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weijie-chen / Linear Algebra With PythonLecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.
ShantanilBagchi / DataCampDataCamp: 1) Data Scientist with Python 2) Data Analyst with Python 3) Data Analyst with SQL Server 4) Machine Learning Scientist with Python
togethercomputer / Open Data ScientistOpen AI data scientist agent that automates complex data analysis tasks using the ReAct framework. Execute Python code locally or in the cloud, upload datasets, and generate detailed analytical reports with minimal setup.
sanusanth / Python Basic ProgramsWhat is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Good to know The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular. In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files. Python Syntax compared to other programming languages Python was designed for readability, and has some similarities to the English language with influence from mathematics. Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses. Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose. Applications for Python Python is used in many application domains. Here's a sampling. The Python Package Index lists thousands of third party modules for Python. Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS. Python's standard library supports many Internet protocols: HTML and XML JSON E-mail processing. Support for FTP, IMAP, and other Internet protocols. Easy-to-use socket interface. And the Package Index has yet more libraries: Requests, a powerful HTTP client library. Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML. Feedparser for parsing RSS/Atom feeds. Paramiko, implementing the SSH2 protocol. Twisted Python, a framework for asynchronous network programming. Scientific and Numeric Python is widely used in scientific and numeric computing: SciPy is a collection of packages for mathematics, science, and engineering. Pandas is a data analysis and modeling library. IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing. The Software Carpentry Course teaches basic skills for scientific computing, running bootcamps and providing open-access teaching materials. Education Python is a superb language for teaching programming, both at the introductory level and in more advanced courses. Books such as How to Think Like a Computer Scientist, Python Programming: An Introduction to Computer Science, and Practical Programming. The Education Special Interest Group is a good place to discuss teaching issues. Desktop GUIs The Tk GUI library is included with most binary distributions of Python. Some toolkits that are usable on several platforms are available separately: wxWidgets Kivy, for writing multitouch applications. Qt via pyqt or pyside Platform-specific toolkits are also available: GTK+ Microsoft Foundation Classes through the win32 extensions Software Development Python is often used as a support language for software developers, for build control and management, testing, and in many other ways. SCons for build control. Buildbot and Apache Gump for automated continuous compilation and testing. Roundup or Trac for bug tracking and project management. Business Applications Python is also used to build ERP and e-commerce systems: Odoo is an all-in-one management software that offers a range of business applications that form a complete suite of enterprise management applications. Try ton is a three-tier high-level general purpose application platform.
bookworm52 / EthicalHackingFromScratchWelcome to my comprehensive course on python programming and ethical hacking. The course assumes you have NO prior knowledge in any of these topics, and by the end of it you'll be at a high intermediate level being able to combine both of these skills to write python programs to hack into computer systems exactly the same way that black hat hackers do. That's not all, you'll also be able to use the programming skills you learn to write any program even if it has nothing to do with hacking. This course is highly practical but it won't neglect the theory, we'll start with basics of ethical hacking and python programming and installing the needed software. Then we'll dive and start programming straight away. You'll learn everything by example, by writing useful hacking programs, no boring dry programming lectures. The course is divided into a number of sections, each aims to achieve a specific goal, the goal is usually to hack into a certain system! We'll start by learning how this system work and its weaknesses, then you'll lean how to write a python program to exploit these weaknesses and hack the system. As we write the program I will teach you python programming from scratch covering one topic at a time. By the end of the course you're going to have a number of ethical hacking programs written by yourself (see below) from backdoors, keyloggers, credential harvesters, network hacking tools, website hacking tools and the list goes on. You'll also have a deep understanding on how computer systems work, how to model problems, design an algorithm to solve problems and implement the solution using python. As mentioned in this course you will learn both ethical hacking and programming at the same time, here are some of the topics that will be covered in the course: Programming topics: Writing programs for python 2 and 3. Using modules and libraries. Variables, types ...etc. Handling user input. Reading and writing files. Functions. Loops. Data structures. Regex. Desiccation making. Recursion. Threading. Object oriented programming. Packet manipulation using scapy. Netfilterqueue. Socket programming. String manipulation. Exceptions. Serialisation. Compiling programs to binary executables. Sending & receiving HTTP requests. Parsing HTML. + more! Hacking topics: Basics of network hacking / penetration testing. Changing MAC address & bypassing filtering. Network mapping. ARP Spoofing - redirect the flow of packets in a network. DNS Spoofing - redirect requests from one website to another. Spying on any client connected to the network - see usernames, passwords, visited urls ....etc. Inject code in pages loaded by any computer connected to the same network. Replace files on the fly as they get downloaded by any computer on the same network. Detect ARP spoofing attacks. Bypass HTTPS. Create malware for Windows, OS X and Linux. Create trojans for Windows, OS X and Linux. Hack Windows, OS X and Linux using custom backdoor. Bypass Anti-Virus programs. Use fake login prompt to steal credentials. Display fake updates. Use own keylogger to spy on everything typed on a Windows & Linux. Learn the basics of website hacking / penetration testing. Discover subdomains. Discover hidden files and directories in a website. Run wordlist attacks to guess login information. Discover and exploit XSS vulnerabilities. Discover weaknesses in websites using own vulnerability scanner. Programs you'll build in this course: You'll learn all the above by implementing the following hacking programs mac_changer - changes MAC Address to anything we want. network_scanner - scans network and discovers the IP and MAC address of all connected clients. arp_spoofer - runs an arp spoofing attack to redirect the flow of packets in the network allowing us to intercept data. packet_sniffer - filters intercepted data and shows usernames, passwords, visited links ....etc dns_spoofer - redirects DNS requests, eg: redirects requests to from one domain to another. file_interceptor - replaces intercepted files with any file we want. code_injector - injects code in intercepted HTML pages. arpspoof_detector - detects ARP spoofing attacks. execute_command payload - executes a system command on the computer it gets executed on. execute_and_report payload - executes a system command and reports result via email. download_and_execute payload - downloads a file and executes it on target system. download_execute_and_report payload - downloads a file, executes it, and reports result by email. reverse_backdoor - gives remote control over the system it gets executed on, allows us to Access file system. Execute system commands. Download & upload files keylogger - records key-strikes and sends them to us by email. crawler - discovers hidden paths on a target website. discover_subdomains - discovers subdomains on target website. spider - maps the whole target website and discovers all files, directories and links. guess_login - runs a wordlist attack to guess login information. vulnerability_scanner - scans a target website for weaknesses and produces a report with all findings. As you build the above you'll learn: Setting up a penetration testing lab to practice hacking safely. Installing Kali Linux and Windows as virtual machines inside ANY operating system. Linux Basics. Linux terminal basics. How networks work. How clients communicate in a network. Address Resolution Protocol - ARP. Network layers. Domain Name System - DNS. Hypertext Transfer Protocol - HTTP. HTTPS. How anti-virus programs work. Sockets. Connecting devices over TCP. Transferring data over TCP. How website work. GET & POST requests. And more! By the end of the course you're going to have programming skills to write any program even if it has nothing to do with hacking, but you'll learn programming by programming hacking tools! With this course you'll get 24/7 support, so if you have any questions you can post them in the Q&A section and we'll respond to you within 15 hours. Notes: This course is created for educational purposes only and all the attacks are launched in my own lab or against devices that I have permission to test. This course is totally a product of Zaid Sabih & zSecurity, no other organisation is associated with it or a certification exam. Although, you will receive a Course Completion Certification from Udemy, apart from that NO OTHER ORGANISATION IS INVOLVED. What you’ll learn 170+ videos on Python programming & ethical hacking Install hacking lab & needed software (on Windows, OS X and Linux) Learn 2 topics at the same time - Python programming & Ethical Hacking Start from 0 up to a high-intermediate level Write over 20 ethical hacking and security programs Learn by example, by writing exciting programs Model problems, design solutions & implement them using Python Write programs in Python 2 and 3 Write cross platform programs that work on Windows, OS X & Linux Have a deep understanding on how computer systems work Have a strong base & use the skills learned to write any program even if its not related to hacking Understand what is Hacking, what is Programming, and why are they related Design a testing lab to practice hacking & programming safely Interact & use Linux terminal Understand what MAC address is & how to change it Write a python program to change MAC address Use Python modules and libraries Understand Object Oriented Programming Write object oriented programs Model & design extendable programs Write a program to discover devices connected to the same network Read, analyse & manipulate network packets Understand & interact with different network layers such as ARP, DNS, HTTP ....etc Write a program to redirect the flow of packets in a network (arp spoofer) Write a packet sniffer to filter interesting data such as usernames and passwords Write a program to redirect DNS requests (DNS Spoofer) Intercept and modify network packets on the fly Write a program to replace downloads requested by any computer on the network Analyse & modify HTTP requests and responses Inject code in HTML pages loaded by any computer on the same network Downgrade HTTPS to HTTP Write a program to detect ARP Spoofing attacks Write payloads to download a file, execute command, download & execute, download execute & report .....etc Use sockets to send data over TCP Send data reliably over TCP Write client-server programs Write a backdoor that works on Windows, OS X and Linux Implement cool features in the backdoor such as file system access, upload and download files and persistence Write a remote keylogger that can register all keystrikes and send them by Email Interact with files using python (read, write & modify) Convert python programs to binary executables that work on Windows, OS X and Linux Convert malware to torjans that work and function like other file types like an image or a PDF Bypass Anti-Virus Programs Understand how websites work, the technologies used and how to test them for weaknesses Send requests towebsites and analyse responses Write a program that can discover hidden paths in a website Write a program that can map a website and discover all links, subdomains, files and directories Extract and submit forms from python Run dictionary attacks and guess login information on login pages Analyse HTML using Python Interact with websites using Python Write a program that can discover vulnerabilities in websites Are there any course requirements or prerequisites? Basic IT knowledge No Linux, programming or hacking knowledge required. Computer with a minimum of 4GB ram/memory Operating System: Windows / OS X / Linux Who this course is for: Anybody interested in learning Python programming Anybody interested in learning ethical hacking / penetration testing Instructor User photo Zaid Sabih Ethical Hacker, Computer Scientist & CEO of zSecurity My name is Zaid Al-Quraishi, I am an ethical hacker, a computer scientist, and the founder and CEO of zSecurity. I just love hacking and breaking the rules, but don’t get me wrong as I said I am an ethical hacker. I have tremendous experience in ethical hacking, I started making video tutorials back in 2009 in an ethical hacking community (iSecuri1ty), I also worked as a pentester for the same company. In 2013 I started teaching my first course live and online, this course received amazing feedback which motivated me to publish it on Udemy. This course became the most popular and the top paid course in Udemy for almost a year, this motivated me to make more courses, now I have a number of ethical hacking courses, each focusing on a specific field, dominating the ethical hacking topic on Udemy. Now I have more than 350,000 students on Udemy and other teaching platforms such as StackSocial, StackSkills and zSecurity. Instructor User photo z Security Leading provider of ethical hacking and cyber security training, zSecurity is a leading provider of ethical hacking and cyber security training, we teach hacking and security to help people become ethical hackers so they can test and secure systems from black-hat hackers. Becoming an ethical hacker is simple but not easy, there are many resources online but lots of them are wrong and outdated, not only that but it is hard to stay up to date even if you already have a background in cyber security. Our goal is to educate people and increase awareness by exposing methods used by real black-hat hackers and show how to secure systems from these hackers. Video course
anurag629 / 50 Days Data ScienceA 50-Day Guide to Becoming a Data Scientist with Python, SQL, and Machine Learning
datamole-ai / EdvartAn open-source Python library for Data Scientists & Data Analysts designed to simplify the exploratory data analysis process. Using Edvart, you can explore data sets and generate reports with minimal coding.
yachty66 / Openai Pricing Logger🚀 openai_pricing_logger: Track & log OpenAI API costs with ease. A Python package for monitoring GPT-3.5-turbo & GPT-4 usage costs. Lightweight, automatic cost logging. Ideal for developers, data scientists. OpenAI cost tracking, API logging, Python, GPT models
MayumyCH / Data Scientist With Python DatacampAnotaciones del career "Data Scientist with Python" de Datacamp 📈, gracias a la beca de DATASCIENCIEFEM💜. #Data_Challenge_365_Fem 👩💻
abdelrahmaan / Machine Learning Scientist With Python By DataCampPython programming skill set with the toolbox to perform supervised, unsupervised, and deep learning, learn how to process data for features, train your models, assess performance, and tune parameters for better performance. natural language processing, image processing, and popular libraries such as Spark and Keras.
AmirhosseinHonardoust / AmirhosseinHonardoustI’m Amirhosein Honardoust, a passionate developer and data scientist with experience in Python, PyTorch, deep learning, and machine learning projects across vision, NLP, and forecasting. I enjoy turning data into insights and building portfolio-ready AI applications that combine practicality with creativity.
datacarpentry / Python SocialsciData Analysis and Visualization with Python for Social Scientists
FTiniNadhirah / Datacamp Data Scientist With Python 2019 And 2020This is about learning data scientist with Python 2019 and some new updated courses in DataCamp. All the answers given written by myself
Hazrat-Ali9 / Big Data Analytics🚂 Big Data Analytics 🚞 the backbone of 🚒 modern data-driven 🛺 decision making Perfect 🚅 data scientists analysts ✈ and engineers working 🚁 with large scale datasets 🛼 Hadoop Spark Hive 🚤 Kafka Flink MapReduce 🚋 and NoSQL databases data 🏰 mining machine learning 🏘 big data tools cloud 🥎 platforms and Python Scala 🎁
Ashleshk / IBM Data Science Specialization CourseraData Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets. It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics. Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.
rsandler00 / Plotly Scientific Plotsplotly-scientific-tools is meant to augment the plotly and dash visualization libraries for python. It is designed to combine rapid and beautiful data visualizations along with statistical analysis for research scientists and data scientists.
tonyleidong / OptimalFlowOptimalFlow is an omni-ensemble and scalable automated machine learning Python toolkit, which uses Pipeline Cluster Traversal Experiments(PCTE) and Selection-based Feature Preprocessor with Ensemble Encoding(SPEE), to help data scientists build optimal models, and automate supervised learning workflow with simpler coding.
AmirhosseinHonardoust / Data Storytelling DashboardA fully interactive data storytelling dashboard for e-commerce analytics. Built with Python, Streamlit, and Plotly, it transforms transactional data into actionable insights through KPIs, cohort retention, RFM segmentation, and global visualizations, perfect for analysts and data scientists.
ultranet1 / APACHE AIRFLOW DATA PIPELINESProject Description: A music streaming company wants to introduce more automation and monitoring to their data warehouse ETL pipelines and they have come to the conclusion that the best tool to achieve this is Apache Airflow. As their Data Engineer, I was tasked to create a reusable production-grade data pipeline that incorporates data quality checks and allows for easy backfills. Several analysts and Data Scientists rely on the output generated by this pipeline and it is expected that the pipeline runs daily on a schedule by pulling new data from the source and store the results to the destination. Data Description: The source data resides in S3 and needs to be processed in a data warehouse in Amazon Redshift. The source datasets consist of JSON logs that tell about user activity in the application and JSON metadata about the songs the users listen to. Data Pipeline design: At a high-level the pipeline does the following tasks. Extract data from multiple S3 locations. Load the data into Redshift cluster. Transform the data into a star schema. Perform data validation and data quality checks. Calculate the most played songs for the specified time interval. Load the result back into S3. dag Structure of the Airflow DAG Design Goals: Based on the requirements of our data consumers, our pipeline is required to adhere to the following guidelines: The DAG should not have any dependencies on past runs. On failure, the task is retried for 3 times. Retries happen every 5 minutes. Catchup is turned off. Do not email on retry. Pipeline Implementation: Apache Airflow is a Python framework for programmatically creating workflows in DAGs, e.g. ETL processes, generating reports, and retraining models on a daily basis. The Airflow UI automatically parses our DAG and creates a natural representation for the movement and transformation of data. A DAG simply is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies. A DAG describes how you want to carry out your workflow, and Operators determine what actually gets done. By default, airflow comes with some simple built-in operators like PythonOperator, BashOperator, DummyOperator etc., however, airflow lets you extend the features of a BaseOperator and create custom operators. For this project, I developed several custom operators. operators The description of each of these operators follows: StageToRedshiftOperator: Stages data to a specific redshift cluster from a specified S3 location. Operator uses templated fields to handle partitioned S3 locations. LoadFactOperator: Loads data to the given fact table by running the provided sql statement. Supports delete-insert and append style loads. LoadDimensionOperator: Loads data to the given dimension table by running the provided sql statement. Supports delete-insert and append style loads. SubDagOperator: Two or more operators can be grouped into one task using the SubDagOperator. Here, I am grouping the tasks of checking if the given table has rows and then run a series of data quality sql commands. HasRowsOperator: Data quality check to ensure that the specified table has rows. DataQualityOperator: Performs data quality checks by running sql statements to validate the data. SongPopularityOperator: Calculates the top ten most popular songs for a given interval. The interval is dictated by the DAG schedule. UnloadToS3Operator: Stores the analysis result back to the given S3 location. Code for each of these operators is located in the plugins/operators directory. Pipeline Schedule and Data Partitioning: The events data residing on S3 is partitioned by year (2018) and month (11). Our task is to incrementally load the event json files, and run it through the entire pipeline to calculate song popularity and store the result back into S3. In this manner, we can obtain the top songs per day in an automated fashion using the pipeline. Please note, this is a trivial analyis, but you can imagine other complex queries that follow similar structure. S3 Input events data: s3://<bucket>/log_data/2018/11/ 2018-11-01-events.json 2018-11-02-events.json 2018-11-03-events.json .. 2018-11-28-events.json 2018-11-29-events.json 2018-11-30-events.json S3 Output song popularity data: s3://skuchkula-topsongs/ songpopularity_2018-11-01 songpopularity_2018-11-02 songpopularity_2018-11-03 ... songpopularity_2018-11-28 songpopularity_2018-11-29 songpopularity_2018-11-30 The DAG can be configured by giving it some default_args which specify the start_date, end_date and other design choices which I have mentioned above. default_args = { 'owner': 'shravan', 'start_date': datetime(2018, 11, 1), 'end_date': datetime(2018, 11, 30), 'depends_on_past': False, 'email_on_retry': False, 'retries': 3, 'retry_delay': timedelta(minutes=5), 'catchup_by_default': False, 'provide_context': True, } How to run this project? Step 1: Create AWS Redshift Cluster using either the console or through the notebook provided in create-redshift-cluster Run the notebook to create AWS Redshift Cluster. Make a note of: DWN_ENDPOINT :: dwhcluster.c4m4dhrmsdov.us-west-2.redshift.amazonaws.com DWH_ROLE_ARN :: arn:aws:iam::506140549518:role/dwhRole Step 2: Start Apache Airflow Run docker-compose up from the directory containing docker-compose.yml. Ensure that you have mapped the volume to point to the location where you have your DAGs. NOTE: You can find details of how to manage Apache Airflow on mac here: https://gist.github.com/shravan-kuchkula/a3f357ff34cf5e3b862f3132fb599cf3 start_airflow Step 3: Configure Apache Airflow Hooks On the left is the S3 connection. The Login and password are the IAM user's access key and secret key that you created. Basically, by using these credentials, we are able to read data from S3. On the right is the redshift connection. These values can be easily gathered from your Redshift cluster connections Step 4: Execute the create-tables-dag This dag will create the staging, fact and dimension tables. The reason we need to trigger this manually is because, we want to keep this out of main dag. Normally, creation of tables can be handled by just triggering a script. But for the sake of illustration, I created a DAG for this and had Airflow trigger the DAG. You can turn off the DAG once it is completed. After running this DAG, you should see all the tables created in the AWS Redshift. Step 5: Turn on the load_and_transform_data_in_redshift dag As the execution start date is 2018-11-1 with a schedule interval @daily and the execution end date is 2018-11-30, Airflow will automatically trigger and schedule the dag runs once per day for 30 times. Shown below are the 30 DAG runs ranging from start_date till end_date, that are trigged by airflow once per day. schedule
sanusanth / C Basic Simple ProgramWhat is C++? C++ is a general-purpose, object-oriented programming language. It was created by Bjarne Stroustrup at Bell Labs circa 1980. C++ is very similar to C (invented by Dennis Ritchie in the early 1970s). C++ is so compatible with C that it will probably compile over 99% of C programs without changing a line of source code. Though C++ is a lot of well-structured and safer language than C as it OOPs based. Some computer languages are written for a specific purpose. Like, Java was initially devised to control toasters and some other electronics. C was developed for programming OS. Pascal was conceptualized to teach proper programming techniques. But C++ is a general-purpose language. It well deserves the widely acknowledged nickname "Swiss Pocket Knife of Languages." C++ is a cross-platform language that can be used to create high-performance applications. C++ was developed by Bjarne Stroustrup, as an extension to the C language. C++ gives programmers a high level of control over system resources and memory. The language was updated 3 major times in 2011, 2014, and 2017 to C++11, C++14, and C++17. About C++ Programming Multi-paradigm Language - C++ supports at least seven different styles of programming. Developers can choose any of the styles. General Purpose Language - You can use C++ to develop games, desktop apps, operating systems, and so on. Speed - Like C programming, the performance of optimized C++ code is exceptional. Object-oriented - C++ allows you to divide complex problems into smaller sets by using objects. Why Learn C++? C++ is used to develop games, desktop apps, operating systems, browsers, and so on because of its performance. After learning C++, it will be much easier to learn other programming languages like Java, Python, etc. C++ helps you to understand the internal architecture of a computer, how computer stores and retrieves information. How to learn C++? C++ tutorial from Programiz - We provide step by step C++ tutorials, examples, and references. Get started with C++. Official C++ documentation - Might be hard to follow and understand for beginners. Visit official C++ documentation. Write a lot of C++ programming code- The only way you can learn programming is by writing a lot of code. Read C++ code- Join Github's open-source projects and read other people's code. C++ best programming language? The answer depends on perspective and requirements. Some tasks can be done in C++, though not very quickly. For example, designing GUI screens for applications. Other languages like Visual Basic, Python have GUI design elements built into them. Therefore, they are better suited for GUI type of task. Some of the scripting languages that provide extra programmability to applications. Such as MS Word and even photoshop tend to be variants of Basic, not C++. C++ is still used widely, and the most famous software have their backbone in C++. This tutorial will help you learn C++ basic and the advanced concepts. Who uses C++? Some of today's most visible used systems have their critical parts written in C++. Examples are Amadeus (airline ticketing) Bloomberg (financial formation), Amazon (Web commerce), Google (Web search) Facebook (social media) Many programming languages depend on C++'s performance and reliability in their implementation. Examples include: Java Virtual Machines JavaScript interpreters (e.g., Google's V8) Browsers (e.g., Internet Explorer, Mozilla's Firefox, Apple's Safari, and Google's Chrome) Application and Web frameworks (e.g., Microsoft's .NET Web services framework). Applications that involve local and wide area networks, user interaction, numeric, graphics, and database access highly depend on C++ language. Why Use C++ C++ is one of the world's most popular programming languages. C++ can be found in today's operating systems, Graphical User Interfaces, and embedded systems. C++ is an object-oriented programming language which gives a clear structure to programs and allows code to be reused, lowering development costs. C++ is portable and can be used to develop applications that can be adapted to multiple platforms. C++ is fun and easy to learn! As C++ is close to C# and Java, it makes it easy for programmers to switch to C++ or vice versa Definition - What does C++ Programming Language mean? C++ is an object oriented computer language created by notable computer scientist Bjorne Stroustrop as part of the evolution of the C family of languages. Some call C++ “C with classes” because it introduces object oriented programming principles, including the use of defined classes, to the C programming language framework. C++ is pronounced "see-plus-plus." C++ Variables Variables are the backbone of any programming language. A variable is merely a way to store some information for later use. We can retrieve this value or data by referring to a "word" that will describe this information. Once declared and defined they may be used many times within the scope in which they were declared. C++ Control Structures When a program runs, the code is read by the compiler line by line (from top to bottom, and for the most part left to right). This is known as "code flow." When the code is being read from top to bottom, it may encounter a point where it needs to make a decision. Based on the decision, the program may jump to a different part of the code. It may even make the compiler re-run a specific piece again, or just skip a bunch of code. You could think of this process like if you were to choose from different courses from Guru99. You decide, click a link and skip a few pages. In the same way, a computer program has a set of strict rules to decide the flow of program execution. C++ Syntax The syntax is a layout of words, expression, and symbols. Well, it's because an email address has its well-defined syntax. You need some combination of letters, numbers, potentially with underscores (_) or periods (.) in between, followed by an at the rate (@) symbol, followed by some website domain (company.com). So, syntax in a programming language is much the same. They are some well-defined set of rules that allow you to create some piece of well-functioning software. But, if you don't abide by the rules of a programming language or syntax, you'll get errors. C++ Tools In the real world, a tool is something (usually a physical object) that helps you to get a certain job done promptly. Well, this holds true with the programming world too. A tool in programming is some piece of software which when used with the code allows you to program faster. There are probably tens of thousands, if not millions of different tools across all the programming languages. Most crucial tool, considered by many, is an IDE, an Integrated Development Environment. An IDE is a software which will make your coding life so much easier. IDEs ensure that your files and folders are organized and give you a nice and clean way to view them. Types of C++ Errors Another way to look at C++ in a practical sense is to start enumerating different kinds of errors that occur as the written code makes its way to final execution. First, there are syntax errors where the code is actually written in an illegible way. This can be a misuse of punctuation, or the misspelling of a function command or anything else that compromises the integrity of the syntax as it is written. Another fundamental type of error is a compiler error that simply tells the programmer the compiler was not able to do its work effectively. As a compiler language, C++ relies on the compiler to make the source code into machine readable code and optimize it in various ways. A third type of error happens after the program has been successfully compiled. Runtime errors are not uncommon in C++ executables. What they represent is some lack of designated resource or non-working command in the executable program. In other words, the syntax is right, and the program was compiled successfully, but as the program is doing its work, it encounters a problem, whether that has to do with interdependencies, operating system requirements or anything else in the general environment in which the program is trying to work. Over time, C++ has remained a very useful language not only in computer programming itself, but in teaching new programmers about how object oriented programming works.
