Scientific Programming with C++ Masterclass with STL, BOOST, CUDA, OpenMP and MPI Libraries: 21 Hours!

What you'll 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++

Requirements

None, this course will cover the basics of C++ to the advanced and useful libraries like STL, BOOST, OpenMP and MPI!

Description

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 FEATURESGet 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&APlease 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.REQUIREMENTSYou 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++

Overview

Section 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

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

Lecture 16 Struct vs Class

Lecture 17 Streams

Lecture 18 Strings

Lecture 19 Initializer

Lecture 20 Rvalue - Move semantics and forwarding

Lecture 21 Literals - User Defined

Lecture 22 Functions - Compiler Generated

Lecture 23 Pointers - Shared, Weak and Unique

Lecture 24 Classes - Resource managing

Lecture 25 Library - Regular Expressions

Lecture 26 Library - Clock and Timer

Lecture 27 Library - Random Numbers

Lecture 28 Tuples

Lecture 29 Constants

Lecture 30 Constructors and Destructors

Lecture 31 Operator Overloading - Assignments

Lecture 32 Types - Conversion and Casting

Lecture 33 Inheritance

Lecture 34 Operators - New Operator and Handler

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

Lecture 35 STL - Sequences (Vectors, List and Deque)

Lecture 36 STL - Associative Containers (Set and Map)

Lecture 37 STL - Unordered Associative Containers (Set and Map)

Lecture 38 STL - Iterators and Iterator Operations (Copy, Insert, etc.)

Lecture 39 STL - Functors

Lecture 40 STL - Non-Modifying Algorithms (Count, Min, Max, etc.)

Lecture 41 STL - Modifying Algorithms (Copy, Move, Swap, Transform, etc.)

Lecture 42 STL - Sorting and Searching Algorithms

Lecture 43 STL - Container Functions - Members vs Algorithms

Lecture 44 STL - Reverse Iterator

Lecture 45 STL - Find with Equivalence vs Equality

Lecture 46 STL - Remove Elements

Lecture 47 STL - Vectors vs Deques

Lecture 48 STL - Object Slicing

Lecture 49 Source Codes - Download

Section 4: C++ Boost Library

Lecture 50 Boost - Lexical Cast

Lecture 51 Boost - Variants

Lecture 52 Boost - Any

Lecture 53 Boost - Optional

Lecture 54 Boost - Arrays

Lecture 55 Boost Graphs Library - BGL

Lecture 56 Source Codes - Download

Section 5: C++ Concurrency (Threads)

Lecture 57 Threads

Lecture 58 Race and Mutex

Lecture 59 Deadlock, Unique Lock and Lazy Initialization

Lecture 60 Conditions - Threads

Lecture 61 Future, Promise and Async

Lecture 62 Callable Objects

Lecture 63 Packaged Tasks

Lecture 64 Time Constraints

Section 6: C++ OpenMP - Multithreaded Parallel Programming

Lecture 65 What is OpenMP - Multithreaded Parallel Programming?

Lecture 66 C++ OpenMP - Introduction

Lecture 67 C++ OpenMP - Fork and Join

Lecture 68 C++ OpenMP - Components for the Fork and Join

Lecture 69 C++ OpenMP - Synchronization

Lecture 70 C++ OpenMP - Clauses

Lecture 71 C++ OpenMP - Reduction (For-loop)

Lecture 72 C++ OpenMP - Parallel For-loop (Source Code)

Lecture 73 C++ OpenMP - Scheduling

Lecture 74 C++ OpenMP - Data Sharing

Lecture 75 C++ OpenMP - Worksharing Constructs

Lecture 76 C++ OpenMP - Hello World (Source Code)

Lecture 77 C++ OpenMP - Hello World! (HPC Demo)

Lecture 78 C++ OpenMP - Section Parallelization

Lecture 79 C++ OpenMP - Vector Addition (Source Code)

Section 7: C++ MPI - Distributed Programming

Lecture 80 C++ MPI: Introduction

Lecture 81 C++ MPI - What is Message Passing Interface?

Lecture 82 C++ MPI - Basics

Lecture 83 C++ MPI - Program Structure

Lecture 84 C++ MPI: Hellow World (Source Code)

Lecture 85 C++ MPI - Hello World (Demo)

Lecture 86 C++ MPI: Send and Receive (Concept)

Lecture 87 C++ MPI: Send and Receive

Lecture 88 C++ MPI - Simultaneous Send and Receive

Lecture 89 C++ MPI - Collective Communication

Lecture 90 C++ MPI - Non-Blocking Communication

Lecture 91 C++ MPI - Topologies

Section 8: C++ CUDA - GPU Programming

Lecture 92 C++ CUDA - Install

Lecture 93 C++ CUDA - Concepts

Lecture 94 C++ CUDA - Programming Model

Lecture 95 C++ CUDA - Parallelizing a For-Loop

Lecture 96 C++ CUDA - Indexing Threads within Grids and Blocks

Lecture 97 C++ CUDA - Memory Model

Lecture 98 C++ CUDA - Synchronization

Lecture 99 C++ CUDA - Vector Addition (Demonstration)

Lecture 100 C++ CUDA - Vector Addition (Source Code)

Section 9: C++ Scientitfic Libraries: MKL

Lecture 101 MKL - Intel® Math Kernel Library

Lecture 102 C++ MKL - Matrix Multiplication

Lecture 103 C++ MKL - Matrix Multiplication (Source Code)

Lecture 104 C++ MKL: Eigen Vector

Section 10: Scientific Software and HPC Job Submission

Lecture 105 Software Modules

Lecture 106 PBS Job Submission Commands

Lecture 107 Scientific Jobs Submission with PBS

Lecture 108 Slurm Commands

Lecture 109 Scientific Jobs Submission with Slurm

Section 11: Additional Content

Lecture 110 Scientific Programming School FREE Content - Introduction to the Interactive C++

Lecture 111 Interactive Version Access - FREE!

Lecture 112 Interactive Shell (by Scientific Programming School)

Developers, Analysts, Research positions requiring good C++