD hours This course is intended for Java Fundamentals is designed for tech enthusiasts who are familiar with some programming languages and want a quick introduction to the most important principles of Java. Overview After completing this course, you will be able to: Create and run Java programs Use data types, data structures, and control flow in your code Implement best practices while creating objects Work with constructors and inheritance Understand advanced data structures to organize and store data Employ generics for stronger check-types during compilation Learn to handle exceptions in your code Since its inception, Java has stormed the programming world. Its features and functionalities provide developers with the tools needed to write robust cross-platform applications. Java Fundamentals introduces you to these tools and functionalities that will enable you to create Java programs. The course begins with an introduction to the language, its philosophy, and evolution over time, until the latest release. You'll learn how the javac/java tools work and what Java packages are - the way a Java program is usually organized. Once you are comfortable with this, you'll be introduced to advanced concepts of the language, such as control flow keywords. You'll explore object-oriented programming and the part it plays in making Java what it is. In the concluding lessons, you'll be familiarized with classes, typecasting, and interfaces, and understand the use of data structures, arrays, strings, handling exceptions, and creating generics. Introduction to Java The Java Ecosystem Our First Java Application Packages Variables, Data Types, and Operators Variables and Data Types Integral Data Types Type casting Control Flow Conditional Statements Looping Constructs Object-Oriented Programming Object-Oriented Principles Classes and Objects Constructors The this Keyword Inheritance Overloading Constructor Overloading Polymorphism and Overriding Annotations References OOP in Depth Interfaces Typecasting The Object Class Autoboxing and Unboxing Abstract Classes and Methods Data Structures, Arrays, and Strings Data Structures and Algorithms Strings The Java Collections Framework and Generics Reading Data from Files The Java Collections Framework Generics Collection Advanced Data Structures in Java Implementing a Custom Linked List Implementing Binary Search Tree Enumerations Set and Uniqueness in Set Exception Handling Motivation behind Exceptions Exception Sources Exception Mechanics Best Practices

Duration 2 Days 12 CPD hours This course is intended for This course is intended for System and network engineers, technical architects and technical support personnel Overview Upon successful completion of this course, students will be able to install and operate a Cisco DNA Center (DNAC) This course will cover the basics of installing and operation of the Cisco DNA Center (DNAC). The Cisco DNAC is a stand-alone product that provides a single dashboard for every fundamental management task to simplify running an enterprise network. The DNAC is the management piece of the Software Defined Access (SDA) solution. Intent-based Networking overview DNA Center overview. DNA Center as a Platform. DNA Center Architecture & Design. DNA Center Installation DNA Center/Identity Services Engine (ISE) Integration ISE Integration configuration in DNA Center. DNA - Global - Add servers (e.g. ISE server(s)). DNA Center integration configuration in ISE. Approve pxGrid in ISE.Verify DNA/ISE integration DNA Center - Device Inventory Add networks devices to the DNA Center device inventory. Verify DNA Center Inventory configuration. DNA Center - Design - Network Hierarchy. Verify DNA Center - design configuration DNA Center - Design - Software Image Management (SWIM) Review SWIM image repository listing. Create golden software image & role. Verify golden software image creation DNA Center - Design ? Templates and Policies Templates ? Apache Velocity Engine. Command Runner. Policies: Group-Based, Application,Traffic Copy, IP-Based DNA Center - Provision Configuration Add devices to newly created sites/locations. Plug and Play (PnP). Verify DNA Center - provision configuration. DNA Center - Assurance Collection. DNA Center ? Administration

Duration 4 Days 24 CPD hours This course is intended for This is an intermediate course for individuals responsible for developing and implementing effective storage management techniques. Overview Establish a DFSMS configuration to automatically enforce your installation's storage management policies Convert service level requirements into appropriate parameters for data class, storage class, management class, and storage groups Create and test Automatic Class Selection (ACS) routines Convert volumes and move data to system-managed volumes with DFSMS Data Set Services (DFSMSdss) Specify appropriate management class and storage group parameters for DFSMS Hierarchical Storage Management (DFSMShsm) processing of system-managed data sets Plan to maintain your DFSMS environment using Naviquest Establish procedures to control, manage, and recover the storage management subsystem with ISMF and operator commands Develop a DFSMS implementation plan In this course you will learn how to plan and implement DFSMS and learn how to manage temporary and permanent data sets with an emphasis on disk storage. Course introduction and DFSMS overview Specify the storage administration functions that can be automatically performed by the system Identify the types of data set services that need to be established by negotiating service level agreements Correlate data set service requirements to the SMS configuration components: data class, storage class, management class, storage group, and automatic class selection routines Activating SMS Identify the functions eligible for exploitation with the installation of DFSMS Data Facility Product (DFSMSdfp) and the activation of SMS Create SMS control data sets Code SYS1.PARMLIB operands necessary to bring up SMS Create a minimal configuration Activate a configuration Writing ACS routines Identify the purpose of the ACS routines Develop an understanding of the statements Differentiate between literals and masks Describe the read variables available in the ACS routines Managing temporary data sets Create/alter storage classes and storage groups Identify steps to install and use the starter set Write ACS routines to handle temporary data sets Activate a system to manage temporary data sets Code commands to change volume/group SMS status Issue operator commands to display current status Exploiting DFSMS Describe the purpose of the data class Identify the features that the data class can exploit Create data sets using the space parameter Define Virtual Storage Access Method (VSAM) and volume attributes for data class Identify special data sets and their exploitation through the data class Managing permanent data sets Create/alter data classes, storage classes, management classes, and storage groups Translate current (DFSMShsm) service level agreements to management class parameters Identify alternatives and concerns for standard naming conventions Establish the controls for automatic backup of data sets Establish the controls for automatic volume dump Write ACS routines to manage permanent data Create a configuration that manages permanent data sets Create a new managed data set Identify function of storage class exit provided by Custom-Built Installation Process Offering (CBIPO) and resulting System Management Facility (SMF) records Using Naviquest Create test cases using Naviquest Perform storage administration tasks in batch Create online DFSMS reports Create model commands using Naviquest Use the COPYFILT macro Device preparation and data movement Initialize volumes as system-managed Move data into/out from system-managed control Convert volumes to/from system-managed Move data to utilize new hardware capabilities Controlling DFSMS Code commands to change SMS volume/group status Issue commands to save configurations and use alternate Active Control Data Set (ACDS) Issue command to use alternate Communication Data Set (COMMDS) Issue VARY SMS commands Communicate with the security administrator about storage management requirements Additional considerations Establish a plan for implementing SMS Locate sources of implementation planning checklists Identify the tools available to document the current system Identify multiple site considerations for recovery and exploitation Additional course details: Nexus Humans SS84 IBM DFSMS Implementation 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 SS84 IBM DFSMS Implementation 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.

Duration 2 Days 12 CPD hours This course is intended for This course is designed for people who want to learn the Python programming language in preparation for using Python to develop software for a wide range of applications, such as data science, machine learning, artificial intelligence, and web development. Overview In this course, you will develop simple command-line programs in Python. You will: Set up Python and develop a simple application. Declare and perform operations on simple data types, including strings, numbers, and dates. Declare and perform operations on data structures, including lists, ranges, tuples, dictionaries, and sets. Write conditional statements and loops. Define and use functions, classes, and modules. Manage files and directories through code. Deal with exceptions. Though Python has been in use for nearly thirty years, it has become one of the most popular languages for software development, particularly within the fields of data science, machine learning, artificial intelligence, and web development?all areas in which Python is widely used. Whether you're relatively new to programming, or have experience in other programming languages, this course will provide you with a comprehensive first exposure to the Python programming language that can provide you with a quick start in Python, or as the foundation for further learning. You will learn elements of the Python 3 language and development strategies by creating a complete program that performs a wide range of operations on a variety of data types, structures, and objects, implements program logic through conditional statements and loops, structures code for reusability through functions, classes, and modules, reads and writes files, and handles error conditions. Lesson 1: Setting Up Python and Developing a Simple Application Topic A: Set Up the Development Environment Topic B: Write Python Statements Topic C: Create a Python Application Topic D: Prevent Errors Lesson 2: Processing Simple Data Types Topic A: Process Strings and Integers Topic B: Process Decimals, Floats, and Mixed Number Types Lesson 3: Processing Data Structures Topic A: Process Ordered Data Structures Topic B: Process Unordered Data Structures Lesson 4: Writing Conditional Statements and Loops in Python Topic A: Write a Conditional Statement Topic B: Write a Loop Lesson 5: Structuring Code for Reuse Topic A: Define and Call a Function Topic B: Define and Instantiate a Class Topic C: Import and Use a Module Lesson 6: Writing Code to Process Files and Directories Topic A: Write to a Text File Topic B: Read from a Text File Topic C: Get the Contents of a Directory Topic D: Manage Files and Directories Lesson 7: Dealing with Exceptions Topic A: Handle Exceptions Topic B: Raise Exceptions

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

Duration 2.5 Days 15 CPD hours This course is intended for This course is intended for those with a basic understanding of Tableau who want to pursue mastery of the advanced features. Overview The goal of this course is to present essential Tableau concepts and its advanced functionalities to help better prepare and analyze data. This course will use Tableau Hyper, Tableau Prep and more. Getting Up to Speed ? a Review of the Basics Connecting Tableau to your data Connecting to Tableau Server Connecting to saved data sources Measure Names and Measure Values Three essential Tableau concepts Exporting data to other devices Summary All About Data ? Getting Your Data Ready Data mining and knowledge discovery process models CRISP?DM All About Data ? Joins, Blends, and Data Structures All About Data - Joins, Blends, and Data Structures Introduction to joins Introduction to complex joins Exercise: observing join culling Introduction to join calculations Introduction to spatial joins Introduction to unions Understanding data blending Order of operations No dimensions from a secondary source Introduction to scaffolding Introduction to data structures Exercise: adjusting the data structure for different questions Summary Table Calculations Table Calculations A definition and two questions Introduction to functions Directional and non-directional table calculations Application of functions Summary Level of Detail Calculations Level of Detail Calculations Building playgrounds Playground I: FIXED and EXCLUDE Playground II: INCLUDE Practical application Exercise: practical FIXED Exercise: practical INCLUDE Exercise: practical EXCLUDE Summary Beyond the Basic Chart Types Beyond the Basic Chart Types Improving popular visualizations Custom background images Tableau extensions Summary Mapping Mapping Extending Tableau's mapping capabilities without leaving Tableau Extending Tableau mapping with other technology Exercise: connecting to a WMS server Exploring the TMS file Exploring Mapbox Accessing different maps with a dashboard Creating custom polygons Converting shape files for Tableau Exercise: polygons for Texas Heatmaps Summary Tableau for Presentations Tableau for Presentations Getting the best images out of Tableau From Tableau to PowerPoint Embedding Tableau in PowerPoint Animating Tableau Story points and dashboards for Presentations Summary Visualization Best Practices and Dashboard Design Visualization Best Practices and Dashboard Design Visualization design theory Formatting rules Color rules Visualization type rules Compromises Keeping visualizations simple Dashboard design Dashboard layout Sheet selection Summary Advanced Analytics Advanced Analytics Self-service Analytics Use case ? Self-service Analytics Use case ? Geo-spatial Analytics Summary Improving Performance Improving Performance Understanding the performance-recording dashboard Exercise: exploring performance recording in Tableau desktop Performance-recording dashboard events Behind the scenes of the performance- recording dashboard Hardware and on-the-fly techniques Hardware considerations On-the-fly-techniques Single Data Source > Joining > Blending Three ways Tableau connects to data Using referential integrity when joining Advantages of blending Efficiently working with data sources Tuning data sources Working efficiently with large data sources Intelligent extracts Understanding the Tableau data extract Constructing an extract for optimal performance Exercise: summary aggregates for improved performance Optimizing extracts Exercise: materialized calculations Using filters wisely Extract filter performance Data source filter performance Context filters Dimension and measure filters Table-calculation filters Efficient calculations Boolean/Numbers > Date > String Additional performance considerations Avoid overcrowding a dashboard Fixing dashboard sizing Setting expectations Summary Additional course details: Nexus Humans Advanced Tableau 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 Advanced Tableau 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.