Trending December 2023 # Top 18 Web Scraping Applications & Use Cases In 2023 # Suggested January 2024 # Top 21 Popular

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In this article, we focus on web scraping use cases and applications from market research for strategy projects to scraping for training machine learning algorithms.

Data Analytics & Data Science Machine learning training data collection

Machine learning algorithms require a large volume of data to improve the accuracy of outputs. However, collecting a large amount of accurate training data is a big pain. Web scraping can help data scientists acquire the required training dataset to train ML models. For example, GPT-3 which impressed the computer science community with its realistic text generation was built on textual content on the web.

To learn more about web crawler use cases in data science, see our in-depth guide to web scraping for machine learning.

Marketing & sales Price intelligence data collection

For every price elastic product in the market, setting optimal prices is one of the most effective ways to improve revenues. However, competitor pricing needs to be known to determine the most optimal prices. Companies can also use these insights in setting dynamic prices.


Bright Data’s Data Collector is a web scraper that can be used to extract competitors’ pricing data and this is the most common web scraping use case mentioned by most companies in the space.

A web crawler can be programmed to make requests on various competitor websites’ product pages and then gather the price, shipping information, and availability data from the competitor website.

Another price intelligence use case is ensuring Minimum Advertised Price (MAP) compliance. Manufacturers can scrape retailers’ digital properties to ensure that retailers follow their pricing guidelines.

Fetching product data

Specifically, in e-commerce, businesses need to prepare thousands of product images, features, and descriptions that have already been written by different suppliers for the same product. Web scraping can automate the entire process and provide images and product descriptions faster than humans. Below is an example of extracted product data from an e-commerce company website.

To learn more about how you can leverage Amazon data for a competitive edge, check out our in-depth guide on scraping Amazon data.

Brand protection

Using web scraping brands can swiftly identify online content (e.g. counterfeit products) which can hurt your brand. Once this content are identified, brands can take legal action against those responsible:

Counterfeiting: Counterfeiters need to market their products and scrapers allow businesses to identify those products before actual users and protect users from buying fake products.

Copyright infringement is the use of copyrighted works without permission. Web scrapers can help identify whether copyrighted intellectual property is used illegally.

Patent theft is the unlawful manufacturing or selling of licensed products.

Trademark infringement is the illegal use of a logotype, pattern, phrases, or any other elements that are associated with the brand.

Competition research Lead generation Lead prioritization

In addition, signals (e.g. promotions, new hires, new investments, M&A) that are likely to trigger purchasing can be scraped from news or company announcements. This can help companies further prioritize their marketing efforts.

Marketing communication verification

Companies invest billions in spreading their message and especially large brands need to be careful about how their marketing messages are delivered. For example, Youtube got in trouble in 2023 by displaying Fortune 500 links in hateful and offensive videos.

Monitoring consumer sentiment

Analyzing consumer feedback and reviews can help businesses understand what is missing in their products & services and identify how competitors differentiate themselves. Social media data is used by companies in many business use cases including sales and marketing purposes. 

Companies extract consumer data from social media platforms such as Twitter, Facebook, and Instagram by using a social media scraping tool.

To learn more about social media scraping, read our comprehensive guide on social media scraping.

However, there are dozens of software review aggregator websites that contain hundreds of reviews in every solution category. Web scraping tools and open-source frameworks can be used to extract all these reviews and generate insights to improve services and products.

For example, AIMultiple solution pages include a summary of insights from all online sources, helping businesses identify different products’ strengths and weaknesses.

SEO Audit & Keyword research

Search engines like Google consider numerous factors while ranking websites. However, search engines provide limited visibility into how they rank websites. This led to an industry of companies that offer insights on how companies can improve their online presence and rank higher on search engines.

Most SEO tools such as Moz and Ubersuggest crawl websites on-demand to analyze a website’s domain. SEO tools utilize web crawlers for SEO monitoring to

run SEO audits: Scrape their customers’ websites to identify technical SEO issues (e.g. slow load times, broken links) and recommend improvements

analyze inbound and outbound links, identifying new backlinks

scrape search engines to identify different companies’ web traffic and their competition in search engines. This scraping can also help generate new content ideas and content optimization opportunities supporting companies’ keyword research efforts.

scrape competitors to identify their successful strategies taking into account factors like the word count of the different pages etc.

scrape the rank of your website weekly/ annually in keywords you are competing in. This enables the SEO team to take immediate action if any unpredicted rank decrease happens.

Website testing

Webmasters may use web scraping tools to test the website’s front-end performance and functionality after maintenance. This enables them to make sure all parts of the web interface are functioning as expected. A series of tests can help identify new bugs. For example, tests can be run every time the tech team adds a new website feature or changes an element’s position.

Public Relations Brand monitoring

Brand monitoring includes crawling various channels to identify who mentioned your company so that you can respond and act on these mentions to serve them better. This can involve news, complaints & praises on social media.

Trading Data-driven portfolio management

Hedge funds rely on data to develop better investment strategies for their clients. According to Greenwich Associates, an average hedge fund spends roughly $900,000 per year on alternative data source. Web scraping is listed as the largest source of alternative data:

One web scraping example is extracting and aggregating news articles for predictive analysis. This data can be used to feed into their own machine learning algorithms to make data-driven decisions.

Strategy Building a product

The goal of Minimum Viable Products (MVPs) is to avoid lengthy and unnecessary work to develop a product with just enough features to be usable by early customers. However, MVPs may require a large scale of data to be useful to their users, and web scraping is the best way to acquire data quickly.

Market research Support functions Procurement

There are various job portals such as Indeed and Times Jobs where candidates share their business experience or CVs. A web scraping tool could be utilized to scrape potential candidates’ data so that HR professionals can screen resumes and contact candidates that fit the job description well. However, as usual, companies need to ensure that they do not violate T&Cs of job portals and only use public information on candidates, not their non-public personal information (NPPI).

AI has significant use cases in HR, for example by automating CV screening tasks and frees up a significant amount of the HR team’s time. For example, candidates’ career progression after joining a new company can be correlated with their educational background and previous experience to train AI models on identifying the right candidates. For example, if those with engineering backgrounds and with a few years of marketing experience in a marketing agency, end up getting promoted fast in a marketing role in a certain industry, that could be a valuable information for predicting the success of similar candidates in similar roles. However, this approach has significant limitations, for example Amazon’s recruiting tool was identified to be biased since it relied on such historical data.

Explore web crawling use cases in recruiting in our in-depth article.

Technology Website transition

For companies that operate on a legacy website and transfer their data to a new platform, it is important to ensure that all their relevant data is transfered to the new website. Companies operating legacy websites may not have access to all their website data in an easy to transfer format. Web scraping can extract all relevant information in legacy websites.

If you still have any questions about web scraping, feel free to read our in-depth whitepaper on the topic:

If you are looking for a web scraping vendor, feel free to check our sortable and regularly updated vendor lists or contact us:

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.





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Web Scraping: For And Against

There’s no doubt that we’re in a very complicated time in terms of personal data. Most uneducated consumers don’t realize how much sensitive information is traded each time they log in to their favorite social media apps or use an in-home electronic assistant.

In turn, they’re unsuspectingly leaving hordes of details about their private lives out for anyone (or any corporation) to expose.

And that’s where web scraping comes in. Also referred to as web harvesting or web data collection, this process involves specialized software that collects information from a website and compiles it for other uses. Just like any other technological tool, the process can be used for both positive and negative purposes.

Here are a few things to consider when looking at the argument of whether web scraping should be considered illegal.

Positive: Compilations of Data, Facts, and Figures

There are numerous benefits of using data scraping, and many businesses around the globe use the byproduct of this practice, whether they know it or not.

Those who feel data harvesting is not a threat, often cite the ability to compile data together from multiple websites in an easy and cost-effective fashion. From this perspective, the general thought is that anything put out on the internet is the same as having it in public view, thus making it general knowledge.

In some cases, they’re right. Web scraping powers the Wayback Machine, a website dedicated to providing previous editions of websites in a clear and easy-to-use manner.

This program makes it easy to look back at previous data, which is definitely a positive. But the technology used to attain the information is what concerns many in the industry.

Also read: How to Start An E-commerce Business From Scratch in 2023

Negative: Difficult to Interpret and Invasion of Personal Privacy

However, there is a downside to the process of web scraping and using personal data for business purposes.

From a technical perspective, harvested data isn’t always easy to interpret or gives you the information you really need. For example, the information scraped using a software program might just be gibberish without any real context. It can also be the wrong information or data that has no real significance on the business you’re trying to conduct.

But the biggest and most hotly contested factor doesn’t deal with technical limitations. Rather, it has to do with the public’s understanding of web scraping and whether it is really an invasion of personal privacy.

Many individuals feel that any outside entity’s ability to pull random data from various public websites and compile it to come up with a specific conclusion is a form of privacy invasion. But, whether they like it or not, it isn’t really all that uncommon.

Marketing companies use this process all the time to try and predict likes, dislikes, and future moves of consumers. They have been doing so for a very long time.

Protections Against Web Scraping and Data Mining

What this all basically comes down to is that website owners are responsible for protecting their customers and users from actions like web scraping and data mining.

By keeping certain sensitive pieces of information private, like banking transaction details or contact information, these organizations can help limit their risk of a breach and ensure positive customer satisfaction.

While that kind of sounds like a no-brainer, it really isn’t always the normal course for some major platforms. For example, Venmo got into a bit of hot water in 2023 by publicly publishing all transactions and keeping them in a database.

This meant that anyone who had a specific user’s username could see every single time they paid for a cup of coffee or sent a roommate half of the month’s rent.

Also read: 5 Best Resource Capacity Planning Tools for Teams

Wrap Up: Pros and Cons of Web Scraping

Like with anything else in tech, there are certainly pros and cons to web scraping. While the process isn’t a big deal when it comes to innocent or general information, it can cause huge problems when you’re talking about very specific details about a website user’s lifestyle.

Thus, it is incredibly important for all website owners to pay extra attention when it comes to protecting certain pieces of data, as the practice is so widely used that it isn’t likely to go away anytime soon.

Overview And Top Applications Of Kafka

Overview of Kafka Applications

One of the trending fields in the IT industry is Big Data. The company deals with a large amount of customer data and derives useful insights that help their business and provide customers with better service. One of the challenges is handling and transferring these large volumes of data from one end to another for analysis or processing; this is where Kafka (a reliable messaging system) comes into play, which helps in the collection and transportation of a huge volume of data in real-time. Kafka is designed for distributed high throughput systems and is a good fit for large-scale message processing applications. Kafka supports many of today’s best commercial and industrial applications. There is a demand for Kafka professionals having strong skills and practical knowledge.

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Hadoop, Data Science, Statistics & others

This article will learn about Kafka, its features, use cases, and understand some notable applications where it is used.

What is Kafka?

Apache Kafka was developed at LinkedIn and later became an open-source Apache project. Apache Kafka is a fast, fault-tolerant, scalable and distributed messaging system that enables the communication between two entities, i.e. between producers (generator of the message) and consumers (receiver of the message) using message-based topics and provides a platform for managing all the real-time data feeds.

The features that make Apache Kafka better than other messaging systems and applicable to real-time systems are its high availability, immediate, automatic recovery from node failures and supports low latency message delivery. Apache Kafka’s features help integrate it with large scale data systems and make it an ideal component for communication.

Top Kafka Applications

This section of the article will see some popular and widely implemented use cases and see some real-life implementation of Kafka.

Real-Life Applications 1. Twitter: Stream Processing Activity

Twitter is a social networking platform that uses Storm-Kafka (an open-source stream processing tool) as a part of its stream processing infrastructure. In turn, input data(tweets) are consumed for aggregation, transformations, and enrichment for further consumption or follow-up processing activities.

2. LinkedIn: Stream Processing & Metrics

LinkedIn uses Kafka for streaming data and operational metrics activity. LinkedIn uses Kafka for its additional features, such as Newsfeed, for consuming messages and performing analysis on the data received.

3. Netflix: Real-time Monitoring & Stream Processing

Netflix has its own ingestion framework that dumps input data in AWS S3 and uses Hadoop to run analytics of video streams, UI activities, events to enhance the user experience, and Kafka for real-time data ingestion via APIs.

4. Hotstar: Stream Processing

Hotstar introduced its own data management platform- Bifrost, where Kafka is used for data streaming, monitoring, and target tracking. Because of its scalability, availability, and low-latency capabilities, Kafka was ideal for handling the data that the Hotstar platform generates daily or on any special occasion (live streaming of any concerts, or any live sports match, etc.) where the volume of data increases significantly.

For these types of use cases, we would want to stream our input data / raw data into a data lake to store our data and ensure data quality without hampering the performance.

A different situation, we might be reading data directly from Kafka, is when we need extremely low end-to-end latency, like feeding data to real-time applications.

Kafka lays out certain functionalities to its users :

Publish and subscribe to data.

Store data in the order they were generated efficiently.

Real-time / On-the-fly processing of data.

Kafka, most of the time, is used for:

Implementing on-the-fly streaming data pipelines that reliably get data between two entities in the system.

Implementing on-the-fly streaming applications that transform or manipulate, or process the streams of data.

Use Cases

Below are some widely implemented use cases of the Kafka application:

Kafka works better than other traditional messaging systems such as ActiveMQ, RabbitMQ, etc. In comparison, Kafka offers better throughput, built-in partition facility, replication, and fault-tolerance capabilities, making it a better messaging system for large scale processing applications.

2. Website Activity Tracking

User activities (page views, searches, or any actions) can be tracked and fed for real-time monitoring or analysis via Kafka or Kafka to store these kinds of data into Hadoop or data warehouse for later processing or manipulation. Activity tracking generates a huge amount of data that needs to be transferred to the desired location without losing data.

3. Log Aggregation

Log aggregation is a process of collecting/merging physical log files from different servers of an application into a single repository (file server or HDFS) for processing. Kafka offers good performance, lower end-to-end latency when compared to Flume.


Kafka is used heavily in the big data space to ingest and move large amounts of data very quickly because of its performance characteristics and features that help achieve scalability, reliability, and sustainability. In this article, we discussed Apache Kafka its features, use cases, and application, making it a better tool for streaming data.

Recommended Articles

This is a guide to Kafka Applications. Here we discuss what is Kafka along with the top applications of Kafka, which include widely implemented use cases and some real-life implementation. You may also look at the following articles to learn more-

Top Programming Languages Powering Fintech Applications In 2023

Analytics Insight has listed major programming languages that are changing the face of fintech


Top five programming languages for fintech

  Java C++ C++ is a cross-platform language that can be used to create high-performance applications. It is an object-oriented C++ was developed by Bjarne Stroustrup, as an extension to the C language. The magic of C++ is that the language is closer to machines than other programming languages, making its frequency very high. In the C++ programming and that makes the language a must be known for job seekers.   Haskell Haskell is a widely used functional programming language that is based on mathematical functions. The language is named for Haskell Brooks Curry, whose work in mathematical logic services as a foundation for functional languages. Extraordinary features like a balance of flexible and inflexible qualities make Haskell a fascinating programming language to learn and use. Programmers can now relieve themselves from writing large software systems, thanks to emerging Python Python is an interpreted, object-oriented, high-level SQL

The fintech industry across the world is very receptive to disruptive technologies. The increase in transaction rates and the low risk on tolerance have surged the need for applications that can streamline the banking process. Unfortunately, before employing the applications directly on fintech , we need to develop or program them. Banks have been directly connecting with IT firms or hiring programmers to carry out the job. The programmers are expected to be well versed in programming languages . Programming is the process of writing instructions for a computer or an application to perform. Even though they don’t expect the candidate to know all programming languages , the professionals should at least be fluent in some of them. When programmers work on a fintech projects, they should consider technical and business requirements and the banks’ specific needs. Analytics Insight has listed major programming languages that are changing the face of fintech in 2023 Java is a general-purpose, class-based, object-oriented programming language designed for having lesser implementation dependencies. It is one of the most used programming languages that are also featured in the computing platform. Java was first released by Sun Microsystems n 1995. It is well known and fast adopted for its secure and reliable features. Remarkably, the fintech industry is embracing java to power its systems and applications. Java also offers everything companies in fintech need to develop robust apps that customers can rely on to assist with their requirements. It is openly accessible in a variety of OD platforms including iOS, Android, Windows, Linux, and others. Henceforth, Java carries the luxury to provide companies with an extensive audience base without necessitating expensive investments. Java’s extensive features like Java Virtual Machine leverages byte code, type safety, garbage collection, etc that helps companies entrust the language for fintech apps.C++ is a cross-platform language that can be used to create high-performance applications. It is an object-oriented programming language that gives a clear structure to programs and allows code to be reused, lowering development costs. C++ is famous for its portable accessibility that is used to develop applications that can be adapted to multiple platforms. Besides, it is also simple in the sense that programs can be broken down into logical units and parts, and has rich library support and a variety of data chúng tôi developed by Bjarne Stroustrup, as an extension to the C language. The magic of C++ is that the language is closer to machines than other programming languages, making its frequency very high. In the fintech industry, a good number of programmers use the C++ language. Most of the professionals in fintech are also good atprogramming and that makes the language a must be known for job seekers.Haskell is a widely used functional programming language that is based on mathematical functions. The language is named for Haskell Brooks Curry, whose work in mathematical logic services as a foundation for functional languages. Extraordinary features like a balance of flexible and inflexible qualities make Haskell a fascinating programming language to learn and use. Programmers can now relieve themselves from writing large software systems, thanks to emerging programming languages like Haskell that make it easier and cheaper to develop applications. Fintech companies use Haskell because of its properties that imperative programming doesn’t provide. It is also great in handling blockchain, immutability, type safety, and the ability to manage distributed computation well.Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It is widely adopted by programmers for its high-level build-in data structures, combined with dynamic typing and dynamic binding. Besides, it can be easy to pick up for both first-timers and well-experienced programmers. Python also provides increased productivity that programmers look for in a programming language. It was created by Guido van Rossum, and released in 1991. Python rose to popularity and has been demonstrated by numerous financial companies after job postings required the language from developers since 2023. Widespread across the investment banking and hedge fund industries, banks are suing Python to solve quantitative problems for pricing, trade management, and risk management chúng tôi is also known as Structured Query Language, is a standard language for accessing and manipulating databases. It features database creation, deletion, fetching rows, modifying rows, etc. Even though SQL is an ANSI (American National Standard Institute) standard language, there are many different versions of the SQL language that has emerged from the core. It can also perform exclusive operations like optimizing and maintaining databases. For a fintech company, SQL is used to analyze consumer data. Doing so will help them identify seasonal variations in demand or consumption patterns.

Top 10 Blowhards Of The Web

On the Web, no one can hear you scream. But no one can stop you, either.

The term for speaking or writing verbosely and windily is bloviation; and to judge from their output, certain online practitioners are more adept than a pod of humpback whales at endlessly spouting vaporous nothings. Some even make a living at it.

Photograph: Thomas Hawk, Zooomr, Inc.A former Microsoft suit and perennial Valleywag whipping boy, Scoble excels at saying nothing about absolutely everything. (Typical headline: “RSS: interesting or boring?”) These days he mostly just plugs his Web host employer Rackspace and interviews a stream of utterly random Web execs, but he can still get his dander up over the most banal of tech topics. (Please don’t get him started on what he thinks about FriendFeed!) Scoble and his camera crew have long been a staple at even the most minor of high-tech events; and at the approach of this entourage, most people scurry for the bar or the buffet.

Then, last month, after the hideaway hubbub had faded, a British court found him guilty of libel and “sustained character assassination,” all but banishing him from the shores of England lest he be arrested at the airport. (In fairness to Arrington, he refused to defend himself against the charges.) The upshot is that his future exile options have diminished.

As hoary old sacred cows go, none are closer to “downer” cattle than the venerable John C. Dvorak, who has been expounding on computers since before computers were invented. Dvorak’s official bio claims that the man has written more than 4000 articles, a number that seems small in view of his omnipresence.

Jason Calacanis is to Nick Denton as Donald Trump is to Warren Buffett. A serial entrepreneur, Calacanis has made a living off of building smallish, dot-commy businesses and then selling them off to outfits with much less business savvy. His biggest hit: Selling Weblogs, Inc. (home of the mega-tech site Engadget) to America Online, reportedly for more than $25 million. His latest play: chúng tôi a human-powered search engine that seems to have dedicated itself to the goal of beating Wikipedia to the top of the list on a variety of common Google search-term results.

Photograph: Courtesy of Huffington PostWhether you’re a political junkie or a borderline anarchist, you can’t easily escape the Web publishing machine that is Arianna Huffington (born Arianna Stassinopoulos in 1950). Despite sounding as though it would be exclusively about herself–seriously, what else could “The Huffington Post” cover?–Huffington’s “HuffPo” Web newspaper has arguably become the leading liberal political Web site (er, excuse us, “media brand”) on the Net.

Kudos to Huffington for building up her brand to the point where she has become a household name. Pity, though, about that run for California governor. And the plagiarism lawsuit.

After decades of toiling in software startups that you’ve never heard of, Winer was in the right place at the right time and became a pioneering force during the early days of the Web. Nevertheless, he’s still working off the chip on his shoulder that came from inventing RSS and (debatably) blogging itself without receiving adequate credit for them. Winer caused his biggest disturbance in the Force when he abruptly (albeit temporarily) shut down his free blog-hosting service, chúng tôi leaving thousands of users in the dark. Hates everyone. Tried to push the idea of providing a permalink to every paragraph in a blog, as if it were a Bible verse.

Want to know what the 2874th line of your Windows Registry really means? Paul Thurrott will tell you. In a seven-part, 5000-word blog post (bonus: with screenshots!). But Thurrott is perhaps most notable for his tendency to compose angry-sounding blog entries aimed at anyone who dares criticize Windows, as demonstrated in this hilarious blog by one of Thurrott’s targets, ZDNet’s Ed Bott.

Holier than thou and–more important–smarter than thou, Coursey (the “Tech Inciter“) pushes the hot-topic buttons of the day while expounding on his superior knowledge of everything from iPhone architecture to how the First Amendment should be interpreted.

Of course he does all this for PC World, so we forgive him: He may be an opinionated loudmouth, but he’s our opinionated loudmouth.

Top 10 Full Stack Web Development Courses To Take Up In 2023

Ever wondered what forms the base of innovative and interesting applications like Swiggy, IMDB, Quora, etc.? Well, full-stack web development plays a pivotal role here. Yes, a career in full-stack web development is quite promising which is why the number of people looking forward to making a career in the same seems to be increasing with every passing day. If you are in the race of becoming a successful full-stack developer, you need to prep up to face the competition. Well, we have made it easier for you. In this article, we will talk about the top 10 full-stack web development courses to take up in 2023. Have a look!

The Advanced Web Developer Bootcamp

“The Advanced Web developer Bootcamp” is a course brought to you by Udemy. This vast full-stack development course takes you through a wide range of topics including React 16, Redux, D3, ES2023, Testing, CSS Flexbox, Animations, SVG, AJAX and so many more. This is a 30+ hours video that has been designed to give you a detailed overview of web development.

Web Design for Everybody: Basics of Web Development & Coding Specialization

As the name suggests, this Udemy course is exclusively designed to focus on the basics of full-stack web development. It takes about 6 months to get done with the course. The best part? Well, the course is absolutely free! You can make the best possible use of this, right?

Learn to Code

How about a course that enables you to understand the basics of programming using HTML, CSS, and Python? This is exactly what “Learn to code” has in store for you to offer. This web development course is designed in a manner that will give you enough knowledge to think and get a logical solution like a programmer in the least possible time.

The Complete 2023 Web Development Bootcamp

Now, this undoubtedly has to be one of the best full-stack developer courses available out there as it enables you to learn front-end technologies like HTML, MongoDB, CSS, JavaScript, Node, and more. This is just the kind of certification course you need to be able to learn how to build a website for your business or startup. By the end of this course, you will be able to learn best practices to develop websites.

Full-Stack Web Development with React Specialization

This Coursera course, covering both React and Bootstrap, teaches you how to build a hybrid mobile app. How amazing is that? With this course, you will not only be able to gather knowledge about implementing NoSQL databases using MongoDB, chúng tôi and Express framework but also get to work on a project, the successful completion of which will give you a certificate.

Beginner Full Stack Web Development

Yet another full-stack web development case that is beginner friendly is this one from Udemy. It helps you learn front-end technologies like web development with HTML, CSS, ES6 React, bootstrap 4, and Node, enabling you to develop a backend server and API. All in all, this is a good course to go about if you intend to build a mobile-friendly website.

Full-Stack Web Development with Angular Specialization

If you are interested in understanding how technologies like chúng tôi and MongoDB are used for communicating with Restful API, then this full-stack development course is all you need. Additionally, it provides a hands-on project that you need to successfully complete to get a certification.

Become a Full-Stack Web Developer

LinkedIn, too, has a good number of courses on web development and this is one of the most sought-after ones. This course aims at teaching you to get the necessary skills needed to work for both the front end and back end and provides you with a solid foundation for working with server configuration, database integration, and creating dynamic data-driven websites. No wonder, why this makes it to the list of top 10 full-stack web development courses to take up in 2023.

Full Stack Web Developer by Udacity

This course majorly focuses on the skills required to build API and web applications. You get good information on designing and building databases for software applications here. To proceed with this course, you require basic knowledge of testing applications using data science technologies like Python, HTML, CSS, and Git. This is definitely one of the best courses available to become a successful full-stack web developer.

Web Development Course by Codecademy

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