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Complete C++ Scientific Programming Bundle – 21 Hours!

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Complete C++ Scientific Programming Bundle – 21 Hours!, available at $54.99, has an average rating of 4.1, with 114 lectures, based on 99 reviews, and has 6889 subscribers.

Rating4.1
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You will learn about Understand programming C++ basics to the advanced C++ 17 Knowledge on developing complex C++ scientific applications Learn about C++ libraries STL, BOOST, MPI, OpenMP Be in a position to apply for Developer jobs, PhD and research positions requiring good C++ This course is ideal for individuals who are Developers, Analysts, Research positions requiring good C++ It is particularly useful for Developers, Analysts, Research positions requiring good C++.

Enroll now: Complete C++ Scientific Programming Bundle – 21 Hours!

Summary

Title: Complete C++ Scientific Programming Bundle – 21 Hours!

Price: $54.99

Average Rating: 4.1

Number of Lectures: 114

Number of Published Lectures: 112

Number of Curriculum Items: 114

Number of Published Curriculum Objects: 112

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand programming C++ basics to the advanced C++ 17
  • Knowledge on developing complex C++ scientific applications
  • Learn about C++ libraries STL, BOOST, MPI, OpenMP
  • Be in a position to apply for Developer jobs, PhD and research positions requiring good C++

Who Should Attend

  • Developers, Analysts, Research positions requiring good C++

Target Audiences

  • Developers, Analysts, Research positions requiring good C++

The ‘Scientific Programming with C++’ is easiest and the most innovative and complete hands-on practical C++ course on the Udemy Platform for learning scientific and research data programming! While languages like Python and R are increasingly popular for Scientific Programming or Data sciences, C/ C++ can be a stronger choice for efficient and effective data and scientific computing. In this course, we hands-on the latest C++17 for Scientific Programming.  The focus of this course lies on learning beginner to advanced programming on high-performance computers, object-oriented software design, generic or template-based programming, and the efficient implementation of numerical algorithms.

C++ is the best choice for efficient and effective programming in Research Data mining & Scientific Computing. In this course, we will hands-on the latest C++17 for Scientific Programming. Learn from the basics of C++ to the advanced and useful libraries like STL, BOOST, OpenMP and MPI! Main learning goals in this awesome course can be formulated as:

COURSE FEATURES

  • Get a basic concepts on the programming with C++.

  • Learn how to program with modern C++, using generic programming and advanced techniques, like meta programming, expression templates, and concepts.

  • Learn how to use programming tools and you can apply these tools to debug, benchmark, and manage your code. The list of tools include compilers, build systems, version control, debuggers, and profilers.

  • Learn to read, understand, and utilize (scientific) software libraries, like BLAS (Basic Linear Algebra Subroutines), LAPACK (Linear Algebra Package), STL (Standard template library), Boost (portable C++ library).

  • Learn how to code in HPC, using OpenMP and MPI.

  • There are numerous hands-on to practice the C++ programming throughout the course. Happy coding!

The focus of this course lies on aspects of software development like programming on high-performance computers, object-oriented software design, generic (template-based) programming, and the efficient implementation of numerical algorithms. Additionally experience in analysis, application and extension of software and software libraries is developed.  Three main learning goals can be formulated:  You know how to program with modern C++, using generic programming and advanced techniques, like meta programming, expression templates, and concepts. You know how to use programming tools and you can apply these tools to debug, benchmark, and manage your code. The list of tools include compilers, build systems, version control, debuggers, and profilers.  You can read, understand, and utilize (scientific) software libraries, like BLAS (Basic Linear Algebra Subroutines), LAPACK (Linear Algebra Package), STL (Standard template library), Dune (framework for the discretization of partial differential equations), MTL4 (Matrix Template Library), Boost (portable C++ library). There will be interactive exercises to practice the C++. programming.

Based on your earlier feedback, we are introducing a Zoom live class lecture series on this course through which we will explain different aspects of the C++17. Live classes will be delivered through the Scientific Programming School, which is an interactive and advanced e-learning platform for learning scientific coding. Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the Scientific Programming School(SCIENTIFIC PROGRAMMING IO). Instructions to join are given in the bonus content section.

Q&A

Please use the Q&A feature on Udemy to ask questions! We’d love to talk about why regular expressions don’t seem to be working, discussing decisions we made about course content, and debating regular expression philosophy. There’s no risk involved in taking this Course! This course comes with a 30-day money-back guarantee.Once you Enroll for this Course, you get lifetime access to this course and you will get all the future updates. you also get a Certification of Completion once you complete the course.

REQUIREMENTS

  • You will need a grasp of basic C++. It is a self-learning course with all Linux environments provided.

WHY YOU SHOULD GET THIS COURSE?

  •         Understand programming C++ basics to the advanced C++ 17

  •         Knowledge on developing complex C++ scientific applications

  •         Learn about C++ libraries STL, BOOST, MPI, OpenMP

  •         Be in a position to apply for Developer jobs, PhD and research positions requiring good C++

Course Curriculum

Chapter 1: C++ Fundamentals

Lecture 1: Welcome

Lecture 2: Why Get this Course?

Lecture 3: Instructor

Lecture 4: Free Interactive Shell with C++ Compiler

Lecture 5: Variables

Lecture 6: Conditions

Lecture 7: Arrays

Lecture 8: Loops

Lecture 9: Structures

Lecture 10: Functions

Lecture 11: Classes

Lecture 12: Pointers

Lecture 13: Inheritance

Lecture 14: Function Templates

Lecture 15: Class Templates

Chapter 2: C++ Advanced (C++11 and 17 Standards)

Lecture 1: Struct vs Class

Lecture 2: Streams

Lecture 3: Strings

Lecture 4: Initializer

Lecture 5: Rvalue – Move semantics and forwarding

Lecture 6: Literals – User Defined

Lecture 7: Functions – Compiler Generated

Lecture 8: Pointers – Shared, Weak and Unique

Lecture 9: Classes – Resource managing

Lecture 10: Library – Regular Expressions

Lecture 11: Library – Clock and Timer

Lecture 12: Library – Random Numbers

Lecture 13: Tuples

Lecture 14: Constants

Lecture 15: Constructors and Destructors

Lecture 16: Operator Overloading – Assignments

Lecture 17: Types – Conversion and Casting

Lecture 18: Inheritance

Lecture 19: Operators – New Operator and Handler

Chapter 3: C++ Standard Template Library (STL)

Lecture 1: STL – Sequences (Vectors, List and Deque)

Lecture 2: STL – Associative Containers (Set and Map)

Lecture 3: STL – Unordered Associative Containers (Set and Map)

Lecture 4: STL – Iterators and Iterator Operations (Copy, Insert, etc.)

Lecture 5: STL – Functors

Lecture 6: STL – Non-Modifying Algorithms (Count, Min, Max, etc.)

Lecture 7: STL – Modifying Algorithms (Copy, Move, Swap, Transform, etc.)

Lecture 8: STL – Sorting and Searching Algorithms

Lecture 9: STL – Container Functions – Members vs Algorithms

Lecture 10: STL – Reverse Iterator

Lecture 11: STL – Find with Equivalence vs Equality

Lecture 12: STL – Remove Elements

Lecture 13: STL – Vectors vs Deques

Lecture 14: STL – Object Slicing

Lecture 15: Source Codes – Download

Chapter 4: C++ Boost Library

Lecture 1: Boost – Lexical Cast

Lecture 2: Boost – Variants

Lecture 3: Boost – Any

Lecture 4: Boost – Optional

Lecture 5: Boost – Arrays

Lecture 6: Boost Graphs Library – BGL

Lecture 7: Source Codes – Download

Chapter 5: C++ Concurrency (Threads)

Lecture 1: Threads

Lecture 2: Race and Mutex

Lecture 3: Deadlock, Unique Lock and Lazy Initialization

Lecture 4: Conditions – Threads

Lecture 5: Future, Promise and Async

Lecture 6: Callable Objects

Lecture 7: Packaged Tasks

Lecture 8: Time Constraints

Chapter 6: C++ OpenMP – Multithreaded Parallel Programming

Lecture 1: What is OpenMP – Multithreaded Parallel Programming?

Lecture 2: C++ OpenMP – Introduction

Lecture 3: C++ OpenMP – Fork and Join

Lecture 4: C++ OpenMP – Components for the Fork and Join

Lecture 5: C++ OpenMP – Synchronization

Lecture 6: C++ OpenMP – Clauses

Lecture 7: C++ OpenMP – Reduction (For-loop)

Lecture 8: C++ OpenMP – Parallel For-loop (Source Code)

Lecture 9: C++ OpenMP – Scheduling

Lecture 10: C++ OpenMP – Data Sharing

Lecture 11: C++ OpenMP – Worksharing Constructs

Lecture 12: C++ OpenMP – Hello World (Source Code)

Lecture 13: C++ OpenMP – Hello World! (HPC Demo)

Lecture 14: C++ OpenMP – Section Parallelization

Lecture 15: C++ OpenMP – Vector Addition (Source Code)

Chapter 7: C++ MPI – Distributed Programming

Lecture 1: C++ MPI: Introduction

Lecture 2: C++ MPI – What is Message Passing Interface?

Lecture 3: C++ MPI – Basics

Lecture 4: C++ MPI – Program Structure

Lecture 5: C++ MPI: Hellow World (Source Code)

Lecture 6: C++ MPI – Hello World (Demo)

Lecture 7: C++ MPI: Send and Receive (Concept)

Lecture 8: C++ MPI: Send and Receive

Lecture 9: C++ MPI – Simultaneous Send and Receive

Lecture 10: C++ MPI – Collective Communication

Lecture 11: C++ MPI – Non-Blocking Communication

Lecture 12: C++ MPI – Topologies

Chapter 8: C++ CUDA – GPU Programming

Lecture 1: C++ CUDA – Install

Instructors

Rating Distribution

  • 1 stars: 11 votes
  • 2 stars: 11 votes
  • 3 stars: 12 votes
  • 4 stars: 24 votes
  • 5 stars: 41 votes

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